Pay and flexible working top the list of things that experienced hires are after – and if you can’t offer both, then you’ll need to consider lowering your expectations in a competitive market.

The Big Two: pay and flexibility 

Job seekers in tech have spoken: the most important priorities for tech candidates are compensation (yes, pay), followed by flexible working arrangements. 

The ‘Big Two’ factors are also ranked the fastest-growing priorities year over year, according to LinkedIn’s recent research, The Future of Recruiting 2023.

So, the thorny issue of pay – the one thing you were never supposed to mention at an interview – is now the key thing people are looking to know upfront. That, followed by the expectation that they can be fully remote if they want to be.

Why are employers reluctant to talk about pay?

Very few employers like to get out there and say “we pay great salaries.” Of course, everyone thinks that they offer above the market average, but few lead with it. Why? 

Because generally, most businesses don’t want to hire people who they perceive are motivated solely by money, because, in their mind, they’re harder to keep happy. And that’s why traditionally, job ads follow the same predictable structure: company size, clients, tech stack, and a touch of benefits (progression plans and training). But pay? That’s usually left until the second interview, by which both sides may be wasting their time.

Changing priorities, challenging times

So why are pay and flexible working driving the market? Two reasons.
On the pay front – it’s pretty obvious. We’ve got a cost of living crisis. Rising inflation, stagnating real wages. Job seekers literally can’t afford to be coy about what they can expect from their wage packet.

Flexible working, on the other hand, is a hangover from the pandemic. Hires, especially experienced ones, have grown used to a new way of working and they’re unwilling to go back, certainly not in the way they were used to.

Why it matters to employers

Frankly, if you’re not offering the ‘big two’ as an employer, you’re not just slightly behind, you’re way behind – to the point where you might not even be shown CVs for experienced hires. And that’s an issue, when you’re trying to recruit and keep people. It’s an issue for all sectors, of course, but it’s particularly prevalent in tech because the demand for skills is so high. 

In tech, hires can afford to be picky

While some companies are forcing people back to the office, in tech, employees can afford to be picky. In a sector where people are being approached once, twice a week for their skills: there’s always someone, somewhere who can offer better money and better flexibility. If you’ve got a loyal tech employee, then you’ve done something right; they’re working with you because they want to be there. 

Can’t offer more? There is an alternative.

We get that not all companies are in a position to offer high or better salaries, and not all companies are able, or willing, to offer flexible working. Assuming you don’t want to go offshore, there’s one way around that. 

Hire people who are less experienced and/or more junior than you would’ve considered. 

This can work, and here’s why: junior candidates are more likely to want to come into the office. They’re less likely to have family duties, which are a real benefit to home workers. Going into the office four days a week doesn’t require major adjustments in their personal lives to accommodate. Of course, juniors will still look to their peers and see flexible working happening there and would likely expect at least one day from home, so you’ll need to factor this into your offer, too.  

Want great hires? Think pay & flexibility first

In a nutshell: if you want experienced candidates, then a good salary and significant flexibility in working hours are an absolute must. If you haven’t, then by definition, you’re automatically shopping in a junior market.

Cybersecurity has traditionally been treated as a technology issue. IT teams manage systems, security specialists monitor threats, and technical teams respond when something goes wrong. 

That model is becoming harder to sustain. 

Technology now sits across almost every part of a business. Customer information, financial systems, operations, communications and supply chains all depend on digital infrastructure. As a result, a serious cyber incident can quickly become a business continuity, financial and reputational issue rather than an isolated IT problem. 

The UK’s approach to cyber resilience is reflecting this shift. The Government’s 2026 Cyber Resilience Pledge makes “cyber a Board responsibility”. Its first commitment: requiring participating organisations to implement the actions in the Cyber Governance Code of Practice and ensure board members undertake NCSC cyber-governance training. 

For businesses, particularly those going through digital transformation, the question is not whether cybersecurity matters. It’s who is accountable for it. 

Cyber Risk Is A Business Risk 

The scale of the problem makes this difficult to treat as purely technical. 

The UK’s 2025/2026 Cyber Security Breaches Survey found that 43% of businesses had experienced a cyber breach or attack during the previous 12 months. That included 65% of medium-sized businesses and 69% of large businesses. 

The same survey found that only 36% of businesses had a formal cyber security policy and just 25% had a formal incident response plan. It also found that the proportion of medium-sized businesses receiving cyber security updates at least annually at board level had fallen from 78% to 70%. 

These figures do not suggest that businesses are ignoring cybersecurity. They do, however, highlight a potential gap between having technical protections and having cyber risk properly embedded into organisational decision-making. 

A security team can identify vulnerabilities. It cannot, on its own, decide how much operational disruption the business can tolerate, which services are most critical or what level of investment is appropriate. 

Those are leadership decisions. 

The Board Does Not Need to Become a Security Team 

Making cybersecurity a leadership responsibility does not mean asking directors to become cybersecurity specialists. 

The NCSC’s Cyber Governance Code of Practice is specifically designed for boards and directors rather than the people responsible for day-to-day cyber security management. It focuses on governance, accountability, risk management, assurance and oversight. 

Senior leaders need enough understanding to ask the right questions and make informed decisions. They do not necessarily need to understand every technical control behind the answers. 

A board might reasonably ask: 

• What are our most important systems and data? 

• What would happen if one of them became unavailable? 

• Which risks are we actively managing, and which are we accepting? 

• How quickly could we recover from a serious incident? 

• Are our suppliers creating additional exposure? 

• Who has authority to make decisions during an incident? 

• Are we investing in the areas of greatest risk? 

The answers should come from the people with the relevant technical expertise. But leadership needs to understand what those answers mean for the organisation. 

Cybersecurity Extends Beyond the IT Department 

Modern businesses rarely operate entirely within their own technology environment. 

They depend on cloud platforms, software providers, managed services, payment systems, data suppliers and other third parties. Employees may also access business systems from different locations and devices. 

That makes the boundaries around cybersecurity less clear. 

The Government’s 2026 Cyber Security Longitudinal Survey found that 67% of medium and large businesses had at least one board member whose role included oversight of cyber security risks, while 71% had a designated cyber security staff member reporting directly to the board. 

External support can be valuable, but outsourcing a technical function does not necessarily outsource accountability. 

If a critical supplier suffers an incident, the consequences may still fall on the business and its customers. 

Leadership therefore needs visibility of the wider technology environment, not just the systems directly controlled by the internal IT team. 

The Role of Technology Leaders Is Changing Too 

This shift has implications for CIOs, CTOs, IT Directors and other technology leaders. 

They increasingly need to translate technical risk into business terms. 

That might mean explaining why a particular investment is necessary, helping the board understand a supplier risk, deciding where resilience needs strengthening or working with operational leaders to establish what should happen during an incident. 

The technology leader does not necessarily own every business risk. 

But they may be responsible for making sure the organisation understands the technology risks that contribute to those wider business risks. 

That requires a combination of technical knowledge, communication, commercial awareness and the ability to work across organisational boundaries. 

Cybersecurity should be considered when roles are designed 

This also raises a question for organisations reviewing their technology structures. 

As cyber risk becomes more closely connected to business operations, organisations need to consider whether their current leadership structure provides enough ownership and expertise. 

That does not automatically mean creating a new senior security position. 

For some businesses, responsibility may sit with an existing technology leader. Others may need dedicated security expertise, stronger governance or clearer responsibilities between technology and business functions. 

The important point is to define the requirement around the organisation’s actual risk and operating model. 

This is particularly relevant for growing businesses. A structure that was appropriate when an organisation had a small internal IT function may become less suitable as it introduces more cloud services, handles more data, expands its supplier network or becomes increasingly dependent on digital systems. 

Regulation Is Adding to the Pressure 

The UK’s Cyber Security and Resilience Bill is another indication that cyber resilience is becoming a broader organisational responsibility. 

As of September 2026, the Bill has completed its committee stage in the House of Lords. Parliamentary scrutiny has included proposed changes concerning incident reporting, data centres, service providers and the liability of senior executives. The Bill is intended to strengthen cyber security requirements for organisations providing essential services, update incident-reporting duties and bring additional sectors into the regulatory framework.  

The Bill is still progressing through Parliament, so organisations should not treat its proposed provisions as final requirements. Report Stage is currently scheduled for 26 October 2026.  

The broader direction is towards treating cyber security as an organisational resilience issue, with responsibilities extending beyond technical teams and into wider business oversight and accountability. 

The Right Question Is Ownership 

For technology leaders, the challenge is not to make everyone responsible for cybersecurity. 

It’s to make sure the right people are responsible for the right decisions. 

Technical teams need the expertise to identify and manage security risks. Business leaders need to understand how those risks could affect operations and make decisions about priorities and investment. Boards need sufficient oversight to challenge, support and hold the organisation accountable. 

That requires clear ownership rather than simply adding more processes. 

As technology becomes more deeply embedded in how businesses operate, cybersecurity becomes part of the wider conversation about resilience, risk and leadership. 

The organisations that manage this effectively will not necessarily be those with the largest security teams. They will be those that understand where responsibility sits, have the right expertise available and ensure cyber risk is considered alongside other important business decisions. 

Building The Right Technology Leadership Structure 

For businesses reviewing their technology organisation, cybersecurity is now part of a wider question: does the current leadership structure reflect the organisation’s reliance on technology and the risks that come with it? 

At Bristow Holland, we work with organisations across the technology and change landscape, helping them consider how their technology leadership needs to evolve as the business changes. 

That might mean strengthening an existing team, redefining responsibilities or introducing a new capability. The starting point is understanding what the organisation needs its technology leadership to achieve – including how it manages risk, resilience and security. 

If you’re considering your technology leadership structure, responsibilities or approach to cyber risk, I’d be happy to discuss what that could look like in practice.  

Contact me,  
Andy Bristow

Many businesses are reaching a point where their technology setup starts to feel wrong. 

The systems have multiplied. Different departments use different platforms. Employees have developed workarounds. The IT team is busy dealing with day-to-day problems, while the leadership team is asking bigger questions about automation, AI, efficiency and growth. 

At some point, the problem may not be the technology, it may be the structure around it. 

For a growing company, having a traditional IT function that operates separately from the wider business can make it harder to turn technology into a source of efficiency and growth. 

The question for CEOs is therefore worth asking: Does your technology leadership structure still match the business you are trying to build? 

Traditional IT Structures Are Changing 

Traditionally, IT had a fairly clear purpose. 

