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.
When a fast-growing software company plants its global headquarters in a region, it does more than move desks. It changes hiring patterns, reshapes salary expectations, attracts new suppliers, and signals to investors that something serious is happening.
That is why Halo moving its global HQ into the Willis Building in Ipswich matters. It is not just a property story. It is a talent story. And from a hiring and resourcing perspective, it could mark the moment Suffolk’s SaaS ecosystem shifts from promising to industrialised.
Anchor Companies Change Labour Markets
Every major tech cluster starts with one or two anchor companies. These firms do not just create jobs. They create capability. They train people, spin out founders, attract recruiters, bring in investors, and raise the bar for what “good” looks like in that region.
Look at what happened in Stockholm. The success of Spotify did not just create roles inside one organisation. It helped turn Stockholm into one of Europe’s highest-producing tech hubs per capita. An overview from Stockholm Business Region highlights how the city continues to produce globally recognised SaaS and fintech scale-ups.
Spotify alumni went on to build or fund other ventures. Recruiters built specialist tech desks. Universities aligned courses to industry demand. Venture capital followed proven execution. The ecosystem industrialised because one breakout SaaS company proved it could be done.
Suffolk Has the Same Ingredients
Suffolk is not Stockholm. But ecosystems do not start as ecosystems. They start as outliers.
Halo’s decision to place its HQ in Ipswich sends a hiring signal. It tells engineers, product managers and commercial SaaS leaders that they can build a serious career without relocating to London, Cambridge or overseas. It tells investors there is execution capability locally. And it tells graduates that high-growth tech does not have to be something you watch from afar.
Regional growth patterns back this up. A report from Tech Nation shows that UK tech growth continues to decentralise beyond London, with regional hubs driving a larger share of scale-up activity than in previous years.
From a hiring standpoint, decentralisation changes everything. When a single high-performing SaaS business embeds itself in a region, it raises salary benchmarks, improves candidate quality, and encourages previously remote talent to consider local opportunities.
Industrialising Talent Means Repeatable Hiring Pipelines
Industrialisation sounds like a manufacturing term, but in SaaS hiring it means something simple: repeatability.
It means graduate pipelines feeding into structured onboarding. It means mid-level engineers trained into senior roles locally rather than imported. It means commercial leaders who understand subscription metrics, churn dynamics and ARR growth.
In Tel Aviv, anchor companies such as Wix helped normalise SaaS skillsets at scale. Today the region is globally recognised for its density of product and cybersecurity talent. Startup Nation Central notes in its 2026 ecosystem data that Israel maintains one of the highest concentrations of startups per capita globally.
“Startup Nation Central continues to showcase this remarkable ecosystem, where Israel ranks #1 in startups per capita, #1 in public companies on Nasdaq, #4 in R&D investment as a percentage of GDP, and #2 in innovation linkages.” – Startup Nation Central
That density did not appear by accident. It came from repeat hiring, spin-outs, and knowledge transfer.
If Halo continues to scale from Suffolk, it can create similar multiplier effects. Employees trained inside a high-growth SaaS environment often go on to found new ventures, join other local firms, or mentor emerging teams. Recruiters and resourcing partners then build specialisms around that sector. Universities adapt. Apprenticeships align.
This is how regions move from isolated tech employers to recognisable SaaS clusters.
The Resourcing Impact: Competition, Standards and Spin-Outs
From a hiring perspective, anchor HQ moves do three things almost immediately.
They increase competition for top talent. That pushes local businesses to sharpen their employer value proposition. It can feel uncomfortable at first, but it raises standards across the board.
They professionalise recruitment. As headcount scales, structured hiring replaces ad-hoc recruitment. Talent acquisition becomes data-driven. Workforce planning becomes proactive.
And they create future founders. Former employees take experience into new ventures. That is exactly what happened in Dublin after global SaaS and fintech players scaled operations there. IDA Ireland has repeatedly highlighted how multinational tech anchors strengthened the indigenous startup ecosystem by seeding experienced talent into the local market.
If Halo scales significantly from Ipswich, Suffolk could see a similar pattern over the next five to ten years.
Accountability and Execution Still Matter
None of this happens automatically. Anchor companies industrialise regions only if they continue to grow and invest locally.
That means building structured graduate schemes. Partnering with local colleges. Investing in leadership development. Supporting meetups and industry forums. Encouraging knowledge-sharing rather than operating in isolation.
It also means hiring with intent. If Halo builds a dense concentration of SaaS product, engineering and revenue leadership in Suffolk, it creates transferable capability. If hiring remains fragmented or overly remote, the multiplier effect weakens.
Stockholm’s growth was not just about Spotify existing. It was about Spotify embedding itself into the city’s ecosystem.
Why This Moment Matters for Suffolk
From a resourcing standpoint, Halo’s HQ move could represent a turning point.
It reduces the psychological barrier that serious SaaS careers require relocation. It improves regional credibility with investors and candidates. It encourages experienced professionals who moved away to reconsider returning. And it signals that Suffolk is not just a place to live – it is a place to build.
Industrialisation of talent is not glamorous. It is slow, structured and built on hiring discipline. But once it begins, it compounds.
If Halo continues to scale and embed in Ipswich, Suffolk could shift from being a location with tech companies to becoming a recognisable SaaS hub in its own right.
And in hiring terms, that changes everything.
Demand for Business Analysts in the IT field continues to grow as organisations work to transform digitally, improve customer experiences and extract value from data.
Hiring teams and talent strategists are increasingly focused on securing candidates who not only understand business needs but can translate them into workable technology solutions. In a competitive market for skilled analysts, knowing which capabilities truly matter helps hiring managers craft better job descriptions, assess talent more effectively, and build teams that can deliver meaningful outcomes.
1. Strong Requirements Gathering and Documentation
The ability to understand, elicit, and document requirements remains the foundational skill for Business Analysts in IT. At its core, this skill enables analysts to bridge the gap between business stakeholders and technical teams. An analysis of BA demand highlights that organisations increasingly value candidates who can ask insightful questions, unpack complex processes, and record detailed, clear requirements that development teams can act on. This ensures that IT solutions align with business needs and reduces costly rework later in delivery.
“A business analyst bridges the gap between business needs and technological solutions. With the ability to analyze data, identify inefficiencies, and recommend actionable improvements, BAs have become essential in driving profitability and performance.” – H2K Infosys
2. Data Literacy and Analytical Thinking
Business Analysts in IT are expected to work with data as much as with stakeholders. Today’s analysts need to interpret data, generate insights, and validate assumptions using quantitative evidence. This means knowing how to query data sources, interpret dashboards and use data to inform recommendations. A report on analytics and business roles confirms that data literacy is a top skill employers seek in BAs, reflecting how data-driven decision making has moved from an advantage to a necessity.
