The Impact of AI on Software Development
27-01-20
Industry Analysis

The impact of AI on software development

Written By
Matthew Foot

Artificial intelligence (AI) is undoubtedly one of the biggest technology trends of the past decade, paving the way for driverless cars and ‘smart’ devices such as Google Home and Amazon Echo, among other innovations.

While AI isn’t necessarily a new technology, companies have only recently discovered ways of harnessing it to disrupt, transform and ultimately improve age-old products and industries.

This is certainly the case for software development, a discipline where the application of AI is already having a telling and transformative impact. Here, we take a closer look at the areas of software development being affected by AI and the benefits it can deliver for developers.

How AI Can Assist Software Development

The application of AI can deliver efficiencies at almost every stage of the software development life cycle (SDLC).

Requirement gathering & analysis

Given the need for conceptual thinking, this phase of the SDLC typically requires a high level of human intervention. However, AI tools such as Infosys Nia and Google ML Kit can minimise human involvement to a small extent, uncovering any loopholes before software moves into the design phase.

Software design

AI isn’t yet capable of planning and designing software from scratch, but it can reduce some of the human errors that often arise in the design phase. One example is AIDA (Artificial Intelligence Design Assistant), a website building platform that enables software designers to understand a client’s needs and present the most appropriate design.

Generating code

Writing the code for a large software project is both labour-intensive and time-consuming. To help ease the load, experts have started to explore AI solutions that create executable code prior to development. Not only does this help developers launch new products faster and more cost-effectively, but it also frees up time to focus on work that is less repetitive.

Automated testing

Testing is another time-consuming phase of the SDLC, albeit one that can be enhanced and made more efficient with the application of AI. Testim.io, Eggplant and Appvance are just a few examples of AI and machine learning tools that can create test cases and eradicate errors in the crucial testing phase.

Other Advantages of AI for Software Developers

Beyond what is outlined above, there are some other key benefits of applying AI to software development.

Improved data security

Security is one of the most crucial aspects of software development. A system will typically collect data from a customers’ network sensors and software. AI can help developers analyse the data, using machine learning to spot any irregularities, while also preventing any delayed warnings or false notifications.

Better bug fixing

The more data that needs to be tested, the higher the chances of human error and overlooked bugs. By auto-correcting codebases without any human intervention, AI makes it easier for developers to instantly identify bugs and fix them. This leads to better code and saves time that would otherwise be wasted on manual checks.

Accurate estimates

Estimating the cost of software projects can be a challenge, but many AI-powered solutions are helping to simplify the process. Employing predictive analytics, these tools analyse the data of previous projects to find any correlating features or statistics that can then be used to provide accurate estimates of time and budget.

Intelligent assistance

AI-based programming assistants can provide code examples, useful material and relevant suggestions to developers who need help debugging software or understanding technical documentation. This can free up their time to deliver higher-value work such as creating new features or improving user experience.

Speedy code compiling

Compilers convert code from high-level programming language into machine language or instructions for software to follow. This is often a time-consuming process, but one that can be made quicker with the use of AI-driven compilers. Because they don’t require the original source code, intelligent compilers can regenerate code within hours, not months.

The Future of Software Development

The adoption of AI only looks set to increase over the coming years, and with it comes an enormous opportunity for software developers and digital firms across East Anglia.

Whether you’re a developer looking for your next opportunity or an employer in need of a specialist resource, don’t hesitate to get in touch or check out our current vacancies. Alternatively, feel free to read more about our expertise in software development.