They were responsible for keeping systems running, maintaining secure networks, supporting employees and managing the hardware, software and suppliers needed to keep the business operating. These responsibilities remain essential. A business cannot function effectively if its technology is unreliable or insecure. 

But technology now reaches much further into the organisation. The Department for Business and Trade’s 2026 update on SME digital adoption highlights the role of digital technology in improving SME productivity and reports ongoing work to make adoption support more accessible to businesses. The update includes work on a scalable online CTO function to provide guidance and support to SMEs. 

That changes the leadership question. If technology affects the way almost every department works, should responsibility for technology leadership sit entirely within an IT function? 

Technology Leaders Need to Understand Business Strategy 

A modern technology leader should understand not only which systems the business uses, but why they are being used and what they contribute to the organisation. 

That means being involved in conversations about business strategy, operational efficiency, customer experience, data and growth. Whether the business is entering new markets, looking to reduce administrative costs, improve customer service or introduce AI, technology should be considered as part of the wider solution. 

The technology leader should be able to identify where technology can create genuine value and where it may not be the answer. 

This is a much broader responsibility than traditional IT management. 

Digital Transformation Needs Long-Term Technology Ownership 

One of the problems with treating digital transformation as a separate project is that transformation eventually has to become normal business operations. 

A new platform gets implemented. 

A process gets redesigned. 

Automation is introduced. 

Employees are trained. 

The project is declared complete. 

Then what? 

Someone still has to own the technology, measure whether it is delivering the expected benefit and identify what should happen next. 

Digital transformation is not simply about implementing a new system and moving on. As technology becomes more closely connected to business strategy, organisations need ongoing technology leadership. The UK Government’s 2026 Chief Digital and Data Leader Programme reflects this broader approach, helping experienced technologists develop the strategic, commercial and leadership skills needed for senior digital and technology roles. 

This creates a strong case for bringing the responsibilities together. 

Rather than having one person responsible for keeping IT operational and another responsible for transforming the business through technology, a growing SME may benefit from a broader technology leadership role. 

How a Technology Leader Can Connect IT and Business Strategy 

For a medium-sized business, this does not necessarily mean building a large digital department. 

In fact, efficiency can mean doing the opposite. 

A single senior Digital Transformation or Technology leader can own the relationship between business strategy and technology. 

They don’t need to personally manage every support issue, device or technical incident. 

Operational responsibility can sit with IT team leaders and specialists. 

That creates a different structure. 

The senior leader looks ahead. 

The operational team keeps the business running. 

The two functions remain connected because they ultimately sit within the same technology strategy. 

What Should CEOs Look for in a Technology Leader? 

The title matters less than the capability. 

A business does not necessarily need a traditional IT manager with a new job title. 

Nor does it necessarily need a large-company CIO. 

It needs someone who can understand the organisation’s strategy and determine how technology can help deliver it. 

That person should be able to move comfortably between the boardroom and the technology team. 

They should understand enough about infrastructure, cybersecurity, systems and technical risk to make informed decisions. 

But they should also understand processes, commercial priorities, budgets, people and change. 

Most importantly, they should be able to explain why a technology decision matters to the business. 

The UK’s 2026 SME Digital Adoption Taskforce update is telling in this respect. The government has completed an 8-week discovery into using a scalable online CTO function to help SMEs adopt digital technology, with services being integrated into the Business Growth Service and Business.gov.uk. 

The underlying problem is not simply access to technology. 

It’s access to the capability to use technology well. 

Signs Your IT Structure Is Holding Your Business Back 

There are some straightforward warning signs: 

Your IT manager spends most of their time dealing with operational issues and has little time for strategic work. 

Technology projects are initiated by individual departments without a clear overall roadmap. 

The business systems are poorly integrated with many overlapping workflows. 

Employees regularly duplicate information between systems. 

The leadership team discusses business strategy without involving technology leadership. 

The IT function is measured primarily on whether things are working rather than whether technology is improving the business. 

Transformation projects are treated as temporary initiatives with no clear long-term owner. 

Or perhaps the simplest sign is this: 

You have technology everywhere, but nobody clearly owns how technology should help the business perform better. 

If that sounds familiar, adding another system may not be the answer. 

Changing the leadership structure might be. 

Why SMEs May Need Smaller, More Strategic Technology Teams 

Technology does not necessarily require a larger headcount as it becomes more important. 

It can require better allocation of responsibility. 

Modern platforms can reduce the amount of internal resource required for routine infrastructure and support. Automation can reduce manual work. Managed services can provide specialist capabilities where maintaining them internally would not make sense. 

That can allow the business to put more emphasis on the person connecting technology to strategy. 

The result may be a relatively lean technology function led by someone with a much broader remit, supported by operational team leaders and specialists. 

For a medium-sized business, that can be more efficient than maintaining separate layers of IT management and digital transformation leadership. 

How CEOs Can Build a Future-Ready Technology Function 

The issue is not whether your current IT manager is good enough. 

They may be excellent at what they do. 

The question is whether the role itself is still broad enough for what the business needs. 

Technology is no longer simply the function that keeps computers and systems running. 

It increasingly shapes how the business operates. 

That means someone needs to own the connection between business strategy, processes, people and technology. 

For some SMEs, that may mean developing an existing IT leader into a broader technology leadership role. 

For others, it may mean hiring someone with transformation experience who can take ownership of both strategic technology and operational delivery. 

Either way, the objective is the same: 

Technology should not simply support the business. It should help the business deliver its strategy. 

At Bristow Holland, we specialise in senior technology leadership across the East of England and increasingly we’re helping businesses think through exactly this challenge. 

Sometimes the answer is developing the technology leadership capability already within the business. Sometimes it’s redefining an existing role. And sometimes it’s bringing in a different type of technology leader altogether. 

If you’re a CEO, CFO or business leader questioning whether your current technology structure is right for where the business is heading, get in touch with me for a confidential conversation. 

Andy Bristow 

Bristow Holland 

Technology leadership used to be relatively easy to define. 

The senior technology person looked after the systems, infrastructure, users and technical team. They kept the network running, maintained systems, resolved problems, managed suppliers and made sure the business had the technology it needed to operate. 

Those responsibilities still matter. But for many UK businesses, particularly growing small and medium-sized enterprises (SMEs), they are no longer enough. 

Technology now touches almost every part of a business: how employees work, how customers interact with it, how information moves between departments, how decisions are made and how efficiently processes operate. 

As a result, the question being asked of technology leaders is changing. 

It is no longer simply: 

“How do we keep IT running?” 

CEOs and CFOs increasingly want to know: 

“How can technology help us run this business better?” 

How can we get greater visibility from our data? Where can we automate manual processes? How can AI genuinely improve the way we operate? How can systems work together more effectively? And where should we invest to support growth? 

That requires a broader type of technology leader. 

Technology Leaders Need to Understand Business Strategy 

The UK government is also recognising the importance of helping SMEs adopt technology more effectively. The Department for Business and Trade’s 2026 update on the SME Digital Adoption Taskforce reports progress on measures to improve SME digital adoption, while the taskforce’s earlier recommendations included a scalable CTO-as-a-service model providing AI-powered guidance and support to SMEs.

That reflects a much wider change in how technology is viewed. 

Technology can no longer sit neatly in its own department while the rest of the business decides what it wants to achieve. 

It increasingly forms part of how the business achieves those objectives. 

A business trying to reduce costs might need automation and better-integrated systems. 

A business trying to improve customer service might need better access to data and a more joined-up customer journey. 

A business trying to grow might need scalable platforms, improved reporting and processes that do not depend on spreadsheets and manual workarounds. 

These are business challenges, not simply IT projects. 

The technology leader therefore needs to understand the strategy of the organisation before deciding what technology it needs. 

Keeping the Lights On Is No Longer Enough 

None of this makes operational technology expertise obsolete. 

A credible technology leader still needs to understand infrastructure, cybersecurity, applications, suppliers, resilience and operational risk. If the technology does not work, everything else becomes academic. 

But that should be the foundation of the role, not its limit. 

Traditionally, the senior technology person might have focused primarily on: 

“Are our systems working properly?” 

Today’s technology leader also needs to ask: 

“Are these the right systems, supporting the right processes, to help us achieve what the business is trying to achieve?” 

That means looking beyond the technology itself. 

Why does the business operate this process in this way? 

Why are people exporting information into spreadsheets? 

Why are employees manually transferring data between systems? 

Are we getting enough value from the technology we already own? 

Could automation remove repetitive work? 

Could better data help management make faster decisions? 

Where could AI genuinely improve productivity? 

And will the way we operate today still work if the business doubles in size? 

These are business questions with technology answers. 

Technology Leaders Need a Seat at the Table 

This is perhaps the biggest change. 

The senior technology leader cannot spend their entire working life inside the technology function. 

They need to be able to sit with the CEO, CFO and other business leaders, understand what the organisation is trying to achieve and help determine how technology can support, and sometimes enable, those ambitions. 

That requires commercial understanding. 

It means understanding how the business makes money, where it loses time, what its customers value, how its major processes work and how management measures performance. 

From there, the technology leader can translate business objectives into a technology roadmap. 

If the objective is reducing operating costs, where can processes be simplified or automated? 

If the objective is growth, what needs to scale? 

If management wants better information, what is preventing the business from getting it today? 

If AI is on the agenda, where can it produce measurable value rather than simply introducing another piece of software? 

The conversation moves from managing technology to improving the business through technology. 

Technology Leaders Also Need to Deliver Transformation 

Having the strategy is only half the job. 

Someone also needs to make it happen. 

Technology transformation rarely succeeds simply because a new system has been purchased. Processes change. Responsibilities change. Systems need integrating. Data needs improving. Employees need training. And, sometimes, established ways of working need challenging.

The modern technology leader therefore needs to be capable of leading change across the organisation. 

They need the credibility to work with technical specialists and suppliers, but also the communication and stakeholder skills to influence people who may have little interest in the technology itself. 

That is where the traditional distinction between technology leadership and digital transformation starts to become blurred. 

SMEs May Not Need Separate Technology and Transformation Leaders 

For larger organisations, separate CIO, CTO, technology operations and transformation functions can make perfect sense. 

For many SMEs, they may not. 

A £50m or £100m business may not need one senior person responsible for keeping technology running and another senior person responsible for changing how the business uses technology. 

It may need one strong technology leader capable of doing both. 

Operational technology does not disappear. 

Infrastructure, support, security, service delivery and applications still need managing. But much of that day-to-day responsibility can sit with capable team leaders, technical specialists, managed-service providers and other suppliers. 