3. Technical Fluency
Although Business Analysts are not typically required to be software developers, they must be technically fluent enough to understand architecture, development constraints and integration challenges. This includes familiarity with APIs, cloud platforms, DevOps practices, and the software development lifecycle.
IT leaders increasingly emphasise this skill because it allows BAs to communicate effectively with engineers, anticipate technical trade-offs, and help ensure that solutions are not only desirable but feasible and scalable. In industry commentary, employers note that BAs who can “speak tech” reduce friction between business and delivery teams and accelerate project timelines.
4. Change Management and Stakeholder Engagement
Business Analysts frequently act as the connective tissue across departments. They manage expectations, navigate conflicting priorities and help business users adapt to new processes or systems. For IT transformations to succeed, BAs must be skilled at stakeholder engagement, influence without authority, and facilitating collaboration.
Organisations with strong stakeholder alignment and engagement, often led by Bas, were much more likely to achieve project success. This makes change management skills particularly valuable because they ensure adoption and value realisation beyond delivery.
“Better communication, as a result of good stakeholder engagement, leads to smoother project execution, fewer conflicts, and a higher chance of achieving project goals.” – Tigernix
5. Agile and Adaptive Delivery Mindset
The way software is delivered has shifted dramatically over the last decade, with agile methodologies now the dominant delivery model in IT. Business Analysts are expected to understand agile frameworks like Scrum and Kanban, contribute to backlog refinement, and support iterative delivery cycles.
More than ever, organisations value BAs who can adapt to changing priorities, break down work into incremental value slices, and work closely with product owners and delivery teams to ensure outcomes are continuously delivered and validated. In 2026, agile fluency, including facilitation of agile ceremonies and iterative requirement refinement, is routinely listed in IT BA job descriptions.
What This Means for Hiring and Resourcing
From a hiring and resourcing perspective, these top skills illustrate how the role of the Business Analyst in IT has evolved beyond simply documenting business needs. Today’s most in-demand BAs combine deep analytical capabilities, technical fluency, and strong interpersonal acumen. For recruiters, this means expanding candidate assessments to evaluate not only traditional business analysis experience but also data literacy, understanding of technical ecosystems, and proven ability to drive engagement across diverse stakeholder groups.
Organisations that align hiring strategies with these market-driven skills are more likely to build BA teams that contribute directly to strategic outcomes rather than just facilitating requirements. In a competitive talent landscape, prioritising these capabilities in job descriptions, interview frameworks and career development pathways helps ensure a strong pipeline of talent that can support sustainable digital value delivery.
In today’s competitive tech hiring market, attracting strong IT candidates is not just about salary. It is about clarity, credibility and alignment. Many organisations believe they have a talent shortage problem. In reality, they often have a messaging problem. Poorly written IT job descriptions quietly push away the very candidates hiring managers want most.
Recent hiring research shows that job seekers are increasingly selective, especially in software, cloud and cybersecurity roles. Candidates compare multiple offers, analyse company culture signals and look for transparency before applying. According to the Future of Recruiting report by LinkedIn, candidates are placing greater value on skills clarity, growth opportunities and flexible working arrangements when deciding where to apply. When job descriptions fail to communicate those elements clearly, applications drop.
Below are the most common reasons IT job descriptions fail to convert high-quality candidates into applicants.
1. The Role Is Too Vague
Top IT professionals want to know exactly what problem they are being hired to solve. Generic phrases such as “responsible for managing systems” or “working in a fast-paced environment” do not communicate real impact. Skilled engineers and analysts look for technical depth and measurable outcomes.
Hiring data shows that clear skills-based descriptions significantly improve application quality. When requirements are ambiguous, experienced professionals often move on to clearer opportunities.
2. The Requirements List Is Unrealistic
Many IT job ads still ask for ten years of experience in technologies that have only existed for five. Overloaded requirement sections discourage even qualified candidates from applying.
“Stop asking for 10+ years of experience or a specific college degree like it’s the only way to succeed.” – Forbes
High-performing engineers often skip roles that appear rigid or unrealistic, especially in markets where demand exceeds supply.
3. There Is No Mention of Career Growth
Digital professionals want to build long-term skills, not just complete tasks. If a job description focuses only on daily responsibilities without addressing growth pathways, training support or exposure to new technologies, it signals stagnation.
This survey from Deloitte found that career development opportunities are one of the top drivers influencing tech job decisions. A job description that fails to mention growth sends a clear message, even if unintentionally.
4. Compensation Transparency Is Missing
Salary transparency is no longer optional in many markets. Even where it is not legally required, candidates expect at least a salary range.
A hiring analysis from Indeed showed that job postings including salary ranges received significantly higher engagement than those without. In competitive IT sectors, omitting pay details can reduce applicant numbers dramatically.
5. The Language Is Too Corporate
Overly formal, buzzword-heavy descriptions feel outdated. Tech professionals respond better to straightforward, human language that reflects how real teams operate.
Candidates often scan job posts quickly. If the tone feels impersonal or filled with vague corporate jargon, it can reduce trust and authenticity. Clear, direct language performs better for both SEO and conversion.
6. Remote and Hybrid Flexibility Is Unclear
Flexible working has become standard expectation rather than a perk. If your job description does not clearly explain remote, hybrid or office expectations, candidates may assume the worst.
Data from McKinsey & Company used by HRDrive in this article showed that flexibility remains a critical factor in tech talent retention and attraction. Ambiguity around location policies creates friction at the very first stage of engagement.
7. The Tech Stack Is Not Clearly Defined
Experienced IT professionals care deeply about tools and architecture. They want to know whether they will work with modern cloud platforms, legacy systems or emerging AI frameworks.
Clear stack visibility signals technical maturity. It also improves search visibility, since candidates often search for roles by specific technologies rather than generic titles.
8. There Is No Sense of Impact
High-quality candidates want to know why the work matters. Does the role contribute to product innovation, digital transformation, cybersecurity resilience or customer experience improvements?
The Job Seeker Trends report from CompTIA highlighted that purpose-driven messaging increasingly influences tech career decisions. If impact is missing from the description, motivation drops.
9. The Hiring Process Feels Slow or Opaque
If a job description does not outline next steps or timelines, candidates may assume a slow process. In fast-moving IT markets, strong candidates are often off the market within weeks.
Transparency about interview stages and decision timelines signals organisational efficiency. Without it, candidates may prioritise competitors with clearer communication.
10. The Description Is Written for Compliance, Not Conversion
Many IT job descriptions are written to satisfy internal HR templates rather than attract people. They focus heavily on internal reporting lines, policy statements and compliance language while neglecting candidate experience.
Modern hiring is part marketing, part assessment. A job description is not just a legal document. It is a conversion tool. When written with clarity, authenticity and strategic positioning, it becomes one of the most powerful levers in attracting high-calibre tech professionals.
