Why AI is the Perfect Partner for Software Engineers

­Each year, National Coding week helps raise the profile of coding and its related career paths in science, technology, mathematics and engineering. In 2024, the focus has been on Artificial Intelligence (AI) and its growing importance in the field of coding. Thales in the UK’s Charlotte Grinyer, Principal AI Researcher, provides some insights into how AI is impacting the role of Software Engineers, and what people should be doing if they’re interested in a career in the sector.

The AI Effect

Coding is fundamental to the world we know. Without coding, the technological environment doesn’t exist. It enables the tools and systems we use every day to interface with you, each other, and the wider world.

However, advances in AI have changed how coding is applied, leading to significant impacts on the roles and opportunities available to software engineers.

The emergence of AI has changed the role of a software engineer in several distinct ways:

1 AI is helping software engineers to work more efficiently in their day-to-day tasks, by alleviating some of the burdens, such as coding language.

2 As AI becomes more integrated into day-to-day tasks, it is creating a greater variety of roles and opportunities within software engineering.

3 The need for AI in a greater number of industries, products and services is increasing the demand for software engineers in non-traditional sectors – i.e. health and social care.

As with any new way of working, there are many challenges that must be overcome. As a leader in the field, Thales has to deal with several misconceptions of AI and provide real world opportunities for its use. It's important to understand that AI is not a one-size-fits-all solution. Creating effective AI models requires significant human involvement, time, and data. Despite our growing reliance on AI, it remains a tool that complements human effort rather than replaces it.

With great advances in generative AI, society needs to better understand its role, limitations, and risks, as well as how we can build trust in our own systems – all things that software engineers are looking to address.

Teaming up with the technology

AI isn’t replacing the role of software engineers, instead, it is serving as a valuable partner, freeing up time and space for more creative work. This is largely because AI can now handle many basic tasks of coding, or programming language. This enables faster product development, while giving engineers the space and time to focus on the more creative areas of high-level design and architecture.

Jay Rajan, a software engineer with Thales in the UK, explained what this meant for him:

“AI has increased our ability to be creative engineers, to think outside of the box, push the boundaries and problem-solve.  AI solutions undertake a lot of the manual process on behalf of engineers, which lets us deal with the critical thinking to help develop more innovative products.”

This also opens the door to people who wouldn’t necessarily consider a career in software engineering, as AI coding-partners lower the barrier to entry into the profession – with creativity and innovation just as valued as logic and an interest in data.

Of course, there will also always be a need for coding-focused engineers. The industry will always require professionals with the skills to evaluate AI partners – understanding how they work and developing better, more trustworthy, AI algorithms.

As Dave Philpott, a future systems architect with Thales in the UK, explained,

“Understanding the skills necessary to perform verification and validation of AI systems is critical for some roles. Developing a high-performing, AI-enabled system is only one side of the story. Ensuring that it performs reliably and with a high level of trust throughout the engineering lifecycle is equally important”.

AI in action

AI has moved from a future concept to an integral part of how we work and what we create. Within our defence and security projects, for instance, AI has rapidly become an essential tool to provide end-users with an advantage in a more dangerous world.

This is reflected in two ways: it enables users to perform their existing tasks more efficiently and effectively, while also completely redefining what users are capable of achieving. 

For example, in enhancing and augmenting the capabilities of soldiers in armoured vehicles.  Thales’ “Digital Crew” metaphorically sits next to the operator to enhance what they can “see” through the sensors – feeding in data from cameras and sights, enabling the soldier to act faster and make better decisions.

However, “Digital Crew” is also capable of using other inputs, such as acoustic sensors, to build an aural picture of the same environment – which can pin-point firing points before they can be seen – completely redefining what is possible.

Increasing demand for software engineers

Despite the growing role of AI in supporting software engineers, the demand for these positions continues to surpass the available supply. Compared to automation in manufacturing, which has led to fewer human workers, increased automation in software engineering has been accompanied by increased demand, as each new problem requires a unique solution from an expert in the field.  Rather than replacing the software engineer, automation has simply enhanced efficiency and allowed them to focus on innovation and creativity.

And, as the benefits of AI grow, so does the integrated environment that these systems and products operate within. More services, industries and sectors are increasingly requiring software engineers to help improve the functionality of their systems.

While those engineers still need to understand coding - to know how to get the most from AI - there are now greater opportunities for those with a skillset centred around creativity and inquisitiveness.

Understanding how humans will shape and use these solutions is also important, and the skills to be able to understand this are essential. Career opportunities in the safety of AI are also likely to grow, so understanding how to verify and validate the AI models and code is a big area for development.

Robert Ball, a graduate software engineer with Thales, added,

“Recognising the risks and how information is used by AI is important to make the most of it.

This is a skill in itself.”

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