The senior technology leader remains accountable for it without needing to personally live inside every operational issue.

That creates the capacity to work across the wider business: understanding strategy, identifying opportunities, setting the technology roadmap and then leading its delivery. 

What Does This Mean for Today’s Technology Leaders? 

For experienced technology leaders, this change represents an opportunity. 

Years spent running technology environments provide valuable foundations: understanding risk, knowing what good service looks like, dealing with suppliers, managing technical teams and understanding what happens when technology goes wrong. 

But that’s becoming the starting point rather than the complete job. 

Technology leaders need to understand how the business makes money. 

They need to understand its major processes across finance, sales, operations, HR and customer service. 

They need to understand how the CFO thinks about investment and return, and the measures the board uses to judge business performance. 

They need to become curious about why departments operate as they do, rather than simply supporting the systems they currently use. 

Then they need to connect technology decisions to those outcomes. 

The UK Government’s Chief Digital and Data Leader Programme reflects a similar direction, helping experienced technical professionals develop the strategic, commercial and leadership skills needed to move into senior digital and technology leadership roles.

Technical knowledge remains an asset. 

But technical knowledge combined with commercial understanding and the ability to deliver change is what defines an effective technology leader. 

The Future of Technology Leadership 

Technology leadership is not becoming less technical. 

It is becoming broader. 

Businesses still need leaders who understand operational technology. They still need secure infrastructure, reliable systems, effective support and sensible technical governance. 

What is becoming harder to justify is stopping there. 

For many SMEs, the technology leader of the future will need to operate in both worlds. 

They need to understand the technology well enough to ensure the business can depend on it. 

They need to understand the business well enough to know what needs to change. 

They need to sit alongside the CEO and CFO and help determine where technology can improve performance, increase efficiency and support growth. 

And then they need to be capable of leading that transformation throughout the organisation. 

Keeping the lights on is still part of the job. 

But the real value of technology leadership lies in helping decide where the business goes next – and using technology to help get it there. 

At Bristow Holland, we work with technology professionals across the East of England, from IT and infrastructure leadership through to technology, transformation and delivery roles.

If you’re an experienced IT manager or technology leader thinking about what the next stage of your career looks like, it may be time to consider how your role is evolving alongside the businesses you support. That could mean taking on greater strategic responsibility, moving closer to digital transformation, or finding a role where your technical and commercial experience can have a broader impact.

If you’re considering your next move or simply want to understand how your experience fits the changing technology leadership market, get in touch with us for a confidential conversation.

Andy Bristow

Bristow Holland

Entry-level technology jobs have traditionally given people a way into the industry. Graduates, apprentices and career changers could start with junior responsibilities, build practical experience and gradually take on more complex work.

Artificial intelligence may be changing that pathway.

AI tools can now assist with tasks that once provided some of the earliest opportunities for junior technology professionals, particularly in areas such as coding, testing, research and data analysis.

That doesn’t mean entry-level technology jobs are disappearing. It does mean employers may need to rethink what they expect from junior candidates and how they develop people once they join.

Is AI Reducing Entry-Level Technology Jobs?

There is evidence that entry-level hiring has become more difficult in the UK, but it would be too early to say that AI is solely responsible.

A June 2026 UK Government analysis of entry-level hiring found that hiring had weakened across the wider labour market. Of 38 entry-level occupations tracked in the analysis, 30 were declining. Software Engineer hiring had fallen by 27%, while Data Analyst hiring had fallen by 15%.

The same research found that the roles experiencing the sharpest declines were often those where AI capabilities had advanced significantly. However, the report specifically warns that this does not establish a causal relationship between AI and the decline in hiring.

Technology hiring has been affected by wider economic and labour market conditions, so organisations should avoid assuming that every reduction in junior recruitment results from automation.

What Happens When AI Can Do Junior-Level Tasks?

The bigger question may not be whether AI eliminates entry-level jobs.

It may be whether AI changes the work that junior employees traditionally did.

A junior Software Engineer might previously have spent considerable time writing straightforward code, fixing relatively simple issues or carrying out repetitive testing. AI tools can now assist with some of those activities.

That creates an interesting problem for employers.

Junior roles have never existed only to complete routine tasks. They have also provided a structured way for people to develop professional judgement, learn how systems work and gain experience from more senior colleagues.

If AI removes some of the simpler work, employers need to consider how junior professionals will develop those skills.

The answer may be to give entry-level employees different responsibilities rather than simply reducing the number of junior roles.

Will Entry-Level Technology Roles Need Different Skills?

The skills expected from junior technology professionals may increasingly extend beyond basic technical knowledge. As AI becomes part of everyday technology work, entry-level employees may also need enough AI literacy to use these tools effectively and understand their limitations.

For example, a junior developer may use AI-assisted development tools as part of their workflow, while a junior Data Analyst may use AI to support analysis and still need to check whether the results are accurate and relevant. In other technology roles, junior professionals may need to recognise when AI-generated output requires further investigation or human review.

The key skill is not simply knowing how to use an AI tool. It is understanding when to use it, how to evaluate what it produces and when human judgement is still required.

Could Employers Expect More From Junior Candidates?

There is a risk that changing technology could encourage employers to raise entry-level requirements rather than rethink the role.

A vacancy might begin as a junior Software Engineer position but gradually accumulate requirements for commercial experience, cloud platforms, AI tools, multiple programming languages and previous experience working in a professional development environment.

That creates a difficult contradiction.

If employers expect entry-level candidates to arrive with the capabilities of experienced professionals, they reduce the number of realistic entry points into the technology sector.

The problem is particularly significant when employers need experienced candidates because they have less capacity to train junior employees.

Hiring teams should therefore distinguish between what a candidate needs to know before joining and what they need to learn after joining.

A junior employee does not need to arrive fully formed. They need enough foundation to contribute, learn and develop.

What Could Entry-Level Technology Roles Look Like?

Entry-level roles may become less focused on completing predictable tasks and more focused on learning how to manage technology effectively.

That could mean junior employees spend more time reviewing AI-generated work, investigating problems, supporting senior professionals, testing systems, documenting decisions and learning how technology affects wider business processes.

The balance will vary by role.

A junior Software Engineer might need stronger code-review and debugging skills alongside programming knowledge. A junior Cybersecurity professional might spend more time investigating alerts and validating automated findings. A junior Data professional might need to focus more heavily on interpreting results and checking data quality.

These are still entry-level responsibilities.

They simply reflect a workplace where AI handles more of the routine activity.

Does This Make Junior Talent More Valuable?

It could.

Skills England’s 2026 analysis of the digital and technologies sector expects substantial growth across priority occupations and identifies higher-than-average proficiency in core skills such as problem-solving and decision-making, digital literacy, and learning and investigating.

The same assessment describes AI-driven changes in technology work, including a shift away from some routine coding and testing towards oversight, verification, communication and judgement.

That could increase the importance of people who can develop those capabilities over time.

For employers, the opportunity is to think about junior hiring as part of a longer-term talent pipeline rather than simply a way to fill lower-cost positions.

Someone who enters a technology team with strong fundamentals and develops alongside changing tools may become more valuable as their experience grows.

How Should Employers Hire Junior Technology Talent?

The first step is to define what the junior employee will actually do.

Employers should identify the technical foundations that matter, the responsibilities the person can reasonably take on and the skills they can develop through training and experience.

AI capability can then be assessed as part of that wider picture.

The candidate may not need specialist AI expertise. They may simply need enough understanding to use AI tools responsibly, question their output and continue developing their technical judgement.

This approach can also help employers avoid creating unrealistic entry-level vacancies.

If every junior role requires previous professional experience, advanced AI knowledge and multiple technical specialisms, employers risk shrinking the very talent pipeline they will eventually depend on.

Could AI Change the Meaning of “Entry-Level”?

It probably will.

Entry-level may increasingly describe a person’s stage of professional development rather than the simplicity of the tasks they perform.

A junior employee could work with sophisticated AI tools from their first day while still developing the judgement and experience needed to operate independently.

That creates a different model of progression.

Instead of starting with simple work and gradually moving towards more advanced tools, new professionals may work with advanced tools immediately while learning how to evaluate, manage and apply them effectively.

The responsibility for developing that capability will not sit entirely with candidates.

Employers will also need to create roles that allow junior professionals to learn.

The Future of Entry-Level Technology Hiring

AI may change what “entry-level” means in technology, but the bigger question for employers is whether their hiring and development practices change with it.

If the pathway into technology becomes narrower, organisations could make future skills shortages harder to solve. Employers that continue to create realistic entry points and develop people early in their careers will be better placed to build the talent they need as technology evolves.

The challenge is not simply deciding which tasks AI can perform. It is deciding how people at the beginning of their careers will gain the experience needed to become the technology professionals of the future.

The EU AI Act could affect more than how organisations use artificial intelligence. For UK technology employers working with European markets, it could also influence the capabilities they need and how they build their technology teams.

The key question for employers is not simply whether they need to comply with the legislation. It is whether their existing teams have the right skills to build, implement, secure and manage AI responsibly.

The EU AI Act is being introduced in stages. Some requirements already apply, while others take effect later. From 2 August 2026, the European Commission’s AI Office and national authorities began enforcing provisions that had reached their application date. The 2026 AI Omnibus also extended some later deadlines, including those covering certain high-risk AI systems.

This creates a workforce question: do you have the right capabilities in place as AI becomes part of your technology environment?

Does the EU AI Act Apply to UK Companies?

Being based in the UK does not automatically put an organisation outside the EU AI Act.

Certain obligations can apply to organisations outside the EU, depending on their role, the AI systems they place on the EU market or use within the EU, and whether the output of those systems is used in the EU.

For UK technology businesses operating across European markets, this means understanding which of their AI activities fall within the Act.

The requirements will vary between organisations. A company using a general-purpose AI tool internally will not necessarily face the same requirements as a technology business developing an AI system for use in a regulated environment.

That distinction matters when planning recruitment. Employers need to understand the capabilities their technology actually requires before adding AI or regulatory requirements to a role.

How Could AI Regulation Affect Technology Skills?

The AI Act takes a risk-based approach. The requirements placed on an AI system depend on how it is used and the risks associated with it.

For high-risk systems, requirements can include risk management, data governance, logging, documentation, human oversight, robustness, cybersecurity and accuracy.

This means AI projects can require a wider range of capabilities than software development alone.

A technology team may need expertise across engineering, data, cybersecurity, testing, governance and risk. In some organisations, these capabilities will already exist across different roles. In others, there may be genuine gaps.

