In 2025, the UK government announced plans to invest £187 million into a national skills programme that will bring AI learning programmes into classrooms. This investment, alongside the government’s AI action plan represents a positive step forward, to address the widening AI skills gap.
Almost two-thirds of workers are using AI for work-related tasks, yet recent data shows that 73% of UK workers have received no formal AI training. These represent a clear imbalance between usage and skills; a gap which will ultimately stall the UK’s AI ambitions. Limited AI education and training, paired with high levels of experimental use, is creating a disconnect that hinders the effective integration of AI into workflows and business processes.
As it currently stands, only 1% of business leaders report their organisations as truly mature in AI deployment; underscoring the importance of the government’s AI action plan delivering tangible outcomes. Converting the government’s investment into worthwhile outcomes will require a dual focus: ensuring AI training is embedded into educational curriculums and ensuring businesses develop their current employees alongside hiring specialist talent. Together, these efforts will empower the UK to fully realise AI’s potential and improve ROI.
Embedding AI education to future proof the workforce
Studies show that students currently lack an understanding of how and when they should be using AI tools in educational settings. In fact, 51% of students want more clarity on exactly this, from teachers. The UK currently lacks the institutional structure for AI training and education in schools and universities, leaving a growing gap between usage, clarity and knowledge. Without structured guidance and education, students risk entering the workforce without the confidence or the literacy needed to use AI effectively and responsibly.
To address this, the government must embed ongoing AI education into school and university curriculums as a long-term national priority, rather than a one-off initiative. In classrooms, AI tools like ChatGPT should be actively integrated into learning, with students being taught how to use the tools critically and productively. Early exposure will build the competence and familiarity that future employers will expect; serving to narrow the skills gap and strengthen the talent pipeline. Crucially, it also creates an opportunity to identify and nurture specialist talent at an early stage.
Closing the AI skills gap from within
The UK is currently facing the biggest tech skills shortage in over 15 years, linked to a surge in demand for specialised AI talent and expertise. It has been found that only 38% of businesses believe their employees are ready to use AI, but at the same time over half of businesses are already using AI to drive daily decision making. These figures expose a significant internal capability gap that businesses must work to address through upskilling employees.
Specialist hiring for AI talent is important and serves a purpose for consultancy and the technical aspects of deployment. However, businesses must balance external hiring with internal upskilling or run the risk of creating internal knowledge siloes that prevent successful usage of the technology on a business wide scale.
To deliver meaningful and lasting value, upskilling initiatives must be tailored, accessible, and evolve along with an organisations usage of AI and the different tools and systems it may adopt. If done correctly, upskilling will ensure that AI is used to its full potential, across business operations, delivering a maximum ROI.
Laying the groundwork for successful AI adoption
Rushing into deployment is one of the reasons businesses struggle with successful AI integration, yet many businesses continue to invest large funds into deployments before fully assessing compatibility with existing processes and workflows. Rushing into deployments can result in poor integration, misuse, and underwhelming outcomes. Scaling AI projects without adequate groundwork is a key factor for why the majority of enterprise AI initiatives fail to deliver expected results.
This is why short pilot phases should be a priority for all businesses. Whether it be agentic systems or LLMs, when integrating AI into existing workflows and business processes, leaders must do so with care and precision. To ensurelong-term success, businesses must select the tools that genuinely support its specific processes rather than simply adopting whichever is the ‘latest and greatest’ tool. Short pilot phases allow organisations to test performance, resolve integration issues and provide targeted employee training before wider deployment.
1 in 4 workers are concerned that increased AI in the workplace will lead to job loss, making pilot phases even more crucial. These concerns stem from lack of knowledge and support, so pilot phases will work to provide the necessary support and involve employees through feedback and participation. Employee buy-in and confidence is crucial for large-scale, long-term successful adoption.
Ensuring the AI action plan creates lasting impact
The UK government’s AI Action Plan is a golden opportunity to position the country as a global leader in AI. Funding creates the right foundations, but it will be strategic adoption that will ultimately determine whether the UK can close its AI skills gap and achieve meaningful, large-scale adoption. By approaching AI education as a long-term national investment, the UK can build a workforce equipped to turn ambition into impact. This will allow for tangible returns on investment, and ensure the UK remains competitive in an increasingly crowded global AI landscape.
David Barber
David Barber is Director UCL Centre for Artificial Intelligence and Distinguished Scientist at UiPath.