Final Thoughts: Job Descriptions Are Strategic Hiring Assets
In 2026, the IT talent market is competitive, selective and skill-driven. Organisations that treat job descriptions as strategic marketing assets outperform those that rely on outdated templates. Clear skills alignment, growth visibility, compensation transparency and authentic tone are no longer optional. They are baseline expectations.
If your IT job descriptions are not attracting strong candidates, the issue may not be a talent shortage. It may be how the opportunity is being presented.
As organisations move away from delayed reporting and towards live decision-making, real-time and streaming data engineers are becoming some of the hardest roles to hire. These engineers sit at the centre of systems that power fraud detection, live dashboards, operational monitoring and personalised customer experiences. From a resourcing perspective, the challenge isn’t just finding data engineers, it’s finding people with the right blend of real-time, cloud and operational skills.
Below are the five skills hiring teams should prioritise when recruiting streaming data engineers in 2026, explained in practical, non-technical terms.
1. Hands-On Experience With Streaming Frameworks
The most obvious and consistently requested skill is real experience with streaming platforms such as Apache Kafka, Apache Flink or Spark Streaming. These tools allow data to be processed continuously instead of in daily or hourly batches, which is what makes real-time intelligence possible. From a hiring perspective, candidates who have actually built and supported streaming pipelines in production are far more valuable than those with only theoretical exposure. Employers increasingly specify these tools in job descriptions because they underpin almost every modern streaming architecture.
“A focus on delivering hyper-personalized experiences, reducing operational latency, and deploying AI-powered insights across supply chains underscores the critical role of advanced streaming analytics platforms in maintaining competitive advantage.” – GlobeNewswire
2. Strong Programming and SQL Foundations
Despite the rise of specialised platforms, streaming data engineers still rely heavily on solid programming fundamentals. Languages such as Python, Java and Scala are commonly used to build, customise and maintain real-time pipelines. Alongside this, strong SQL skills remain essential for shaping data, validating outputs and making streaming results usable for analytics and reporting teams. For resourcing teams, this means avoiding candidates who specialise only in tooling and instead prioritising those with strong core engineering skills that will remain relevant as technologies evolve.
“The company says that when software application developers and data engineering professionals lack contextualized and trustworthy data, driving meaningful AI innovation becomes impossible.” – Forbes
3. Understanding of Event-Driven and Distributed Systems
Real-time systems behave very differently from traditional applications. Data arrives out of order, systems fail mid-stream, and performance issues can cascade quickly. This is why organisations are placing more value on engineers who understand event-driven architectures and distributed system behaviour. From a hiring standpoint, this skill helps teams avoid costly outages and performance bottlenecks by ensuring engineers know how to design systems that can recover gracefully and scale reliably.
4. Cloud and Platform Integration Skills
Most real-time data systems now run in cloud or hybrid environments, which makes cloud fluency a hiring priority. Streaming data engineers are expected to integrate pipelines with services such as AWS Kinesis, Azure Event Hubs or Google Cloud Pub/Sub, while also connecting to data lakes, warehouses and analytics platforms. For recruiters, this means looking beyond on-premise experience and prioritising candidates who understand how streaming fits into modern cloud ecosystems and managed services.
“This integration gap prevents organizations from leveraging AI effectively, as models require access to comprehensive, real-time data.” – Integrate.io
5. Operational Awareness and Monitoring Capability
Because streaming systems run continuously, operational awareness is no longer optional. Engineers must know how to monitor pipelines, detect issues early and respond before business users are affected. Skills in observability tools, alerting, logging and automation are increasingly mentioned in job ads for streaming roles. From a resourcing perspective, this is where many teams underestimate effort — hiring engineers who can operate and support live systems reduces long-term risk and prevents burnout across teams.
Why These Skills Matter for Hiring in 2026
For hiring managers and workforce planners, streaming data engineering is no longer a niche specialism. It’s becoming a core capability that supports real-time business operations across multiple departments. Teams that recruit for these five skills early are better positioned to deliver reliable live insights, set realistic project timelines and avoid overloading traditional data or cloud teams with responsibilities they weren’t designed for.
As demand continues to grow, organisations that understand what to look for, and why will have a significant advantage in attracting and retaining the right talent.
Delivering a new target operating model in a midsize business is a significant undertaking. It isn’t just about rewriting process diagrams or deploying new technology. It’s about reshaping how the organisation functions; how people work, make decisions, and create value. For hiring and resourcing teams, understanding what it takes to successfully deliver a new operating model is crucial. The way a business designs, staffs, and supports the transition often determines whether the changes stick or fade away after the initial launch.
What Is a Target Operating Model and Why It Matters
A target operating model describes how a business organises itself to deliver its strategy. It typically includes business processes, organisational structure, technology, governance, and metrics. When a business decides to change its operating model, it’s usually because existing ways of working no longer support growth ambitions, competitive pressures, or transformation goals.
Industry analysts describe operating model change as a key part of business transformation, especially for organisations looking to scale or innovate in fast-moving markets.
People Are at the Heart of Change
One of the first things hiring teams should recognise is that delivering an operating model change is fundamentally a people-centric challenge. While technology platforms and process redesigns are visible parts of the change, real success depends on how people adopt new ways of working. Talent resourcing strategies need to anticipate not just the skills required to build the model but also the capabilities to sustain it, from leaders who drive cultural alignment to operational teams executing daily work under the new model.
“In many cases, they are looking beyond previously established people management practices and people function (or HR) operating models and taking a step into the future of people management.” – McKinsey
Balancing Flexibility and Expertise in Midsize Businesses
For midsize businesses, one of the biggest considerations is balance. These organisations often sit between the agility of smaller companies and the complexity of larger enterprises. They may have fewer specialised roles but greater flexibility to shift priorities quickly.
“However, the key to a successful transformation lies in more than just technology implementation. It requires a well-defined Target Operating Model (TOM) that acts as a strategic guide, ensuring operations are optimized to drive growth and address future challenges effectively.” – SAPinsider
This means hiring and internal resourcing must be purposeful and aligned with what the new operating model aims to achieve. If a business is moving toward a customer-centric model, resourcing teams may need to strengthen roles in customer success, data analytics, and digital engagement, not just traditional operations or IT.
Governance, Metrics, and Measuring Success
Delivering a new operating model requires clear governance and value measures. Organisations should define success early and agree on metrics that matter, spanning customer outcomes, efficiency gains, financial performance, or employee engagement. Hiring teams should identify talent who can execute and also track, report, and optimise value delivery. Success metrics should be reinforced through coaching, incentives, and leadership behaviours.