The result will not necessarily be a new generation of AI-specific job titles. It may instead change what employers expect from existing technology roles.

AI Skills Are Not Just Technical Skills

AI capability extends beyond people who build machine-learning models.

Research from the Department for Work and Pensions and Skills England in 2026 identifies three broad areas of AI skills: technical, responsible and ethical, and non-technical capabilities. It also found that most roles require a combination of these skills rather than advanced technical expertise alone.

That changes how AI capability should be assessed.

A Software Engineer may need to verify AI-generated code and understand its limitations. A Data Engineer may need stronger data governance knowledge. A Cybersecurity professional may need to understand AI-specific risks. A Technology Manager may need enough understanding of AI and its risks to make informed decisions about technology projects.

These capabilities don’t necessarily require separate hires.

Employers should first establish what their existing teams can already do, where the gaps are and which capabilities genuinely need to be added.

AI Literacy Could Affect Existing Teams

The AI Act also includes an AI literacy obligation.

Article 4 requires providers and deployers of AI systems to take measures to support the AI literacy of staff and others working with AI systems on their behalf. The obligation has applied since February 2025, with supervision and enforcement beginning in August 2026. The European Commission says organisations should consider factors such as technical knowledge, experience, education, training and the context in which the AI system is used.

For employers, the practical implication is that AI capability may need to be developed across existing teams rather than concentrated in a single specialist role.

Some organisations may be able to close capability gaps through training and development. Others may need specialist expertise. Many will need both.

The important question is not whether an organisation has an “AI person”. It is whether the people responsible for its AI systems have the knowledge they need to do their jobs effectively.

Should Employers Hire AI Specialists?

Sometimes. But not automatically.

An organisation might assume that increasing use of AI means it needs to hire an AI specialist. In practice, the required capability may already sit across several technology disciplines.

A Software Engineer may provide the engineering expertise. A Data Engineer may manage data requirements. A Cybersecurity professional may address security risks. A Technology Architect may consider how the AI system fits into the wider technology environment.

Another organisation may genuinely need dedicated AI expertise.

The starting point should therefore be the business and technology problem, not the job title.

This is particularly important when defining specialist vacancies. Combining software engineering, machine learning, cybersecurity, data governance, regulatory compliance and transformation into one role may create a specification that very few candidates can realistically meet.

Hire for Capability, Not Buzzwords

AI experience is becoming an increasingly common requirement in technology vacancies. Adding it to a job description, however, does not necessarily tell employers what a candidate actually needs to do.

A Software Engineer working on an AI-enabled product may need experience with AI-assisted development, testing and verification. A Data Engineer may need experience with data quality and governance. A Cybersecurity specialist may need to understand AI-specific attack surfaces.

These are different capabilities.

Treating them all as “AI skills” can make a role harder to define and harder to recruit for.

A better approach is to identify the outcome the person needs to deliver, then determine which capabilities are essential to achieving it.

That also makes it easier to separate skills that are required on day one from those that can be developed after hiring.

What Does This Mean for Software Engineers?

AI will not affect every Software Engineering role in the same way.

For some engineers, AI may primarily be another tool within the development process. Others may build or maintain AI systems operating in environments with additional requirements around testing, documentation, data, security and human oversight.

This makes “AI experience” a poor standalone measure of suitability.

Someone who regularly uses AI coding tools is not automatically equipped to develop or maintain a regulated AI system.

Employers should instead assess whether candidates understand the technology they are building, can critically evaluate AI-generated output and can work within the technical requirements of the environment.

Data and Cybersecurity Skills Are Also Changing

AI increases the importance of understanding the data behind a system.

For higher-risk AI systems, data quality, governance and documentation can form part of the wider technology responsibility. Depending on the system, Data Engineers may therefore need to understand areas such as data provenance, quality and governance alongside their existing technical skills.

The same applies to cybersecurity.

Cybersecurity and robustness are among the requirements associated with high-risk AI systems. In July 2026, the European Commission also published an Action Plan on Cybersecurity and Artificial Intelligence, highlighting the growing connection between AI and cybersecurity.

For employers, this could increase the value of professionals who understand both areas.

It does not necessarily mean creating new “AI Data” or “AI Cybersecurity” roles. It may mean strengthening the capabilities of existing teams or bringing in specialist expertise where a genuine gap exists.

What About AI Used in Recruitment?

AI regulation is particularly relevant to employers because certain AI systems used in employment are classified as high risk.

The European Commission identifies examples including systems used to place targeted job advertisements, analyse and filter applications and evaluate candidates. However, the classification applies to specific use cases rather than automatically making every AI tool used by a recruitment team high risk.

Understanding the technology’s actual use is therefore important.

An AI tool used somewhere in the recruitment process does not automatically create the same regulatory requirements as an AI system used to evaluate candidates.

Where AI is used for screening, evaluation or other employment-related decisions, employers may need closer collaboration between Talent, HR, Technology, Data, Legal and Compliance teams.

When Do the High-Risk Employment Rules Apply?

The timing gives employers an opportunity to prepare.

Following the 2026 AI Omnibus changes, the rules for high-risk AI systems covered by Annex III are scheduled to apply from 2 December 2027. This includes the relevant employment-related use cases covered by the framework.

Employers can use the time before these requirements apply to understand which AI systems they use, what those systems do, who is responsible for them and whether the necessary capabilities exist within their teams.

That assessment can inform workforce planning before a skills gap becomes a recruitment problem.

Avoid Creating an Impossible Technology Role

AI can make job descriptions more complicated very quickly.

An employer may want someone who understands software engineering, machine learning, cybersecurity, data governance, regulatory requirements, risk management and business transformation.

That may sound comprehensive, but it can also describe an unrealistic candidate.

The more requirements a role combines, the smaller the pool of genuinely suitable candidates becomes. It can also become difficult to distinguish between capabilities that are essential and those that would simply be useful.

Employers should start with the outcome they need.

From there, they can identify the capabilities required, determine what already exists within the team and decide whether the remaining gap should be addressed through development, recruitment, contracting or specialist support.

What Should Technology Employers Do Now?

The EU AI Act does not mean every UK technology employer needs to restructure its workforce.

It does mean organisations should understand how AI is being used across their technology environment and consider whether their teams have the capabilities required to support it.

That means looking at the systems being developed or deployed, the markets they serve and the responsibilities attached to them.

Employers can then assess their existing capability and identify genuine gaps.

Some gaps may be addressed through upskilling. Others may require changes to existing responsibilities. Some may justify a permanent hire, while others may be better suited to contractors or specialist project support.

The important thing is to make that decision based on the capability the organisation actually needs.

Key Takeaways

• AI regulation is changing the capabilities technology employers need, not necessarily creating demand for entirely new roles.
• AI capability extends beyond technical expertise, with existing roles increasingly needing relevant data, cybersecurity, governance and AI knowledge.
• Employers should define the capability they need before defining the vacancy, particularly where several technology disciplines overlap.
• Not every capability gap requires recruitment; employers can consider upskilling, changing responsibilities, contractors or specialist support.
• Hiring should focus on genuine capability gaps, rather than adding broad AI requirements to existing technology roles.

Technology employers have spent years competing for people with scarce technical skills. Software Engineers, Cybersecurity specialists, Data Engineers, Cloud Engineers and other technology professionals remain essential to organisations across the UK.

The next technology skills shortage, however, may look different.

As artificial intelligence changes how technology work gets done, employers may increasingly need people who can combine technical expertise with judgement, problem-solving, communication and adaptability.

Technical skills are not becoming less important. The challenge is that employers may need a broader combination of capabilities from the people who use them.

For hiring teams, that changes the question from “Which technical skill do we need?” to “What capabilities does this role actually require?”

Why Are Technology Skills Changing?

The UK technology workforce is still expected to grow significantly.

Skills England’s 2026 Sector Skills Needs Assessment projects that employment across 30 priority occupations within the digital and technologies sector will grow by 239,000 jobs, or 27%, between 2025 and 2035. It also estimates 249,000 replacement workers will be needed over the same period, bringing total estimated demand to around 488,000 workers.

The assessment also highlights how AI could change the nature of technology work. As AI-enabled tools become more capable, some routine coding and testing tasks may shift towards activities such as oversight, assurance, verification and judgement.

That does not remove the need for technical expertise. Instead, it changes where that expertise creates value.

A Software Engineer may spend less time completing routine coding tasks but more time reviewing generated code and making technical decisions. A Cybersecurity professional may use AI to identify potential threats while remaining responsible for assessing whether those findings are accurate. A Data professional may automate parts of a workflow while still needing to understand data quality and context.

The technology changes the workflow. The need for people who understand the work remains.

Which Skills Will Technology Employers Need?

Technical knowledge increasingly sits alongside broader capabilities.

Skills England’s 2026 Annual Skills Report highlights communication, critical thinking and analytical skills as important capabilities as workers adapt to AI. It also stresses the need for workers to develop the skills needed to use AI effectively as its role in the workplace grows.

For technology employers, these are not simply generic soft skills.

Judgement matters when an engineer needs to decide whether AI-generated code is safe to deploy. Communication matters when an Architect needs to explain a technical decision to senior stakeholders. Problem-solving matters when an AI-enabled system produces an unexpected result.

As more routine activity becomes automated, the ability to understand context and make sound decisions can become more important.

That means hiring teams may need to assess how candidates apply their technical knowledge, rather than focusing only on the technologies listed on their CV.

Could Human Judgement Become More Valuable?

AI can produce an answer quickly. That does not necessarily make the answer correct, appropriate or useful.

This makes the ability to evaluate information increasingly important.

UK Government research published in 2026 found that AI skills span both specialist technical expertise and broader workplace capabilities. The research identifies different levels of AI users, from AI experts and specialists to professionals who implement AI in their existing roles, highlighting the need for people to develop the skills required to use and evaluate AI effectively.

This reinforces the importance of looking beyond technical keywords.

A candidate may have extensive experience with a particular programming language or platform, but employers also need to understand how that person approaches unfamiliar problems, evaluates information and responds when a technology does not behave as expected.

The strongest candidate will not always be the one with the longest technical checklist.

Are Skills Shortages Becoming Capability Shortages?

A traditional skills shortage suggests that employers cannot find enough people with a particular skill.

The emerging problem may be more complicated.

An organisation might be able to find Software Engineers with strong coding experience but struggle to find people who can combine software development with AI-assisted workflows, quality assurance and effective communication.

