AI In Software Development: How The Role Of Developers Will Change In The Future

AI is radically transforming many areas of technology. No longer is it a case of whether AI should be used in software development, but how we can implement AI in software development, prioritising efficiency and effectiveness.

Despite OpenAI’s CEO Sam Altman’s recent assertion that as AI tools have the ability to complete extensive coding tasks, “…why would [companies] continue to hire actual human engineers?”, many in the industry believe that AI will complement human software developer skills and evolve the role – not replace them.

What is the impact of AI in software development at present?

Over the last few years, AI tools have been driving innovation within the software development sector, particularly through writing and debugging lines of code.

Currently, around 82% of software developers are using AI in their workflows to write code and 50% are using it to help debug code. These tools are not replacing developers, as Sam Altman described, but are actually being used by developers as a tool to increase productivity and complete sprints faster.

The key ways developers are using AI to increase efficiencies include:

Writing code – Natural Language Processing (NLP) tools such as GitHub and GitHub Copilot are being used to aid developers in writing code through generating suggestions for the next lines of code based on what the developer is creating. This can help speed up the process, but with developers still in the driving seat.

Debugging code – Whilst developers are less likely to use AI within debugging tasks, AI tools have the ability to detect vulnerabilities or inefficiencies in code, and either autocorrect them or can suggest solutions to the developer.

Testing code – Manual tests undertaken by developers can be long and repetitive. Automating the testing process can reduce the time developers need to spend on testing within a particular lifecycle, enabling them to move forward in a project quicker.

Furthermore, AI tools have also been involved in more routine tasks such as documentation and project management.

The current limitations of AI in software development

Despite nearly 30% of software developers in a survey of 550 respondents stating that they believe their development skills will be replaced by AI in the foreseeable future, there are a number of clear limitations currently in AI that means that AI tools will not replace human developers any time soon. Many believe elements of these limitations will never go away, which means software developer skillsets will never become obsolete.

• Bias

AI is made by humans, which makes it inherently biased. Many of the issues in using AI in software development come from problems in the way the AI model has been trained. If the data used to train these tools includes biased material, the tool can perpetuate these discriminatory biases. This can be particularly pertinent in software development systems that are being used in situations with human interactions and key decision-making.

• Security issues

Complacency with how reliable an AI tool will be at fixing bugs and vulnerabilities can lead to incorrect codes remaining or bugs being overlooked. In their current state, AI tools for software development are nowhere near 100% reliable and their actions need to be checked and vetted by human developers.

• Overreliance on AI

If software development gets to a point where AI is replacing developers or taking over large sections of the SDLC (Software Development Life Cycle), this could erode fundamental programming skills. In a worst-case scenario, if AI tools handle 100% of software developer responsibilities, then the skills would eventually die out or could be developed beyond human capabilities, which would cause major issues within computing.

• Lack of transparency

Not all AI models have been created with full transparency. There are no official guidelines that force AI models to provide clarity to users regarding what data has been used and how the tools have been programmed. This can make it difficult for developers to understand why the tools they are using are making certain decisions and lead to challenges in the lifecycle process. This would then have a knock-on effect on the project and ultimately, the business.

How can developers adapt to the growing use of AI in software development?

In the distant future, while AI will not replace human developers, AI’s impact in software development will mean that it will likely change the roles and responsibilities of software developers.

With AI taking over day-to-day tasks, developers will need to adapt to remain valuable. This might include:

• Work on creative thinking, such as being able to design more complex systems or identifying out-of-the-box solutions to solve complicated problems, as currently AI tools do not have the ability to work creatively.
• Embrace AI through learning about the different AI tools involved in a software development lifecycle and gaining skills in data science and analysis. Doing so can help developers use AI to boost their skills and employability.
• Focus on the human side of software development, such as building relationships with clients and businesses, and working with key stakeholders to advise on their development needs and potential innovations.
• Specialise in a particular sector such as healthcare or finance. By having a deep understanding of the regulations in the sector or the best workflow designs to suit a particular project, developers will continue to be essential in certain industries.

How will junior developers fair in the future?

Junior developers are likely to experience the greatest impact of AI in software development, as currently AI tools are beginning to take on simpler tasks such as generating simple lines of code and debugging them. This is where many senior developers learned and practiced their skills, so there is a risk that with AI taking over parts of a software developer’s responsibilities, there will be no space for junior developers to grow into senior developers.

There is a chance that fewer software developer graduates will be hired and the current pipeline to senior development may be disrupted. Instead of checking and debugging lines of code generated from senior developers, junior developers may become more used to testing and debugging AI generated lines of coding instead. Many junior developers will need to embrace and gain a deep understanding of how to use AI tools to position themselves as a valuable commodity in the future.

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