External Expertise and Hybrid Roles
A common challenge in midsize businesses is that internal teams may lack experience with large-scale transformation initiatives. External expertise and hybrid roles often become critical. Organisations frequently bring in transformation leads, operating model specialists, or consultants to help design and implement changes while mentoring internal staff. These hybrid engagements help build internal capability while ensuring execution gaps don’t stall the project.
Technology, Tools, and People Integration
Midsize businesses may adopt new platforms, automation, or data tools as part of the operating model shift. Technology alone does not drive change; success comes when teams understand how to use these tools effectively. Resourcing practices should ensure that roles with both technical proficiency and operational context are present. This includes upskilling around data literacy, cloud solutions, workflow automation, or digital collaboration tools, depending on the model’s direction.
“Perhaps the biggest change is the realisation that the operating model is no longer static. Leading organisations now treat it as a continuously evolving system that is enhanced based on strategic priorities, external shifts, and internal learning.” – k3
Communication and Change Leadership
Communication plays a central role in operating model delivery. Employees need clarity on what is changing, why it matters, and how their daily work will be different. Hiring and resourcing teams can support this by ensuring change leadership, internal communications, and organisational development skills are present in the project team. Roles focusing on employee experience, stakeholder engagement, and organisational readiness help adoption happen faster and with less resistance.
Timing, Phasing, and Lifecycle Resourcing
Delivering a new operating model unfolds in phases: design, build, test, transition, and full adoption. Each phase benefits from different skills and capabilities. Staffing often focuses on design and planning early, but execution and sustainment capabilities may be overlooked. Hiring strategies that account for the entire lifecycle of the operating model, from design to run, will be more robust and less reactive.
Leadership Alignment and Accountability
Successful operating model change depends on leadership alignment. Leaders must not only support the transformation but embody it. Hiring for leadership roles should prioritise individuals with experience shaping culture, leading change, and holding teams accountable. Leadership reinforces new behaviours and ensures the operating model becomes embedded in day-to-day operations.
Conclusion: Aligning Talent with Transformation
Delivering a new target operating model in a midsize business is complex but achievable when organisations consider people, process, technology, and leadership holistically. For hiring and resourcing teams, it’s not enough to fill roles; teams must be intentionally shaped to support both the transition and the long-term model. Organisations that anticipate skill needs, invest in capability building, and align talent with strategic outcomes are better positioned to realise the value that operating model change promises.
As we move into 2026, organisations across industries are integrating artificial intelligence deeper into products, services, and ways of working. This shift is reshaping hiring priorities, meaning recruiters and resourcing teams are now looking for a blend of technical know-how, strategic thinking, and human-led oversight when filling AI-related roles. Understanding the key skills employers want can help hiring managers target the right talent and help professionals prepare for the most relevant opportunities.
1. Machine Learning Fundamentals and Model Understanding
Machine learning remains the core of most modern AI systems. Employers are looking for people who understand how models learn from data, how to evaluate their accuracy, and how to tune them for better performance. This skill isn’t just for specialists; even non-technical team members benefit from knowing the basics of supervised and unsupervised learning if they work with data-driven systems. Sources indicate that recognising how models work helps teams interpret outputs more wisely and collaborate better with technical leads.
2. Prompt Engineering and AI Workflow Orchestration
As generative AI tools become embedded in workflows, knowing how to shape effective prompts and integrate AI into broader processes is becoming essential. Prompt engineering has evolved from simply asking questions to structuring multi-step workflows that automate tasks and connect tools, data, and decisions. Professionals who can turn AI from a standalone tool into a scalable, integrated part of business processes are increasingly in demand.
3. Data Literacy and Feature Engineering
AI systems are only as good as the data fed into them, so data literacy (the ability to clean, interpret, and structure data) is one of the most sought-after skills. Hiring teams want candidates who can work with imperfect datasets, reduce bias, identify meaningful features, and ensure that AI outputs are grounded in high-quality inputs. This skill cuts across many roles because data is the backbone of AI deployment.
4. AI Governance and Responsible AI Practices
With AI becoming embedded in products and processes, organisations are increasingly focused on ethical, transparent, and compliant use of these technologies. Skills that cover bias mitigation, explainability, model monitoring, and compliance frameworks are now part of core hiring criteria for AI teams. Understanding where AI fails or misbehaves is just as important as knowing how to build it.
“The AI talent market has experienced unprecedented growth in 2025, with job postings increasing 74% year-over-year according to LinkedIn’s Global Talent Trends report. This surge comes despite broader tech industry layoffs, highlighting AI as a recession-resistant sector driving continued hiring.” – Hakia
5. Cloud and MLOps Infrastructure Skills
Deploying AI models at scale means understanding how to operate them reliably in production environments. This includes expertise with cloud platforms (such as AWS, Azure or GCP) and AI infrastructure tools that support continuous integration and deployment, monitoring, and version control of models. MLOps (machine learning operations) bridges engineering and operations to make AI systems reliable and robust for business use.
“Job postings mentioning Google Cloud rose from about 3 % to over 5 % in a year, while AWS mentions increased from over 12 % to nearly 14 %. Companies are migrating workloads and need engineers comfortable with containers, microservices and serverless functions.” – Cogent University
6. Programming Languages and Framework Fluency
Technical fluency remains a foundation. Languages like Python dominate AI roles, given their versatility and extensive libraries for machine learning and data analysis. Frameworks such as PyTorch and TensorFlow are widely used, and familiarity with them helps engineers build and refine AI systems efficiently. Recruiters often screen for this fluency because it signals readiness to contribute from day one.
7. Natural Language Processing (NLP) and Multimodal Skills
Ability in NLP (making machines understand and generate human language) continues to be a high-value skill as chatbots, virtual assistants, and conversational AI grow more common. Beyond text, multimodal skills that enable AI to work across text, images, audio, and more are becoming increasingly relevant for interactive and immersive user experiences.
8. Recommendation Systems and Personalisation Expertise
AI isn’t only about understanding data; it’s also about tailoring experiences. Recommendation systems help personalise content, products, and interactions for users, driving engagement and growth in sectors like e-commerce, media and SaaS platforms. Professionals who know how to design and tune these systems can make measurable business impact.
“Jobs requiring experience working with ‘recommendation systems’ offer the highest median salaries.” – Yiba
9. Distributed Systems and Performance Optimisation
Modern AI applications often run on distributed systems that must handle heavy loads and deliver responses in real time. Understanding how to design efficient distributed architectures and optimise performance helps organisations scale AI work without crippling latency or cost overruns. This skill is especially relevant to high-performance computing and large user bases.
10. Strategic Thinking and Change Management
Technical skills are crucial, but organisations increasingly recognise the importance of strategic and people skills in making AI initiatives succeed. Professionals who can guide cross-functional collaboration, manage organizational change and align AI projects with business outcomes are increasingly valuable. These higher-order skills help ensure AI delivers real value rather than becoming siloed or underutilized.