It could find Project Managers with extensive delivery experience but fewer candidates who can manage technology programmes involving AI, changing processes and uncertain requirements.

The organisation does not necessarily have a shortage of people with individual skills.

It may have a shortage of people with the right combination of capabilities.

That distinction matters because it changes how employers should define vacancies.

Instead of continually adding requirements to an existing job description, hiring teams should identify which capabilities genuinely determine success in the role.

Should Employers Hire for Potential?

Hiring for potential can help employers respond to changing skills requirements, but it should not become an excuse to overlook genuine technical requirements.

The right balance depends on the role.

A highly specialised position may require significant expertise from day one. Other roles may allow an employer to hire someone with strong technical foundations and develop more specific skills over time.

This approach can also widen the candidate pool without compromising the capabilities the role genuinely requires.

The same principle applies to existing employees. If a capability can realistically be developed internally, reskilling may be more practical than competing for a small pool of candidates who already possess every emerging skill.

What Should Employers Look For?

Technology employers should increasingly assess how candidates apply their knowledge, not simply how many technologies they can list on a CV.

Technical assessment remains important. Candidates still need to demonstrate the expertise required for the role.

However, employers should also consider how candidates approach unfamiliar problems, explain technical decisions, evaluate information and work with people outside their immediate specialism.

The ability to learn matters too. Technology tools and workflows can change quickly, making adaptability increasingly valuable.

Someone who has worked with one particular technology may not always be the strongest long-term hire. A candidate with strong technical foundations, sound judgement and a demonstrated ability to learn may adapt more effectively as the technology environment changes.

The Next Technology Skills Shortage May Be About Capability

Technical skills shortages are not disappearing.

The UK will continue to need people who can build software, secure systems, manage infrastructure, analyse data and deliver technology change. What is changing is the combination of skills employers need from those people.

AI can automate parts of technical work, but organisations still need professionals who understand the underlying technology, evaluate outputs, solve unfamiliar problems and take responsibility for results.

Introduction

Technology roles are becoming harder to define.

Businesses are adopting new technologies, changing operating models and asking technology teams to solve increasingly complex problems. As a result, a vacancy that once had a straightforward remit can quickly become a combination of technical delivery, strategy, leadership, security, infrastructure and business change.

The problem is that trying to find one person who can do everything can make recruitment less effective.

An overly broad role can reduce the number of suitable candidates, increase salary expectations and make it difficult to assess whether someone is genuinely right for the position. It can also leave the successful candidate with competing priorities and unclear expectations.

For Small and Medium-sized Enterprises (SMEs), where every senior technology hire can have a significant impact, defining the role correctly before recruitment begins is particularly important.

Start With the Problem

The starting point for a technology hire should not necessarily be a job title.

It should be the problem the business needs someone to solve.

An organisation might initially decide that it needs a Head of IT. However, the underlying requirement could actually be to modernise infrastructure, improve cybersecurity, establish technology governance or prepare the business for growth.

Those requirements may need very different capabilities.

Starting with the problem allows employers to establish what the person will actually be expected to achieve. It also makes it easier to determine whether the requirement calls for a permanent hire, a specialist contractor, an interim leader or additional support around an existing team.

This approach is becoming more important as technology roles continue to change. The UK Standard Skills Classification, published by Skills England in 2026, provides a common framework for describing the skills, tasks and knowledge required across UK occupations and contains 3,350 occupational skills.

Separate Responsibilities From Capabilities

A common mistake is to build a vacancy by combining every responsibility currently sitting within the technology function.

For example, an SME might look for someone responsible for:

IT operations, cloud infrastructure, cybersecurity, software development, vendor management, data, project delivery and technology strategy.

Each area is legitimate. The problem is expecting one person to provide senior-level expertise across all of them.

Employers should instead distinguish between responsibilities and capabilities.

A technology leader may need enough knowledge of cybersecurity to manage risk without being a cybersecurity specialist. A CTO may need to understand infrastructure without personally managing it. An IT Director may oversee transformation without being the organisation’s principal project manager.

This distinction helps employers identify the level of expertise genuinely required rather than building an unrealistic list of requirements.

Define What Success Looks Like

A strong technology job description should explain what the successful candidate is expected to change.

This is particularly important for senior appointments.

“Responsible for IT strategy” tells a candidate very little. “Develop and implement a technology strategy that supports the company’s next stage of growth” provides considerably more context.

The same principle applies to technical roles.

Instead of simply listing technologies, employers should consider what the person needs to achieve with them. Is the objective to reduce technical debt? Improve resilience? Build a scalable platform? Improve security? Reduce operational costs?

The answer changes the type of candidate required.

It also gives candidates a better opportunity to assess whether their experience is relevant.

Avoid the Perfect Candidate

Technology recruitment can become unnecessarily difficult when employers try to create a specification for an ideal candidate rather than a realistic one.

This often happens when desirable experience gradually becomes essential. A vacancy starts with five genuine requirements and ends with fifteen.

The result can be a highly experienced candidate who meets most of the requirements being rejected because they have not worked with one particular platform or technology.

This approach is particularly important in a rapidly changing market. Skills England’s 2026 Digital and Technologies assessment found that priority technology occupations require higher-than-average proficiency in digital literacy, learning and investigating, creating, problem-solving and decision-making. It also found that AI adoption is reshaping digital roles and workflows, with greater emphasis on adaptability, accountability, collaboration and the effective use of AI alongside technical expertise.

For employers, this means assessing whether a candidate has demonstrated the ability to solve comparable problems can be more useful than requiring an exact match against every technology in the environment.

Consider the Team Around the Role

A role should not be assessed in isolation.

Before recruiting, employers should consider the capabilities already available within the organisation.

If an SME already has strong infrastructure engineers, for example, its next hire may need to provide leadership rather than additional infrastructure expertise.

Likewise, if the business has a capable IT team but lacks strategic direction, recruiting another technical specialist may not address the underlying problem.

Understanding the existing team also helps establish where responsibilities should sit.

This can prevent senior hires from becoming overloaded with operational work that could be delegated while also being expected to deliver strategic change.

Don’t Build Tomorrow’s Role Around Yesterday’s Structure

Technology teams should evolve with the business.

An organisation that has grown significantly may still have a technology structure designed for a much smaller company. Roles that once made sense can gradually accumulate additional responsibilities until they become difficult to recruit for.

The wider UK technology market is also changing. Skills England’s assessment mentioned above also projects a 27% increase in employment across 30 priority digital and technology occupations between 2025 and 2035, alongside an estimated 249,000 workers needed to replace people leaving these occupations.

For employers, this makes workforce planning more important. The question should not simply be “Who can manage what we have today?” It should also be “What capability will the business need as it grows?”

That does not necessarily mean hiring a more senior person. It may mean separating responsibilities that have become too broad or creating a role that did not previously exist.

Get the Market View Before Advertising

One of the most useful points at which to involve a specialist recruitment partner is before the vacancy formally exists.

An employer may have a clear idea of the problem but an inaccurate idea of the role needed to solve it. Speaking to people with knowledge of the technology talent market can help test those assumptions before they become part of a job description.

That conversation can establish whether the proposed combination of skills is realistic, whether the level of seniority matches the responsibility and whether the organisation is likely to find the required capability within its target market.

This is particularly valuable for SMEs, which may not regularly recruit senior technology professionals.

The UK’s 2026 SME Digital Adoption Taskforce update highlights capability, cost and awareness as key barriers to SME digital adoption, reinforcing the importance of having the right expertise to support technology decisions.

Early consultation can therefore save time later. It can help an employer decide what it actually needs before spending weeks searching for a candidate who may not exist.

Build a Role Someone Can Succeed In

Defining a technology role correctly is not about making the job description shorter.

It is about making the requirement clearer.

The strongest roles have a defined purpose, realistic responsibilities and an appropriate balance between technical expertise, leadership and business understanding. They give the successful candidate enough authority to deliver what they were hired to achieve.

That benefits both sides of the recruitment process.

Employers gain a clearer basis for assessing candidates. Candidates gain a better understanding of what they are being asked to do. The eventual hire is more likely to enter the organisation with realistic expectations and a clear definition of success.

Conclusion

A difficult technology vacancy is not always evidence of a difficult talent market.

Sometimes the real problem is that the organisation is trying to hire one person to solve several different problems.

For SMEs, the consequences can be significant. A senior technology hire represents a substantial investment, and a poorly defined role can lead to a long recruitment process, limited candidate choice or a placement that fails to deliver what the business actually needed.

The solution is to start earlier.

Define the problem. Understand the capability required. Assess the existing team. Separate essential skills from desirable experience. Then test the role against the market before taking it to candidates.

The best technology recruitment processes do not begin with a job advert.

They begin with a clear understanding of what the business needs someone to achieve.

Key Takeaways

• Start with the business problem, not the job title.
• Separate responsibilities from specialist capabilities.
• Define measurable outcomes before defining candidate requirements.
• Avoid turning desirable experience into an unrealistic wish list.
• Consider the capabilities already available within the technology team.
• Review whether existing roles still fit the organisation’s current stage of growth.
• Get an informed view of the talent market before formally opening a difficult vacancy.
• Build roles around what the successful candidate can realistically achieve.

Moving data infrastructure to the cloud can change how an organisation stores, processes and uses its data. The technology matters, but the people delivering the migration can have just as much impact on its success.

Hiring the right Data Engineers therefore requires more than looking for experience with a particular cloud platform. Employers need to understand the migration itself, the existing data environment and the skills required to move between the two.

The right candidate should be able to work with the organisation’s current infrastructure while helping build a reliable and scalable future-state environment.

Understand What the Migration Actually Requires

Before recruiting, employers need a clear view of what the cloud migration involves.

A straightforward migration may require engineers to move existing pipelines and data workloads into a cloud environment. A larger transformation could involve redesigning data architecture, rebuilding pipelines, integrating new platforms and changing how teams access and use data.

Those differences have a direct impact on recruitment.

A Data Engineer who has experience maintaining cloud-based pipelines may be well suited to one project but may not have the architecture or migration experience required for another.

The hiring process should therefore start with the migration requirements rather than a generic Data Engineer job description.

Look for Relevant Cloud Experience

Cloud experience is likely to be important, but employers should be specific about what they actually need.

Experience with AWS, Microsoft Azure or Google Cloud can demonstrate familiarity with cloud environments, but the platform alone does not determine whether someone can successfully support a migration.

