As AI starts to reshape the UK economy, the greatest risk isn’t that machines will take our jobs; it’s that people will be left behind without the skills to thrive in an AI-driven world.
While 90% of global tech leaders are investing in AI, rising compute costs and tightening budgets are forcing businesses to make difficult choices. In the UK, nearly one in fivebusinesses are actively reducing staff training budgets. This is short-sighted and a threat to long term competitiveness.
At a time when the UK Government is making a £2 billion commitment to positioning the country as an AI leader, we must remember that infrastructure alone won’t drive transformation. The most sophisticated tools mean little without people who know how to use them. To reap the most return from AI, skills and training must be hard-coded into the plan from the outset.
Skills shouldn’t be an afterthought
AI investments often begin with infrastructure such as models, platforms and compute. But too often, skills development is treated as optional or deferred until “later”. Later often never comes.
The result is that businesses automate tasks without empowering employees to adapt or grow. This kind of automation is a blunt instrument that reduces costs in the short term but stifles creativity, erodes morale and creates resistance to innovation.
Instead, we need to help people work with AI. That doesn’t mean turning everyone into a machine learning engineer. It means giving teams the confidence and capability to use AI to solve problems, make better decisions and focus on higher-value work. That shift is what delivers lasting ROI, not just from the technology but from the people behind it.
The workforce already has the raw talent
The good news is most organisations already have deep domain knowledge in-house. With the right support, existing teams can evolve their roles by using AI tools to automate the repetitive and elevate the creative. But this can’t happen in isolation.
Skills development needs to be embedded from the outset; in AI strategy, in change programmes and in daily workflows. It requires more than a single training module or centre of excellence. It calls for a culture where learning is continuous and AI is demystified.
This also means ensuring training isn’t limited to abstract or academic environments. People learn best when they see how AI works in the real world, where they can experiment, get feedback and solve the problems that matter to them.
Access and inclusion must be part of the plan
Globally, there’s growing momentum behind democratising access to AI education. High quality, hands-on training (especially when offered at no cost) helps level the playing field and build a more diverse pipeline of AI-literate talent.
Whether someone is a student, an early career professional or making a career change, access to enterprise-grade tools and learning content can help them develop practical skills in data engineering, analytics and AI development. Removing barriers to entry allows more people to gain real-world experience in applied problem solving that reflects the challenges businesses face every day.
Enterprises, too, should invest in domain-specific upskilling. Most of tomorrow’s AI-specific jobs won’t be brand new; they’ll be existing roles transformed by access to real-time intelligence and automation. This means training must be tailored, contextual and aligned to what teams actually do day-to-day.
Make AI tangible and trustworthy
Ultimately, confidence in AI grows when employees see it working in their world. Deploying tools into real workflows, securely and at scale, is essential. That means overcoming data silos, establishing clear governance and embedding AI agents into the systems people already use. The most inclusive innovations don’t require teams to start from scratch, but rather meet users where they are.
This approach reduces friction, builds trust and encourages cross-functional teams to collaborate around shared goals. When AI becomes part of how decisions are made across product, operations and customer service, it shifts from being a technical project to a business-wide asset.
AI leadership starts with people
If the UK and its businesses want to lead in the AI economy, they must make training the bedrock of innovation, not an afterthought. The future belongs to those who can harness data and AI to solve real problems, at every level of the workforce.
Investing in broad upskilling is a national priority, not just good for business. We need to act now to ensure the AI era is one of inclusion, opportunity and shared progress, rather than one in which potential is wasted for lack of access.
Let’s stop treating skills as optional, and start building the AI future from the ground up; one empowered individual at a time.
Michael Green
Michael Green is UK&I Managing Director at Databricks, leading growth across the company’s largest EMEA market. With over two decades in Data, AI, CRM and SaaS, he has a strong record of delivering value to enterprise clients and building lasting relationships. Beyond Databricks, he advises and invests in start-ups and social enterprises, championing technology as a driver for positive impact.