What This Means for Hiring and Resourcing in 2026
Hiring teams in 2026 are looking for more than just technical expertise. They want individuals who can bridge business needs and AI capabilities, support ethical and responsible use, and integrate AI into real-world workflows. As AI continues to transform roles and industries, building talent strategies around these ten skills can help organisations attract, retain, and grow the right people.
As we move through 2026, the technology job market is shifting in ways that matter for hiring, resourcing, and planning ahead. Some roles that looked promising a few years ago have now become core to business strategy, while organisations are investing more in skills that help them stay resilient, competitive and ready for change.
Based on current hiring trends and labour market demand, five tech roles stand out as the most sought after this year, and they reveal a lot about where teams are focusing their energy.
1. Cybersecurity Engineer / Analyst: Security First, Always
One of the most persistent trends heading into 2026 is the demand for cybersecurity talent. As organisations embrace digital transformation and expand their cloud, mobile, and data-driven platforms, the importance of securing systems has never been greater. Job postings and industry insight consistently show that cybersecurity analysts and engineers are topping demand lists, with organisations prioritising skills in threat detection, secure architecture, and incident response.
Growing breaches, regulatory pressure, and the need for proactive protection mean that teams need specialists who can help shape safer delivery pipelines and reduce risk across the organisation. This demand reflects a broader pattern where security expertise is becoming foundational rather than optional.
“As AI becomes embedded across industries, it’s driving expansion in cybersecurity, data sharing and a new generation of hybrid roles that combine technical skill, strategic judgement and ethical awareness.” – LSE
2. Cloud Engineer / Cloud Architect: Building the Backbone of Digital Services
Cloud computing remains central to modern IT strategy, and with nearly all new workloads projected to run on cloud-native platforms, engineers who can design, manage and optimise cloud infrastructure continue to be in hot demand. Cloud engineers and architects are expected to be well-versed in AWS, Azure, Google Cloud Platform, hybrid configuration, and performance/cost optimisation.
For hiring teams, this means planning ahead for professionals who can help organisations scale securely and efficiently, especially as workloads move further away from on-premise models and more into distributed, multi-cloud ecosystems. Organisations are looking for candidates who can translate business needs into cloud strategy, manage migrations, and build resilient systems that support ongoing growth.
“Cloud skills appear in 85% of tech job postings, making them virtually mandatory for modern developers.” – Hakia
3. DevOps Engineer / Platform Specialist: Enabling Fast and Reliable Delivery
Another role gaining momentum in early 2026 is the DevOps engineer, often paired with platform engineering responsibilities. While DevOps has been a well-established discipline for some time, the focus has shifted toward combining delivery speed with stability and quality. Teams are hiring DevOps and platform engineers who can build and maintain CI/CD pipelines, automate infrastructure, and support continuous delivery practices.
These skills are crucial for organisations that want to remove bottlenecks between development and operations, foster collaboration across teams, and ensure that new features and updates reach users quickly without sacrificing reliability. DevOps expertise also aligns closely with hybrid cloud and microservices environments, making it a versatile and strategic addition to modern IT teams.
4. Data Engineer / Analytics Specialist: Turning Data Into Competitive Advantage
Data remains a driving force in how businesses make decisions, spot patterns, and optimise performance. Specialised data engineers and analytics professionals are in high demand because they enable organisations to collect, clean, transform, and action complex datasets. Data engineering roles often support real-time analytics, data lakes, warehouse strategy, and the infrastructure needed to power machine learning or business intelligence.
Hiring and resourcing teams are prioritising these skills because companies of all sizes now rely on data proficiency to inform strategy, from operations and financial planning to customer experience and product development. These roles often sit at the intersection of technology, business insight, and strategic decision-making.
“The WEF ranks analytical thinking as the top core skill, while the CIO study shows analysis skills were required in over 19 % of tech postings in 2024 and over 21 % in 2025. Data science careers are expected to grow 34 % over the next decade.” – Cogent University
5. UX / Human-Centred Design Roles: Making Technology Work for People
Finally, UX (user experience) and human-centred design roles have risen in importance as organisations emphasise adoption, usability, and customer satisfaction. Although UX roles are sometimes overshadowed by more technical specialisations, they are increasingly in demand because software success now depends on intuitive interfaces and user journeys that help customers realise value quickly. Hiring teams are looking for UX professionals who can collaborate with product management, engineering, and business stakeholders to ensure experiences are clear, accessible, and aligned with strategic goals.
As the tech landscape becomes more competitive and user expectations rise, investing in UX talent helps organisations retain customers and reduce friction in digital interactions.
What This Means for Hiring in 2026
The common thread across these five roles is that they are not just technical jobs, but roles that tie directly to business outcomes. Cybersecurity protects trust and continuity. Cloud architects build the flexible platforms modern companies rely on. DevOps and platform specialists help teams move faster with confidence. Data engineers turn information into insight. UX designers make technology usable and valuable for people.
From a resourcing perspective, this means planning beyond surface job titles and considering how these roles interact with strategy, delivery, risk, and customer satisfaction. Organisations that align hiring with these priorities will be better positioned to adapt to change, innovate safely, and build products that users actually want to use.
When most people hear “blockchain,” they think of Bitcoin and other cryptocurrencies. But in 2026, organisations are increasingly exploring blockchain for applications outside of digital money, especially where security, transparency, identity, and trust matter. This broader adoption matters not just to technology teams, but also to hiring and resourcing leaders who are planning future capabilities.
Blockchain is being used to support secure digital identities, build transparent supply chains, verify product origin (provenance), and even manage enterprise compliance in new ways. These emerging use cases are creating demand for specialised skills and new kinds of roles in IT and operations teams.
“This shift reflects a broader understanding that blockchain is not merely a financial tool, but a transformational business platform.” – WebcomSystems
Supply Chain Transparency and Provenance Bring New Skills into Play
One of the clearest examples of blockchain outside cryptocurrency is in supply chain management and product provenance. Enterprises are using distributed ledgers to create tamper-proof records of goods as they move from raw materials to the finished product delivered to customers. This not only improves traceability and accountability, but also enhances compliance with regulations and helps brands prove ethical sourcing.
For hiring leaders, this trend translates into opportunities and challenges. Organisations need people who understand how to integrate blockchain with existing enterprise systems, how to ingest data from sensors or partners, and how to interpret and use immutable records for real-time decision making. Skills in blockchain architecture, distributed systems engineering, and integration with IoT or ERP platforms are increasingly valuable.
Digital Identity and Decentralised Verification
Another blockchain use case beyond crypto is secure digital identity, often called self-sovereign identity (SSI). Instead of storing credentials in centralised databases (which are high-risk targets for breaches), blockchain lets individuals and organisations hold and verify identity credentials cryptographically. This means better privacy, reduced fraud, and greater control for users.