Candidates should be able to explain how they have used cloud technology in practice. This could include building data pipelines, managing storage, working with cloud databases, improving performance or supporting large-scale data processing.

The depth of experience matters more than simply having a cloud platform listed on a CV.

Assess Migration Experience

Cloud migration introduces challenges that do not necessarily appear in day-to-day data engineering.

Engineers may need to understand legacy systems, map existing data flows, identify dependencies and decide how workloads should move into the new environment. They may also need to manage migration risks while keeping existing services operational.

Candidates who have supported previous migrations can bring valuable experience because they understand that moving data is rarely just a matter of transferring files from one system to another.

During interviews, ask candidates to explain a migration they have worked on. What was the starting environment? What problems did they encounter? How did they approach dependencies, testing and data quality?

These questions can reveal far more than a list of migration technologies.

Assess Data Pipeline Skills

Data pipelines sit at the centre of many cloud migration projects.

Engineers may need to build new pipelines, adapt existing ones or move workloads between different platforms. They need to understand how data moves through the organisation and how changes to one part of the environment can affect another.

Look for candidates who can explain the design decisions behind their pipelines rather than simply naming the tools they have used.

Experience with technologies such as SQL, Python, ETL or ELT processes, orchestration and cloud data platforms may all be relevant, depending on the project.

The important question is whether the candidate can apply those skills to the organisation’s specific migration requirements.

Don’t Overlook Data Quality

A successful migration is not simply about moving data from one environment to another.

The organisation also needs confidence that the data remains accurate, complete and usable after the move.

Data Engineers may therefore need to identify inconsistencies, validate migrated data and build processes that detect problems before they affect users.

This makes data quality experience particularly valuable when assessing candidates.

Ask how candidates have previously identified or resolved data-quality problems. Their answers can help reveal whether they understand the wider impact of poor data rather than treating quality as a final testing exercise.

Consider Security and Governance

Moving data into the cloud can introduce new security and governance considerations.

The Data Engineer may work with sensitive customer, financial or operational information. Depending on the organisation and the project, they may need to understand access controls, encryption, data retention and regulatory requirements.

Employers should therefore consider these requirements when defining the role.

The UK’s 2026 Digital and Technologies Sector Skills Needs Assessment highlights the growing importance of data, cybersecurity and other digital capabilities as technology continues to change.

The level of security knowledge required will vary, but candidates should understand that data engineering decisions can have consequences beyond the technical environment.

Look for Problem-Solving Ability

Migration projects rarely follow the original plan perfectly.

Legacy systems may behave differently than expected. Data dependencies may be poorly documented. Performance can change after migration, while previously hidden quality problems can emerge during testing.

Strong Data Engineers need to investigate these problems and find practical solutions.

Interview questions should therefore explore how candidates have handled unexpected technical issues. Ask what happened, how they investigated the problem and why they chose their eventual solution.

This provides evidence of how they think rather than simply confirming that they have worked with a particular technology.

Seniority Matters

Not every cloud migration requires a senior Data Engineer, but larger or more complex projects may need people who can make decisions beyond individual pipelines.

Senior engineers may need to contribute to architecture decisions, establish engineering standards, review technical approaches and help less experienced team members.

They may also need to communicate with architects, project managers, security specialists and business stakeholders.

The more complex the migration, the more important it becomes to distinguish between someone who can execute defined tasks and someone who can help shape the technical approach.

Consider the Existing Technology Environment

The ideal candidate depends partly on what the organisation already has.

A business moving from on-premise SQL Server into Azure will have different requirements from an organisation migrating a large distributed data platform into AWS.

Existing technology, internal skills and the target architecture should therefore influence the recruitment profile.

This also prevents employers from creating unnecessarily broad specifications. Requiring experience across every major cloud platform, database technology and data tool may make the vacancy look comprehensive, but it can also exclude candidates who have the right transferable experience.

Decide What Can Be Learned

Cloud technology changes quickly, so employers should distinguish between skills that genuinely need to be present on day one and those that can be developed.

A candidate may have strong migration experience on Azure but little experience with AWS. Another may have extensive AWS experience but limited exposure to the organisation’s preferred data platform.

Neither should automatically be ruled out.

Strong data engineering fundamentals, problem-solving ability and experience working with complex data environments can transfer between technologies. The recruitment process should identify which gaps are manageable and which would create a genuine delivery risk.

Use Practical Technical Assessments

Technical assessments can help employers test whether candidates can apply their experience to a realistic migration problem.

Rather than asking candidates to recall definitions, give them a scenario. They might need to explain how they would approach moving a legacy data pipeline into the cloud, identify potential risks or suggest how they would validate the migrated data.

The aim is not necessarily to find one perfect answer.

A strong assessment should reveal how the candidate thinks, what questions they ask and whether they recognise the technical and business consequences of their decisions.

Hire for the Migration You Actually Have

There is no single Data Engineer profile that fits every cloud migration.

A small migration may need an experienced engineer who can execute a well-defined technical plan. A complex transformation may require senior engineers who can work across architecture, data, security and delivery.

The recruitment process should reflect that difference.

Employers that define the migration first can build a much more accurate candidate profile. They can then assess candidates against the skills that genuinely matter rather than relying on long technology lists or generic cloud experience.

What Should Employers Look for in a Data Engineer for Cloud Migration?

The strongest candidates combine solid data engineering fundamentals with relevant cloud experience, problem-solving ability and an understanding of migration challenges.

They should be able to explain their previous work, understand the impact of their technical decisions and adapt their approach when the environment changes.

For employers, successful hiring starts before the vacancy is advertised. Understanding the migration, identifying the capabilities required and separating essential skills from those that can be learned will create a stronger basis for finding the right Data Engineer.

A good cloud migration depends on good technology, but it also depends on having the right people to move it forward.

AI is changing software development, but that does not mean every Software Engineer needs to become an AI specialist.

For employers, the more useful question is how a candidate uses AI within their existing engineering work. Can they use AI tools to improve productivity? Can they check the output? Do they understand the risks? Can they recognise when an AI-generated solution is wrong?

These questions are becoming more important as AI becomes part of everyday software development. Hiring teams need to assess both traditional engineering ability and the new skills that allow developers to work effectively with AI.

What AI Skills Should Software Engineers Have?

The right AI skills depend on the role.

A Software Engineer might use AI to generate code, explain unfamiliar systems, write tests, identify bugs or speed up routine development work. A senior engineer may also need to review AI-generated solutions, assess their risks and decide where AI should be used within the development process.

Skills England’s 2026 research shows that AI is changing software development, with greater emphasis on verification, oversight, judgement and communication as AI takes on more routine development tasks.

For employers, this means that AI experience should not become another keyword to add to a job description. The important question is what the candidate can actually do with AI and how well they understand its limitations.

Look at How Candidates Use AI

Asking whether a candidate has used ChatGPT, GitHub Copilot or another AI development tool will tell you very little on its own.

Instead, ask how they use those tools.

A strong candidate should be able to explain when AI helps them, when they avoid using it and how they check its output. They should also understand that an AI tool can produce an answer that looks convincing without being technically correct.

This distinction matters because effective AI use requires more than knowing which button to press. Software Engineers still need to understand the problem, assess the proposed solution and remain responsible for the result.

Assess AI-Assisted Code Review

One of the most useful ways to assess AI skills is to look at how candidates review generated code.

AI can produce functional-looking code that contains bugs, security weaknesses, inefficient logic or design problems. An engineer therefore needs enough technical understanding to question the output rather than accept it automatically.

A practical recruitment exercise could give candidates a piece of code and ask them to identify potential problems, explain their reasoning and suggest improvements. The code could come from an AI tool, but it does not have to. The objective is to assess engineering judgement.

This approach also avoids turning the interview into a test of whether someone knows a particular AI product.

Don’t Confuse AI Tool Experience With AI Expertise

A candidate who has used AI extensively is not automatically more capable than one who has only recently started using it.

Tool experience can be useful, but employers should distinguish between familiarity and capability.

The UK Government’s 2026 AI Labour Market Survey identifies significant skills gaps and evolving skills requirements within the AI sector, highlighting the growing challenge of finding people with the capabilities organisations need.

For Software Engineer recruitment, this means employers should define the level of AI capability they actually need rather than assuming that more tool experience always means a better candidate.

Test Software Engineering Without AI

AI skills should add to strong engineering fundamentals, not replace them.

Candidates still need to understand software design, debugging, testing, architecture and the principles behind the systems they build. They should also be able to reason through a technical problem when an AI tool cannot provide a useful answer.

This is particularly important when hiring senior engineers. Someone who relies heavily on AI but cannot explain the underlying solution may struggle when a system behaves unexpectedly or when the generated answer does not fit the organisation’s architecture.

Technical assessments should therefore test understanding as well as output.

Assess Security and Responsible AI Use

Software Engineers may work with source code, customer information, credentials, intellectual property and other sensitive data. Using AI tools can introduce additional risks if employees do not understand how those tools handle information.

Responsible AI use should therefore form part of the assessment for relevant roles.

The UK’s 2026 AI Skills for Life and Work employer research identifies different levels of AI capability across organisations, including people who use AI tools, implement AI models and develop AI models.

For employers, this reinforces the importance of defining what AI responsibility looks like within the specific role.

An interview could explore how a candidate would decide whether to put a piece of proprietary code into an AI tool, how they would validate an AI-generated answer or what they would do if an AI-assisted solution introduced a security concern.

Senior Engineers Need More Than Tool Knowledge

The level of AI capability required should increase with the level of responsibility.

A junior Software Engineer may need to understand how to use approved AI tools safely and check the work they produce. A Senior Software Engineer may need to make decisions about where AI fits into development workflows and how teams should review AI-assisted work.

Engineering Leads and senior technical specialists may need to consider wider questions around architecture, security, governance, quality and accountability.

That means employers should avoid using one generic definition of “AI skills” across every Software Engineering vacancy.

Use AI in the Assessment Process Carefully

AI has also changed the way employers assess candidates.

Traditional coding tests can become less useful if candidates can simply ask an AI tool to produce a solution. However, banning AI entirely may create an artificial assessment that does not reflect the working environment.

A better approach is to decide what the assessment is intended to measure.

If the goal is to assess independent technical reasoning, give candidates an opportunity to demonstrate that without AI assistance. If the goal is to understand how they work with AI, allow appropriate tools and assess how they verify and improve the results.

The assessment should reflect the actual expectations of the role.

Look for Learning and Adaptability

AI tools will continue to change. A candidate who knows one particular coding assistant today may need to work with a completely different tool in the future.

