£2 billion for AI – but who’s going to use it, and how?

The UK Government’s Spending Review this week confirmed a £2 billion investment into artificial intelligence. It’s a necessary move to back up the ambitions of the AI Action Plan. But I found myself asking the same question I always do when these announcements land:

Where’s the equivalent investment in people?

It’s not just me. A quote from the Institute of Physics regarding the separate 86bn for the science and technology sector echoed the same concern: if we’re going to pour billions into science and technology, we need a matching plan to grow the pipeline of skilled workers, saying “This must include a plan for the skilled workforce we need to deliver this vision” and to “underpin the industrial strategy.”

That's right. Without this, we risk a sort of ‘overbuilding’ - like a city plan that’s too ambitious, without enough laborers to complete the vision, which leads to unfinished infrastructure meaning no one can ever move in... and we end up with a ghost town.

AI skills are not just for engineers 

Much of the conversation is understandably focused on technical AI roles – and yes, we need more AI Engineers, Developers, Testers, and Architects. As I’ve said before, more AI Makers, not just AI Takers.

At QA, we already train people for these roles, and I’m not as worried as some about the supply of trainers or content. That part of the ecosystem is maturing.

What keeps me up at night is the looming AI Divide – a growing gap between those who understand and use AI, and those who don’t. If we want AI to benefit society as a whole, we need to think beyond the tech teams. We need to help everyone understand how to use AI safely, ethically, and effectively – from frontline workers to senior leaders.

The risk of rogue training

There’s another challenge brewing: the rise of rogue traders in the AI training market. As demand surges, mis-matching use of various AI related terminology that can cause confusion when seeking training.

As with all new technologies, there is an emerging lexicon – which extends to proficiency and skills, too - that is not always used consistently. It can lead to different understandings of the skilling that’s really needed.

“If we want AI to benefit society as a whole, we need to think beyond the tech teams”

For instance, misunderstanding the (sometimes overlooked, but fundamental) difference between a Generative AI course and Machine Learning, or Forecasting training – all types of ‘AI’ - could be a costly waste of time and learning budget with outcomes that simply don’t apply in-role or translate to business results. Businesses should be mindful of this and engage with a strategic training partner to ensure they are injecting the right skills, where they are actually needed.

This isn’t just a training issue, though. It’s also a hiring and professional credibility issue. Employers need to know what someone can actually do, and what a given project or role demands. Right now, there’s no universal framework for AI roles, like there is for data science (thanks to the Alliance for Data Science Professionals).

Until we have one, certifications from trusted providers may be the only reliable signal of competence.

The real risk is complacency

There’s a lot of reassurance going around right now. “Your job is safe.” “AI won’t replace you.”

Now, I understand the intent to avoid panic and resistance; and that’s prudent – rejection of AI is a very real risk in itself, that could put us at a huge disadvantage. However, I worry that just “don’t worry about it”, without caveat or call to action, is sending the wrong message.

Because the truth is, some jobs will change. Some will disappear. And many will evolve in ways we can’t yet predict. The people who survive and thrive will be those who’ve built the habit of continuous learning - in AI, and everything.

There needs to be an imperative attached to this reassurance. “Your job future is safe, as long as you keep learning.”

We need to start treating learning like we treat exercise or nutrition; something we do regularly and for our own long-term benefit, not just when we’re forced, or to tick a box. It’s the new baseline for career hygiene. Maybe we even need a national target: “Five hours of learning a week” or “10,000 learning steps a month.” Something to make it stick.

The £2 billion investment in AI is a good thing. And it’s bolstering to see the AI Action Plan backed up with funds to enact it.

But, it’s just the start. If we want that investment to pay off – for businesses, for public services, for society – we need to invest just as seriously in people. In their skills, their understanding, and their ability to adapt.