For resourcing teams, identity use cases create demand for people who understand decentralised identifiers (DIDs), verifiable credentials (VCs), cryptography, and privacy-preserving systems. These are not typical skills on every IT resume, so organisations often find they need to invest in training, cross-skilling, or targeted recruitment to build teams capable of delivering secure identity solutions.
“By 2025, over 20 million citizens in countries like Estonia and Singapore use blockchain-based IDs for government services, per a 2025 World Bank report.” – Webiii3
Provenance and Anti-Counterfeiting
Blockchain’s ability to record an asset’s entire history (who touched it, when, and how it changed) is known as provenance. This is valuable in industries where authenticity is crucial: pharmaceuticals, luxury goods, electronics and industrial materials all use blockchain to track provenance and thwart counterfeit products.
This trend matters for recruiting because organisations need professionals who can build interfaces between business users and distributed ledgers, design data models that are both efficient and secure, and ensure that blockchain systems work reliably with external partners.
Tokenisation and New Business Models
Beyond identity and supply chain, blockchain enables tokenisation, the representation of real-world assets as digital tokens on a ledger. This can make assets like real estate, commodities or intellectual property easier to trade, divide or manage. This capability is seen spreading into corporate finance and operations, creating demand for roles that blend blockchain engineering with financial systems knowledge.
From a staffing perspective, bridging traditional business functions with technical blockchain expertise requires hybrid profiles, people who understand both the business logic of assets and how to represent them securely on a distributed ledger.
“Tokenization, aka converting assets into digital tokens, results in fractional ownership, quicker fundraising, and global investor participation.” – Hyperlink InfoSystem
What This Means for Hiring and Resourcing
The broader uptake of blockchain beyond cryptocurrency has several important implications for hiring and resourcing teams. Organisations are increasingly finding that blockchain initiatives require new competency areas that go beyond traditional software development. Roles focused on blockchain strategy, architecture, systems integration, and governance are becoming more relevant, particularly where decentralised identity, data provenance, and enterprise assurance are involved.
At the same time, the most in-demand profiles tend to be cross-functional. Professionals who understand security, cloud platforms, and distributed systems together are often more valuable than specialists who operate in only one domain. Many organisations discover that existing software engineers need additional training in cryptographic concepts, ledger design, and decentralised trust models to effectively contribute to blockchain projects.
Because enterprise blockchain use cases are still evolving, many teams are choosing to invest in internal upskilling rather than expanding headcount immediately. Structured training, pilot programmes, and partnerships with specialist vendors are common approaches to building capability while reducing delivery risk. Organisations that fail to plan for these skill requirements often end up reacting late, struggling to staff projects once timelines are already under pressure. This can delay adoption and undermine the very trust, transparency, and compliance benefits that blockchain is intended to deliver.
Conclusion
Blockchain’s reach has grown far beyond cryptocurrencies into practical, enterprise-focused use cases like secure identity, transparent supply chains, digital provenance, and tokenisation. These shifts are reshaping how IT and business teams operate and, equally importantly, how they hire.
For recruiters, IT leaders, and resourcing teams in 2026, understanding these trends and the associated skills is essential. The ability to plan and attract talent with blockchain architecture, decentralized identity, systems integration, and secure distributed systems expertise will make the difference between teams that deliver value and those that struggle with adoption.
Why Real-Time Data Is Gaining So Much Attention
In today’s fast-paced business environment, data no longer arrives in neat batches once a day or once a week. Instead, it flows continuously from sensors, apps, cloud platforms and customer interactions. Organisations that can capture and analyse that data as it happens (often called data streaming and real-time intelligence) are gaining an edge by making decisions faster, spotting opportunities earlier, and responding to problems before they grow. This shift is not just a technology trend; it’s reshaping how companies think about teams, skills and resourcing as we head into 2026.
“The increasing demand for instantaneous insights is fueling the adoption of streaming analytics solutions globally.” – GlobeNewswire
What Data Streaming Actually Means in Practice
At its core, real-time data streaming refers to the continuous flow of information through systems that can immediately process, analyse and act on data as it arrives. Platforms such as Apache Kafka, Apache Flink, AWS Kinesis and Azure Event Hubs are among the technologies that make this possible, and businesses are investing in these tools to unlock live insights that drive operations, customer experience, and innovation. For hiring teams, this trend means planning for new roles and skills that support these always-on data pipelines.
Why Organisations Are Moving Away from Batch Reporting
One of the biggest reasons interest in streaming analytics has grown so rapidly is that it supports faster, smarter decision-making. Instead of waiting for data to be collected, stored and processed overnight, organisations can monitor operations, customer behaviour, and market trends in real time, enabling more agile responses. A logistics firm, for example, can adjust delivery routes instantly based on live traffic data, and a financial institution can spot and block fraudulent transactions as they occur rather than after the fact. These capabilities are not just nice to have, they are increasingly part of how companies compete in sectors such as finance, retail, and telecommunications.
“It worked well when speed wasn’t critical. But in today’s hyperconnected world, where customer behaviors, transactions and machine signals evolve by the second, real-time data processing has become a competitive edge, not a luxury.” – OpsTree
The Impact on Teams and Ways of Working
For hiring and resourcing leaders, there are a few clear implications. Teams that built analytics around traditional batch reporting often relied on roles such as data engineers, BI analysts and database administrators focused on periodic reporting.
With real-time intelligence becoming more important, organisations now need specialists who can build and operate streaming data pipelines, integrate them with cloud infrastructure, and make live insights available to business stakeholders. Roles such as real-time data engineers, streaming architects, site reliability engineers (SREs) with event-driven system experience, and analytics engineers who understand continuous data workflows are increasingly in demand.
Another practical impact is on team planning and workload expectations. Building and maintaining real-time pipelines requires ongoing coordination between development, operations, security, and business analysts. Organisations that underestimate this hidden effort often find that project timelines slip or that teams are stretched thin caring for systems they don’t fully understand.
Hiring managers who recognise this early can proactively recruit or train teams with the right blend of skills, rather than reacting when delivery bottlenecks emerge.
“With stream analytics now being mission-critical, organizations put more emphasis on monitoring, auditing, and transparency. Tools that provide observability and track data lineage are becoming ever more important for compliance and long-term trust.” – Alibaba Cloud
Building Capability Through Hiring and Upskilling
Real-time intelligence also amplifies the need for cross-functional capability. Unlike batch analytics, which often sat with central analytics or IT teams, streaming data systems touch customer experience, risk, marketing and operations all at once. This necessitates people who can bridge technical and business domains, translating live data insights into actions that departments outside IT can understand and use.
