5 ways to prepare for the impact of generative AI on the IT profession

The rise of generative artificial intelligence (AI) is often seen as a reason to be scared. Some experts believe emerging technologies are developing capabilities to complete tasks quicker and more effectively than their human counterparts.

Research suggests technology leaders feel about 17% of IT jobs could be lost to automation. Whether that proportion is correct is up for debate, but what’s already certain is IT professional roles are set to change forever.

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So, how can technology workers prepare for the transformation in responsibilities? Five business leaders give us tips on how IT professionals can get ready for change.

1. Develop a good grounding

Nigel Richardson, SVP & CIO Europe at PepsiCo, says the fact that AI can write code effectively won’t mean blue-chip businesses like his don’t need programmers — in fact, he sees the rise of generative AI as an opportunity for IT professionals.

“It’s going to make some of the boring parts of programming quicker and easier,” says Richardson. With AI picking up the slack for some areas of development work, he advises IT professionals to focus on three underlying areas: Compute, algorithms, and data.

“I would always focus on having — and particularly early in my career — a good broad grounding in the different technologies because you still want to learn some of the core infrastructure skills,” he says. “There’s a lot of infrastructure in the cloud now, but you’ve still got kit you need to look after.”

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Richardson says to ZDNET that IT professionals should also learn the finer details of machine learning. Finally, he points to the importance of learning how to exploit data safely and securely. 

“Data governance sounds like a boring topic, but it’s a key part of what we do,” he says. “When you think of those three things — the compute, the algorithms, and the data — then you need to understand all of them. And then you can become a specialist in an area like information security. But I would always try to get that broad grounding.”

2. Aim to become a generalist

Nic Granger, director of corporate and CFO at North Sea Transition Authority (NSTA), agrees that a good technical grounding is still crucial for IT professionals in an age of AI — but that advice comes with a subtle twist.

“I’m not convinced about people choosing to focus on one particular skill,” she says. “If you do a computer science degree and learn C++, are you still relevant in five, 10, or 15 years? It’s difficult to know.”

What’s easier to understand, says Granger to ZDNET, is that wedding yourself to a single language or skillset is likely to restrict your career opportunities.

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“Having the skills to adapt and learn new technologies is important. For example, I think there will be degrees looking at how to prompt generative AI rather than how to do the underlying coding,” she says. “Becoming more of a generalist will become more important for people in the digital and data professions.”

3. Augment your human skills

Caroline Carruthers, CEO at consultancy Carruthers and Jackson, thinks of AI as augmented intelligence rather than artificial intelligence.

“The blend of using the right tools with the humans to control it excites me,” she says. “I love the idea of getting rid of the boring, repeatable, transactional work, so people in IT can focus on the interesting stuff and solve the challenging problems.”

Carruthers says to ZDNET that patience is the key to using AI to augment human skills. Yes, AI has the potential to do more of the boring stuff, but only if people approach emerging technology without prejudice.

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“It’s all about trying to help IT professionals see what’s in it for them without the fear. With AI, if it doesn’t solve the first answer, people think it’s wrong. With something like Copilot, it learns from you, so you must keep using it,” she says. “It’s like the way you work with graduates. If you get a graduate through the door, and the first thing they do is bad, you don’t go, ‘Let’s get rid of them.’ Instead, you take the time, and you help them to learn. If you’re doing something with AI, you must use the same process.”

4. Focus on value-generating areas

Craig Donald, CIO at The Football Association (FA), says his organization is already thinking about the potential impact of AI on the IT profession. 

“Internally within technology, we’ve just kicked off some trials with the development teams,” he says to ZDNET, suggesting this work is at the “pre-beta stage.” One of the areas his team is looking at is how AI can be used to deal with unit testing, which is a method that checks units of source code to ensure they are fit for purpose.

“It’s one of these things that, if you ask a developer, they don’t want to sit and write a document about unit testing — they want to go and build the code,” he says.

Donald says these initiatives will free up his IT professionals to focus on projects that add more value for The FA’s customers, whether that’s footballers, managers, administrators, or fans.

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“We’re looking at whether we can use some of the AI functions that have come out within GitHub and some of the other Microsoft tools to build some of those unit tests for us in a more automated fashion to get rid of some of that drudgery and to allow the teams to focus on the stuff that adds value,” Donald says to ZDNET. 

5. Hone your prompt engineering skills

Andy Moore, chief data officer (CDO) at Bentley Motors, says standing out from the crowd is tough in the fast-moving world of technology. He refers to generative AI tools like Copilot and how they can be used across the IT development process.

However, while new technology is crucial, Moore says to ZDNET that tech professionals shouldn’t forget the increased importance of prompt engineering skills. IT professionals who write prompts for generative AI will need excellent writing skills.

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“If you’re coding, whether it’s Python or SQL, the most common programming language is going to be English because we’ll use Copilot to augment the IT skills we already have,” he says. “I think understanding that process and delivering value is key. You need to think carefully about how you’ll leverage generative AI to generate value — and success is going to be about human plus AI.”