Building the UK’s AI advantage: why upskilling can’t be an afterthought (www.techradar.com)

As AI adoption accelerates in the UK, the biggest economic risk isn’t machines replacing people but people being left behind without the right skills. Despite 90% of global IT leaders investing in AI and the UK government committing £2 billion to AI infrastructure, nearly one in five UK companies are cutting training budgets—threatening long-term competitiveness. The piece argues that skills development must be baked into AI strategy from day one: infrastructure alone won’t deliver value. When upskilling is postponed, automation can reduce short-term costs while stifling innovation, lowering morale and creating resistance to change. For the AI/ML community this means shifting focus from purely technical buildouts to workforce enablement and practical deployment. Companies should leverage existing domain experts, provide hands-on training in data engineering, analytics and model-driven workflows, and democratize access to enterprise-grade tools so learners can experiment and solve real problems. Technical implications include breaking data silos, instituting transparent governance, and embedding AI agents into existing platforms to scale safely and build trust. Tailored, contextual learning—rather than one-off centers of excellence—will convert AI from a technical project into a business-wide asset, maximize ROI, and broaden the talent pipeline for an inclusive, resilient AI economy.