Some organisations are also embracing cloud-native streaming analytics platforms to lower the operational burden. Managed services for streaming reduce the need for deep infrastructure expertise while still requiring strong data engineering and analytics capabilities so teams can focus on extracting value from the data rather than managing servers. Even so, recruiting for experience with these managed services and real-time data processing frameworks remains an important priority for IT leaders.
As demand for real-time data continues to grow, the skills organisations seek are evolving. Many are choosing to upskill existing staff in streaming technologies, while others are building dedicated real-time data teams. Either way, recognising the trend early allows hiring and resourcing teams to plan work fairly, budget for training where needed, and construct teams that can deliver live insights reliably.
Why This Trend Matters Going Into 2026
Data streaming and real-time intelligence are no longer experimental technologies. They are becoming part of how organisations operate day to day. For hiring managers, recruiters and IT leaders, this means planning ahead for the skills, roles and workloads required to support always-on data systems. Organisations that take a proactive approach are more likely to deliver reliable, insight-driven services, while those that ignore the resourcing impact risk falling behind despite investing in the right tools.
UX Is No Longer a “Nice to Have” in SaaS
Over the past year, hiring interest in UX skills, especially in Software-as-a-Service environments, has been steadily increasing. This renewed focus is not driven by flashy trends or design fads. Instead, it reflects a growing understanding that user experience has become central to how SaaS products succeed, retain customers, and generate long-term revenue. In crowded SaaS markets, where switching costs are low, poor usability quickly translates into churn. As a result, UX has shifted from a supporting function to a core business capability.
Industry commentary increasingly points out that organisations now compete on experience as much as functionality. This shift has pushed UX skills higher up the hiring priority list, particularly for companies trying to differentiate themselves in mature or highly competitive SaaS categories.
“Technology has become unavoidable in our daily lives—and where technology exists, design becomes the language that people interact with.” – LinkedIn
Why User Experience Directly Impacts SaaS Growth
SaaS products live or die by ongoing user engagement. Unlike one-off software purchases, subscription-based models rely on customers finding value quickly and consistently. Poor onboarding, confusing workflows, or clunky interfaces can cause users to disengage long before the product’s underlying capabilities are fully explored.
Research and industry reporting consistently show that well-designed user experiences improve retention, adoption, and conversion. This has made UX a commercial concern rather than just a design one. Many SaaS companies now see UX designers as contributors to growth, not just polishers of interfaces.
“Effective UI/UX design directly impacts the bottom line. A seamless, intuitive interface guides users toward key actions—signing up, purchasing, or subscribing—ultimately boosting conversions and revenue.” – Uplers
The Changing Shape of SaaS UX Work
Modern SaaS products are more complex than earlier generations of software. They often support diverse user roles, operate across multiple devices, and integrate with other platforms. As a result, UX work has expanded beyond visual design into areas like workflow optimisation, accessibility, personalisation, and behavioural insight.
Designers working in SaaS environments are increasingly expected to understand how users move through systems over time, not just how screens look in isolation. Trends such as adaptive interfaces, mobile-first design, and behaviour-driven personalisation are reshaping what good UX looks like and what skills hiring teams need to look for.
What This Means for Hiring and Resourcing Teams
From a resourcing perspective, this shift has important implications. UX roles in SaaS organisations now sit much closer to product strategy, customer success, and commercial decision-making. Hiring managers are no longer just looking for designers who can produce wireframes or mock-ups. They want people who can interpret user research, work closely with engineers and product managers, and explain design decisions in business terms.
This has also changed how candidates are assessed. Communication skills, stakeholder management, and the ability to balance user needs with technical and commercial constraints are becoming just as important as design craft. Recruiters increasingly favour candidates who can demonstrate impact, not just aesthetics.
“Hiring managers today are looking for designers who can operate across the design lifecycle—from research to wireframes to interactive prototypes. The most in-demand UX recruit skills 2025 go beyond basic UI tool use.” – Govt College of Art and Design
UX as a Cross-Functional Capability
Another reason SaaS UX hiring is picking up is that design no longer happens in isolation. UX professionals are now embedded in delivery teams that include engineering, data, marketing, and customer success. This requires designers who are comfortable working iteratively, handling feedback, and contributing throughout the product lifecycle.
For resourcing leaders, this means planning for UX capacity in a more integrated way. UX skills are needed not only at the start of product development, but throughout delivery, optimisation, and continuous improvement cycles. This sustained demand is driving more consistent hiring rather than sporadic design recruitment.
Why This Trend Is Likely to Continue Into 2026
As digital transformation continues across industries, SaaS products are becoming the default way organisations deliver services internally and externally. This increases the importance of intuitive, reliable, and user-centred design. Products that are powerful but difficult to use struggle to gain adoption, no matter how strong the underlying technology may be.
For hiring managers and resourcing teams, the takeaway is clear. SaaS UX skills are seeing renewed demand because they directly influence customer retention, product success, and business performance. Organisations that plan ahead for these capabilities are better positioned to build products people actually want to use, while those that treat UX as optional risk are falling behind despite heavy investment in technology.
The UK mergers and acquisitions landscape may be entering a period of structural change, particularly around how deals are being planned and executed. At first glance, news about regulatory consultations might sound like just another update in legal land. But when the UK government launches a formal consultation on reforming the merger control regime, it’s worth paying attention, especially if you’re hiring talent to support deal execution and integration.
The consultation, launched in January 2026, aims to make the UK’s competition framework more predictable, proportionate, and business-friendly, while retaining the Competition and Markets Authority’s independence. Proposals include changes to merger investigations to speed up decisions and offer clearer engagement with businesses and advisors.
“The consultation aims to make jurisdictional thresholds more predictable, enhance the CMA’s political accountability, and improve interactions between businesses and the regulator.” – Latham.London
From a headline perspective this might read like regulatory tinkering. In reality, it could slowly but meaningfully change how deals are structured, timed and staffed. Recruitment teams and hiring managers in M&A, project management, integration and change leadership roles should be thinking about how this might reshape demand for skills and timing of hires.
Why Regulatory Predictability Matters to Hiring
For years M&A professionals have told recruiters that one of the biggest bottlenecks in a deal isn’t valuation or strategy, it’s uncertainty around regulatory clearance timelines. Long or unpredictable merger control investigations can stretch planning horizons, delay resource planning and force hiring decisions to wait until “certainty” arrives. If the CMA’s process becomes more predictable and proportionate, that could help reduce one of the biggest unknowns in planning headcount for integration teams, HR transformation and post-deal execution.
