As we start 2026, the UK’s AI standing makes for impressive reading. The country remains the third-largest hub globally for AI venture capital investment (after the US and China) and is significantly ahead of most of Europe combined. Its computer science education also ranks third in the world, while in September major US tech firms pledged billions of pounds worth of AI investment into the UK.

All this, and there is still no general statutory AI regulation in the UK. So, does it need it?

The US and China both adopt a light-touch, innovation-first stance. The US has a mindset of big, forward-thinking ambition, particularly around sovereignty and scale, that is propelling its AI development forward. China, meanwhile, is racing ahead with state-supported AI deployment across every sector imaginable. These are the AI leaders out front.

The EU’s AI Act, on the other hand, was the world’s first comprehensive AI law. It has the well-intentioned goal of protecting its citizens. But it has also grappled with the tricky balance of ensuring compliance requirements and regulations don’t stall innovation. Due to this, it is now in the process of simplifying the Act for companies with its recent omnibus proposals – these will see it transition from a more cautionary to innovation-friendly stance.

Given the UK’s AI standing, you might think why should it change anything? But while the UK is a leading hub of AI talent, research and investment, our talent is also moving abroad. Crucially, our infrastructure needs major investment to match our bold AI ambitions. And other countries are quickly catching up in the AI race.

UK needs its own AI regulation

So, the UK definitely needs greater clarity of strategy and vision within the AI landscape like the other major players. It has a strong opportunity to forge its own path and draw on its historical strengths. We have access to world-class funding and exceptional talent; the real challenge lies in cultivating greater scale, ambition and execution speed.

Therefore, as regulatory uncertainty remains, UK companies have a great chance to show what effective AI implementation can look like. The major task that faces them in 2026 is achieving tangible value from AI tools, as AI moves from boardroom fantasy to the messy reality of enterprise implementation. After two years of frenzied AI adoption, next year will be the year enterprises hit the wall. Not because AI doesn’t work (it does!) but because organisations are finally confronting the uncomfortable truth: there are no shortcuts.

This trough of disillusionment isn’t a reason for pessimism, it’s a sign of maturity. It means we’re moving past the easier part (demos and pilots) to the harder part (actual transformation). The companies and countries that embrace this reality, invest in the unglamorous infrastructure, and do the difficult work of genuine change will emerge stronger on the other side. With the right mindset, it’s a golden opportunity to forge ahead with enterprise AI implementation.

There’s also a wider picture to be aware of. While enterprise AI grapples with its growing pains, consumer AI is about to have its breakthrough moment. Google’s deep integration of Gemini across Android will finally deliver what we’ve been promised for years: an AI assistant that’s proactive, contextual and genuinely useful. It won’t just answer queries when asked, but anticipate needs, connect information across apps, and become a true daily companion.

Consumer AI must lead regulatory policy

The smartphone is therefore about to become the primary interface through which billions of people experience AI. And that’s going to change everything about how we think about human-computer interaction.

When people experience truly useful AI in their daily lives – AI that saves them time, reduces friction, and adds genuine value – their expectations for enterprise AI will skyrocket. The “that’s just how the system works” excuses that IT departments have relied on for decades won’t fly anymore.

Consumer AI will create pressure that flows back into every workplace. If enterprises don’t adopt AI, then they risk “shadow AI” (where employees use AI anyway without organisational oversight), in the same way there was “shadow IT” for working around systems. This is dangerous and one to be avoided.

So, yes, UK regulation needs to match this speed of innovation for enterprise AI, so that organisations are able to match their employees’ expectations. But most importantly, companies need to confront the hard truths of organisational change. There’s no silver bullet. The hard work on AI implementation starts now. If they can do this, they can drive the UK’s AI strategy and pave the way for other companies to follow.