Employers should therefore look for people who can learn, experiment and adapt rather than focusing too heavily on a fixed list of AI products.

2026 research from the UK Government and Skills England highlights the need for employers to build workforce capability so that people can use AI effectively, safely and responsibly.

For Software Engineer recruitment, that makes learning ability particularly valuable. The strongest candidate may not have used every tool an organisation currently uses, but they should be able to understand new technology and work out how to use it responsibly.

Don’t Add AI Requirements Just for the Sake of It

There is a risk that employers will start adding “AI experience” to every Software Engineer vacancy simply because AI is becoming important.

That can unnecessarily reduce the candidate pool.

A Software Engineer developing machine-learning systems will need very different AI expertise from a full-stack developer who uses AI to support coding, testing and documentation. Treating both roles as requiring the same AI background makes the recruitment process less accurate.

Before advertising a role, hiring teams should establish what AI will actually mean for the person’s day-to-day work.

That makes it easier to distinguish genuine requirements from desirable experience.

What Should Employers Look for When Hiring Software Engineers?

AI is changing the skills employers need from Software Engineers, but the fundamentals of good engineering remain.

The strongest candidates will combine technical knowledge with problem-solving, judgement and the ability to work effectively with new tools. They should understand what AI can do, where it can create problems and when human review remains essential.

For hiring teams, the goal is not to find the candidate who uses AI the most. It is to find someone who can use AI productively without losing the engineering judgement needed to build reliable, secure and maintainable software.

As AI becomes a normal part of software development, that ability to combine technical expertise with responsible AI use is likely to become an increasingly important part of Software Engineer recruitment.

Small and medium-sized businesses (SMEs) often assume that attracting experienced technology professionals requires competing with larger organisations on salary alone.

That can be difficult. Larger employers may have bigger technology teams, larger recruitment budgets and more established career structures.

The UK technology labour market is already under significant pressure. Skills England estimates that 68% of priority digital and technology occupations are currently in critical or elevated demand, while total demand across 30 priority occupations is projected to reach around 488,000 workers between 2025 and 2035 when growth and replacement demand are combined.

However, salary is only one part of what experienced technology candidates consider when choosing their next role.

For SMEs, the opportunity is to compete differently.

Interesting technical problems, greater responsibility, access to decision-makers, flexibility and the opportunity to make a visible impact can all make a smaller organisation attractive. The challenge is understanding what the business can realistically offer and communicating it clearly during the recruitment process.

For employers competing for specialist technology talent, the question is therefore not simply how to offer more. It is how to offer something different.

Understand What Candidates Value

Experienced technology professionals are unlikely to assess a role based on salary alone.

The nature of the work, the technology environment, leadership, flexibility and opportunities to develop can all influence whether someone considers a position worthwhile.

Flexible working is also a significant part of the employment proposition for highly skilled workers. UK Government research found that 86% of employees in high-skill occupations had access to some form of flexible working.

This can work in an SME’s favour.

A senior technology professional may have more influence in a business where technology is still developing than they would in a large organisation with established teams and layers of management.

For the right candidate, being able to shape architecture, introduce new systems, establish processes or influence technology strategy can be a significant attraction.

The key is to understand what the role genuinely offers rather than relying on generic statements about culture or career development.

Sell the Opportunity, Not the Size

An SME cannot always compete with a multinational on salary or benefits. It can, however, compete on the scope of the opportunity.

A candidate should be able to understand what they will be responsible for, what problems they will be expected to solve and what influence they will have.

For example, a senior engineer might prefer a role where they can influence technical direction rather than simply deliver within a narrowly defined function.

Similarly, an experienced IT leader may be attracted to an organisation where they can build a technology function rather than inherit one that is already established.

This makes the role itself part of the recruitment proposition.

Be Clear About Flexibility

Flexible working is now an established consideration for many technology professionals, but simply advertising a role as “hybrid” is unlikely to differentiate an employer.

Businesses should be clear about what flexibility actually means.

How often is someone expected in the office? Is the arrangement genuinely flexible? Can working patterns change when circumstances require it? Does the business support remote collaboration effectively?

Being precise gives candidates a more realistic understanding of the opportunity and reduces the likelihood of mismatched expectations later.

Give Technology a Voice

Senior technology candidates want to know whether technology is taken seriously by the wider business.

An SME may offer an attractive role, but if technology leadership has little influence over commercial decisions, investment or organisational planning, experienced candidates may question how much they can actually achieve.

Where technology is important to business growth, candidates should be able to see how their work connects to wider objectives.

This is particularly important when recruiting senior roles such as Heads of IT, CTOs, technology leaders and transformation specialists.

The CIPD’s 2026 guidance on AI and technology emphasises the importance of involving the right people in technology decisions and considering how new technology will affect jobs and working practices.

The candidate is not simply evaluating the job. They are evaluating whether the organisation will allow them to succeed.

Avoid Overloading the Job Description

SMEs can unintentionally make recruitment harder by trying to find one person who can do everything.

A vacancy might ask for infrastructure, cloud, cybersecurity, applications, project management, vendor management and strategic leadership experience in a single role.

The result is often a candidate profile that barely exists.

Before advertising, employers should separate essential capabilities from desirable experience. They should also consider which skills can be developed after joining and which genuinely require previous experience.

This is particularly important as technology roles continue to change. The UK Government’s 2026 AI Labour Market Survey found that 97% of organisations surveyed identified at least one AI skills gap, with both technical and non-technical capabilities affected.

This is particularly important in specialist technology recruitment, where transferable skills can be more valuable than an exact match against every technology listed in a job description.

Make the Recruitment Process Match the Role

An SME can lose strong candidates through a recruitment process that is unnecessarily slow or unclear.

Technology professionals with specialist skills are likely to have other options. Long gaps between interviews, unclear decision-making and changing requirements can make an otherwise attractive role less appealing.

The wider UK labour market does not remove this pressure. The CIPD’s Summer 2026 Labour Market Outlook found that only 62% of employers planned to recruit over the following three months, with many businesses concentrating on maintaining existing staffing levels.

The process should therefore reflect the organisation’s priorities.

Candidates should understand what the business is looking for, who they will meet, how decisions will be made and what the expected timescale is.

A well-structured process also helps the employer assess candidates more effectively rather than relying on repeated interviews that add little new information.

Recruit for Impact

One of the strongest advantages an SME can offer is the opportunity to see the results of someone’s work.

In a smaller organisation, a technology professional may be able to introduce a new platform, improve security, modernise infrastructure or establish a development function and see the impact directly.

Employers should therefore explain what success looks like.

Instead of simply describing responsibilities, explain what the person will have the opportunity to change.

That gives experienced candidates a clearer reason to join and gives the organisation a stronger basis for assessing whether someone is genuinely suited to the role.

Know When You Need Specialist Advice

Some technology vacancies are difficult because the market is difficult. Others are difficult because the role has not been defined clearly enough.

This can happen when an SME knows it needs senior technology expertise but is uncertain whether it needs a CTO, Head of IT, Transformation Director, architect or another specialist.

Engaging specialist advice before the vacancy is formally opened can help clarify the capability required, establish realistic expectations and identify where the available talent market may differ from the organisation’s initial assumptions.

That early work can also prevent businesses from spending weeks recruiting for a role that was unlikely to attract the right candidates in the first place.

Compete on What You Can Offer

SMEs do not need to become larger employers to compete for technology talent.

They need to understand what makes their opportunity valuable and present it honestly.

For some candidates, that may be influence and autonomy. For others, it may be flexibility, technical challenge, career progression or the opportunity to build something from the ground up.

The strongest approach is not to imitate the largest employers. It is to identify where a smaller organisation can offer a better professional opportunity and build the recruitment process around that.

Conclusion

Technology talent does not automatically choose the biggest employer.

Experienced professionals choose roles where the work, environment and opportunity make sense for their career. An SME may have less financial scale than a large organisation, but it can often offer greater influence, broader responsibility and a more visible connection between an individual’s work and business outcomes.

The challenge is making those advantages clear.

For employers, that starts before a vacancy is advertised. Defining the role properly, understanding the available talent, setting realistic requirements and communicating the opportunity clearly can have as much influence on recruitment success as the salary attached to the position.

Competing for technology talent is therefore not simply a question of offering more.

It is about understanding what the right candidate values — and building a role that gives them a compelling reason to choose your organisation.

Key Takeaways

• SMEs do not have to compete on salary alone. Scope, autonomy, flexibility and influence can make smaller employers attractive.
• The role itself is part of the recruitment proposition. Candidates need to understand what they will be able to achieve.
• Avoid unrealistic wish lists. Prioritise genuine requirements and consider transferable skills.
• Be specific about flexibility. Clear expectations help attract suitable candidates and prevent mismatches.
• Technology candidates need confidence in the organisation. Senior professionals want to know that they will have the support and influence needed to succeed.
• A strong recruitment process matters. Delays and unclear decision-making can cause employers to lose candidates.
• Define difficult roles before advertising them. Specialist advice can help establish what capability is actually required and what the market can realistically provide.

Hiring the right Business Analyst can be difficult because job titles do not always tell you what someone has actually done.

Two candidates might both have “Business Analyst” on their CVs while having very different experience. One may have spent most of their career documenting requirements. Another may have worked across complex transformation programmes, challenged existing processes and helped shape the solution.

For employers, assessing Business Analysis experience therefore requires more than matching keywords on a CV. The focus should be on what the candidate has delivered, the problems they have solved and how they have worked with stakeholders.

Look Beyond the Job Title

Business Analyst roles can vary significantly between organisations.

Some positions focus heavily on requirements gathering and process mapping. Others involve strategy, technology implementation, business change, data, product development or large-scale transformation.

The job title alone cannot tell you which type of experience a candidate has.

When reviewing applications, look for evidence of the candidate’s responsibilities and outcomes. A strong CV should give you an indication of the environments they have worked in, the complexity of the projects they supported and the stakeholders they worked with.

This is particularly important when hiring for transformation roles, where experience in a similar environment can be more valuable than simply having held the same job title.

Assess the Complexity of Their Experience

Not all Business Analysis experience carries the same level of responsibility.

A candidate who has worked on a small internal system change may have useful skills, but their experience may not transfer directly to a major technology transformation.

Consider the scale and complexity of previous projects. What systems or processes were involved? How many teams were affected? Did the candidate work across multiple business functions? Were there competing requirements or difficult stakeholders?

These questions help establish whether someone’s previous experience matches the demands of the vacancy.