“Our Strategy centres on promoting competition and protecting consumers with a clear end goal in mind: to drive economic growth and improve household prosperity.” – Gov.uk
This matters not just for lawyers and compliance specialists but for a whole ecosystem of talent: integration programme leads, PMO professionals, change management experts, and commercial HR partners. These are roles that often sit in the “execution” phase of a deal, but growing focus from buyers on early regulatory risk assessment means these functions are increasingly involved before signing. That early engagement drives demand for professionals who understand both commercial strategy and regulatory nuance.
M&A Activity Trends Still Suggest Opportunity
While volumes of deals dipped in some parts of 2025, deal value held up, especially in strategic, high-value segments. According to PwC, UK M&A activity saw fewer transactions in the first half of 2025, but average deal size rose and strategic sectors like financial services and technology remained active.
Market analysts for 2026 also point to ongoing consolidation strategies in mid-market deals and continued inbound investment saying that overall activity levels are likely to be similar to or higher than in 2025, thanks in part to sectors like software, AI-enabled businesses and private equity buy-and-build strategies.
“90% of our team predicts that dealmaking levels will be higher or broadly in line with 2025, and despite domestic caution, there is still significant dry powder within private equity and corporate balance sheets.” – PKF Smith Cooper
For hiring teams this means there’s demand where commercial strategy and execution intersect. Corporate development teams, private equity deal teams and advisory boutiques all look for people who can manage uncertainty and help execute with speed and confidence.
What This Means for Talent Demand
In a shifting regulatory environment, recruiters and hiring managers should be thinking about three key implications:
Firstly, hiring timelines are likely to extend if teams delay recruiting until after regulatory milestones. Firms that build bench strength in M&A project management and regulatory liaison roles will move faster and more confidently.
Secondly, professionals who can operate at the intersection of compliance, commercial strategy and execution will be especially valuable. This could be regulatory savvy PMO leads, integration directors who understand competition risk, or M&A lawyers comfortable guiding teams through complex multi-jurisdictional reviews.
Thirdly, uncertainty (even if reduced) still changes how deals move from intent to impact. Hiring teams should emphasise adaptability and cross-functional collaboration in role profiles, as deals in 2026 are likely to hinge on rapid assessment and execution across functions.
For Candidates: Why You Should Watch This
If you’re a professional in M&A, PMO, change leadership or integration, it’s worth watching how merger control reforms take shape. Talent demand often follows market friction points. When regulatory processes are seen as opaque or slow, firms tend to hoard seasoned advisors and regulatory specialists. If processes become clearer and more predictable, the emphasis might shift toward execution talent that can accelerate integration and deliver value quickly.
In other words, candidates who can bridge commercial outcomes with regulatory insight will stand out. And for hiring managers, defining roles that explicitly blend these skills will help attract this hybrid talent.
Final Thoughts
On the surface, regulatory reforms can seem dry. But when the UK government signals an intent to make merger investigations more predictable and proportionate, it’s not just legal teams that should pay attention. HR, integration, M&A operations and change leadership teams are directly affected by how deals are structured and cleared.
Deal activity may wobble in volume at times, but the ongoing need for strategic hires that can navigate uncertainty and aid execution means resourcing strategies need to evolve too. Organisations that anticipate these shifts and invest in the right talent early will be better placed to capitalise on growth and consolidation opportunities in the evolving UK M&A landscape.
Over the past few years, cloud adoption has become the default rather than the exception. Alongside that shift, the way software is built and released has also changed. Continuous Integration and Continuous Deployment, better known as CI/CD, is now how most modern teams deliver software. What is changing in 2026 is the growing expectation that security is built directly into these pipelines, rather than added at the end.
This move towards secure cloud CI/CD practices is not just a technical trend. It is reshaping how organisations think about team structures, skills, and resourcing.
What Secure CI/CD Actually Means in Practice
At a simple level, secure CI/CD means making sure security checks happen automatically as part of building, testing, and deploying software. Instead of waiting for a separate security review after code is written, vulnerabilities are caught earlier through automated scanning, policy checks, and controlled release processes.
In cloud environments, this often includes checking infrastructure-as-code templates, scanning container images, managing secrets safely, and enforcing access controls inside the pipeline itself. The goal is not perfection, but reducing risk before issues ever reach production.
For hiring managers, the key point is that this work sits somewhere between traditional development, cloud engineering, and security. That overlap is where many teams are currently under-resourced.
“In software development, a CI/CD pipeline refers to the automated steps involved in building, testing, and deploying code changes. Hardening this pipeline involves implementing security measures and best practices to ensure the reliability and security of the software delivery process.” – CloudSecurityWeb
Why This Matters for Hiring and Resourcing
Many organisations still plan teams as if security is owned by a single, separate function. In reality, secure CI/CD spreads responsibility across developers, platform teams, cloud engineers, and security specialists. When this isn’t reflected in resourcing plans, teams either slow down delivery or quietly accept higher risk.
Hiring teams are increasingly looking for people who understand both automation and security, even if they are not “security engineers” by title. Developers who can work with secure pipelines, cloud engineers who understand policy enforcement, and DevOps professionals who can balance speed with control are all becoming harder to find.
This also affects workload planning. Security checks take time to design, maintain, and respond to. If organisations do not account for this invisible effort, delivery timelines often become unrealistic, leading to pressure on teams and rushed releases.
“Involving both security and development stakeholders in the tool selection process increased adoption and reduced resistance.” – eajournals
The Shift Away from After-the-Fact Security
One of the reasons interest in secure CI/CD is rising is that traditional, end-of-cycle security reviews no longer scale. Cloud systems change too quickly, and manual reviews struggle to keep up with frequent releases.
From a resourcing perspective, this means fewer last-minute fire drills but more ongoing, embedded work. Teams need people who are comfortable improving pipelines incrementally, tuning security checks, and working closely with development teams rather than acting as gatekeepers.
Organisations that invest in these skills early tend to see smoother releases and fewer surprises later. Those that don’t often find themselves hiring reactively after an incident or audit failure.
“Integrating security into CI/CD pipelines creates a synergy between development and security teams, ensuring that risks are identified and addressed early. This integration also enables organizations to pivot quickly in response to emerging threats. By embedding security tools and practices early in the process, teams can catch issues before they reach production, minimizing the risks of exploitation in live environments.” – DataCalculus
What Hiring Teams Should Be Planning for in 2026
Secure cloud CI/CD practices are no longer a niche concern. They are becoming a baseline expectation for mature cloud environments. Hiring strategies need to reflect that by valuing practical experience with secure pipelines, not just theoretical knowledge of security or automation.
This does not always mean hiring more people. In many cases, it means hiring differently, prioritising adaptable, cross-functional skills and allowing time for teams to build security into their delivery processes properly.
As cloud environments continue to grow in complexity, secure CI/CD is emerging as one of the clearest signals of whether an organisation’s delivery model is sustainable. For recruiters and IT leaders alike, understanding this shift is essential to building teams that can move fast without breaking trust.