Look at What They Actually Delivered

A strong Business Analyst should be able to explain the contribution they made to a project.

Rather than simply saying they “gathered requirements”, candidates should be able to explain what they discovered, how they analysed the problem and what happened as a result.

For example, did their analysis lead to a redesigned process? Did they help define requirements for a new system? Did they identify a problem that changed the direction of a project?

The distinction matters because employers are ultimately hiring people to solve business problems, not simply to complete a list of activities.

Assess Stakeholder Management

Business Analysts often sit between business and technology teams. Their ability to communicate with different stakeholders can therefore be just as important as their technical knowledge.

Candidates may need to gather requirements from senior stakeholders, challenge assumptions, resolve conflicting priorities and explain technical concepts to non-technical colleagues.

During an interview, ask candidates about situations where stakeholders disagreed or where requirements were unclear. Their answers can reveal how they approach difficult conversations and whether they can move a project forward when there is no obvious solution.

Skills England’s 2026 research identifies problem-solving, decision-making, communication, collaboration and adaptability as important capabilities across digital and technology roles.

Test Their Problem-Solving Approach

Business Analysis is not simply about documenting what people tell you.

Good analysts investigate why a problem exists, challenge assumptions and consider different ways of addressing it.

Interview questions should therefore give candidates an opportunity to demonstrate their approach to a problem.

You might ask them to describe a situation where the original requirements were incomplete, contradictory or technically difficult to deliver. Their response can show how they investigate problems, work with stakeholders and reach a practical outcome.

This can be more revealing than asking whether they consider themselves a “good problem solver”.

Understand Their Technical Knowledge

The level of technical knowledge required from a Business Analyst varies considerably.

A role supporting a software implementation may require an understanding of systems, integrations and data. A Business Analyst working on a digital transformation may need to understand how technology affects wider business processes.

That does not mean every Business Analyst needs to be technically specialised.

Instead, employers should define the level of technical understanding the role actually requires before assessing candidates. This prevents businesses from rejecting strong analysts simply because they cannot demonstrate skills that the job does not genuinely need.

Assess Their Requirements Experience

Requirements analysis remains a core part of many Business Analyst roles, but employers should look at how candidates approach requirements rather than simply whether they have experience gathering them.

Strong candidates should be able to explain how they identify requirements, validate them with stakeholders and manage changes throughout a project.

It’s also useful to ask how they deal with requirements that conflict with business objectives, technical constraints or project timelines.

These situations provide a clearer picture of a candidate’s judgement than a list of requirements-management tools on a CV.

Look for Adaptability

Digital transformation projects rarely remain exactly as they were at the beginning.

New information can change requirements. Technology can introduce new possibilities. Business priorities can shift.

A Business Analyst therefore needs to adapt while maintaining a clear understanding of the project’s objectives.

This is becoming increasingly relevant as AI changes technology and business processes. UK Government research published in 2026 shows that employers need different levels of AI capability across their workforces, from people who use existing AI tools to those who implement or develop AI systems.

For employers, the question is not necessarily whether a Business Analyst has used every new AI tool. It is whether they can understand new technology and assess how it could affect the business.

Use the Interview to Validate the CV

A CV should start the assessment, not finish it.

If a candidate claims experience with a major transformation programme, ask them to explain their role in it. What problem was the organisation trying to solve? What did they personally do? Which stakeholders did they work with? What changed because of their analysis?

Strong candidates should be able to explain their experience clearly and consistently.

This approach can also help distinguish between candidates who genuinely owned significant responsibilities and those who worked within a large programme without having direct responsibility for the areas described on their CV.

Define the Right Requirements Before You Recruit

One of the biggest recruitment challenges comes from creating a Business Analyst specification that tries to cover everything.

Requiring experience across multiple industries, methodologies, technologies and transformation environments can dramatically reduce the available candidate pool.

Instead, employers should identify the capabilities that are genuinely essential for the role. From there, they can separate requirements that a candidate must already have from skills that could be developed after joining.

This creates a more realistic candidate profile and makes the recruitment process easier to assess consistently.

What Makes a Strong Business Analysis Hire?

The strongest Business Analyst is not necessarily the candidate with the longest list of qualifications or tools on their CV.

Relevant experience, analytical thinking, stakeholder management, communication and the ability to understand business problems all matter.

For employers, the key is to assess what candidates have actually done, rather than relying on job titles or keyword matches.

A clear understanding of the role, combined with evidence-based interviewing, can make it much easier to identify Business Analysts who have the experience needed to contribute to a transformation programme.

Ultimately, good Business Analysis recruitment starts with a clear question: what problem does this person need to solve, and what evidence shows they can solve it?

Digital transformation roles can be difficult to recruit for because they rarely fit neatly into one skill set. Employers may need someone who understands technology, but they also need someone who can work with stakeholders, manage change and connect technical work to business goals.

That makes a strong digital transformation candidate more than someone with the right technical experience. For hiring teams, the challenge is finding the combination of skills, experience and behaviours that will allow someone to deliver transformation successfully.

What Skills Do Digital Transformation Candidates Need?

Digital transformation candidates need a mix of technical, business and people skills.

The balance depends on the role. A Business Analyst will need different technical knowledge from a Project Manager, while a Transformation Lead will need a broader understanding of strategy, delivery and organisational change.

Technical knowledge still matters, particularly when the role involves technology implementation. However, employers also need people who can understand business requirements, identify problems and work with different teams to find practical solutions.

Skills England’s 2026 research identifies problem-solving, decision-making, learning, digital literacy and adaptability as important capabilities across digital and technology occupations. It also highlights the growing importance of collaboration and communication as AI changes how technology work is performed.

For recruitment teams, this means defining the actual capabilities required for the role rather than simply creating a long list of technical requirements.

Business Understanding Matters

Digital transformation should ultimately support a business objective.

That might mean improving customer experience, reducing costs, replacing outdated systems, increasing efficiency or enabling growth. A candidate who understands the technology but cannot connect it to those objectives may struggle to deliver the expected results.

Strong transformation candidates can explain why a change is needed, not just how to implement it.

This becomes particularly important in senior roles, where transformation leaders often need to work with stakeholders who are focused on commercial and organisational outcomes rather than technical detail.

Stakeholder Management Is a Core Skill

Transformation affects people across an organisation, making stakeholder management an important part of many transformation roles.

A candidate may need to work with technology teams, business leaders, suppliers, customers and employees, often with competing priorities.

Strong candidates can adapt their communication to different audiences. They can explain complex issues clearly, challenge decisions when necessary and build agreement without losing sight of the programme’s objectives.

For hiring managers, these capabilities can be difficult to assess from a CV alone. Interviews should explore how candidates have handled disagreement, competing priorities and difficult stakeholders in previous roles.

Look for Evidence of Change Delivery

Experience with technology does not automatically mean experience with transformation.

Someone may have worked on a system implementation without having responsibility for the wider business change surrounding it. Another candidate may have managed a programme involving new technology, redesigned processes and changes to how employees work.

Those are very different experiences.

When assessing candidates, employers should look for evidence of what changed, what the candidate was responsible for and what happened as a result.

Asking someone to explain a specific transformation they delivered can reveal much more than simply asking whether they have “transformation experience”.

Problem-Solving and Decision-Making

Transformation rarely follows the original plan.

Requirements change. Technology creates unexpected problems. Stakeholders disagree. Projects encounter budget or resource constraints.

Strong candidates can work through these problems without losing sight of the wider objective.

The UK’s Essential Digital Skills Standards reflect the impact of technological change, with the updated standards expanding the digital skills adults need for life and work in response to developments including artificial intelligence.

For employers, this makes it worth exploring how candidates approach unfamiliar problems rather than assessing experience alone.

Adaptability Is Becoming More Important

Technology changes quickly, and digital transformation professionals need to keep learning.

AI makes this even more important. New tools can change processes, create new opportunities and alter the skills required within a team.

A candidate does not necessarily need experience with every new technology. What matters is whether they can understand new technology, assess its relevance and apply it appropriately.

The UK Government’s 2026 research shows that employers need different levels of AI capability across their workforces, from people who use AI tools to those who implement or develop AI systems. This suggests that AI skills requirements extend beyond specialist AI roles.

For employers, learning ability and adaptability can therefore be useful indicators of future potential.

Technical Skills Still Matter

A focus on transferable skills should not mean overlooking technical capability.

Digital transformation candidates still need enough technical understanding to work effectively with technology teams and make informed decisions. The level required will depend on the position.

A Project Manager may not need to write code, but they should understand the technology being implemented well enough to manage dependencies, risks and delivery.

A Business Analyst may need stronger knowledge of systems, data and processes because they will translate business requirements into practical solutions.

A senior technology or transformation leader may need to understand architecture, data, security and emerging technologies at a strategic level.

The key is to assess the technical depth the role actually requires, rather than making every transformation vacancy a search for a technical specialist.

Cultural Fit Should Not Become a Hiring Shortcut

“Cultural fit” often appears in senior recruitment discussions, but employers should be careful about using it too broadly.

Hiring managers may describe a candidate as a “good cultural fit” without clearly explaining what that means. This can create subjective assessments and potentially exclude candidates who bring different perspectives.

It is more useful to assess specific behaviours.

Can the candidate collaborate effectively? Can they challenge senior stakeholders? Can they handle uncertainty? Can they communicate difficult information? Can they work across different functions?

These questions give employers something concrete to assess.

How Should Employers Assess Digital Transformation Candidates?

The strongest recruitment processes focus on evidence.

Rather than asking candidates whether they are good communicators or problem-solvers, ask them to describe situations where they had to use those skills.

A strong interview might explore a transformation that faced resistance, a project where requirements changed or a situation where the candidate had to make a difficult decision with incomplete information.

The answers can reveal how someone actually works rather than how well they can describe themselves.

Employers should also separate essential requirements from desirable experience. Requiring every possible skill can make an already competitive candidate market even smaller.

What Makes a Strong Digital Transformation Candidate?

There is no single profile that defines a successful transformation professional.

The strongest candidates usually combine relevant technical or functional expertise with business understanding, communication, problem-solving and the ability to work through change.

For employers, the most important step is to define those requirements before starting the search. A clear role profile makes it easier to identify suitable candidates, assess experience consistently and avoid filtering out people who could deliver simply because their CV does not match every requirement.

In a changing technology market, the strongest digital transformation candidate is not necessarily the person with the longest list of skills. It is often the person who can connect technology, people and business outcomes while adapting as the transformation evolves.