By Tram Anh Nguyen, Co-founder, CFTE, and Chairwoman, Global Women in AI
The UK’s AI objectives are changing. It is no longer only a question of ambition, innovation or adoption. It is now a question of implementation.
We are entering the age of agentic AI: systems that do not only assist, but act. They can plan, reason across steps, coordinate with other agents and operate inside the tools organisations already use. Generative AI changed how people create and analyse information. Agentic AI will change how work is organised, how decisions are made and how institutions deliver value.
For the UK, this creates a strategic opening. The country has world-class research, a strong technology ecosystem, sophisticated regulators, deep sector expertise and a government that has placed AI at the centre of national growth. But if we want AI to translate into productivity, trust and inclusive prosperity, the next phase cannot be only about tools, models or infrastructure. It must also be about people.
The UK does not only need AI adoption. It needs AI fluency.
Adoption means access to tools. Fluency means the capability to understand what AI can do, where its limits are, when to trust it, when to challenge it and how to apply it responsibly in context. It is the difference between using AI as a faster task-doer and knowing how to redesign work around intelligent systems.
This distinction matters because agentic AI is not just another software upgrade. When a system can act, leaders must ask new questions. What should be automated? Who authorises an action? Who is accountable for the outcome? How do we audit decisions made or supported by autonomous systems? When should humans intervene? What happens when an agent acts across multiple systems, suppliers or jurisdictions?
These are not purely technical questions. They are questions of operating model, governance, skills and trust.
The opportunity is already visible. In financial services, Lloyds Banking Group has announced an AI-powered financial assistant for millions of customers. In education, the UK government is supporting the development of AI tutoring tools that could help disadvantaged pupils. In public services, police forces are experimenting with digital agents to respond to non-emergency citizen queries and free human teams to focus on higher-value work.
The next frontier is agentic commerce, where agents search, compare, negotiate and buy on behalf of individuals and businesses. For companies, the question will shift from “How do we reach the customer?” to “How do we become discoverable, trusted and chosen by the agent acting for the customer?”
This is the scale of the change ahead. Agentic AI will begin to decouple cognitive work from headcount. Organisations will be able to increase output without increasing people in the same way. Some professionals will be outcompeted by systems that are faster, cheaper and always available. Others will be supercharged, using AI with their judgement, domain expertise and contextual understanding to reach a new level of performance.
The dividing line will not be the technology. It will be capability.
From our work with financial institutions, regulators and governments internationally, we see the same pattern repeatedly. Organisations rarely struggle because they lack access to AI tools. They struggle because their people do not yet have the fluency to redesign workflows, govern risks and create value responsibly.
This is why AI fluency must become a national priority.
If fluency remains concentrated among a small group of technical experts or already advantaged firms, AI will widen the gap between those who can benefit and those who are displaced. But if fluency is built deliberately across sectors, regions and communities, it can become a foundation for broader participation in the AI economy.
For the UK, this requires a human-capital infrastructure for AI.
First, the UK needs a shared understanding of AI fluency. Not everyone needs to become an engineer. But citizens, frontline workers, managers, executives, regulators and board members all need the ability to use, question and govern AI at the right level for their role. A common fluency framework would help organisations move beyond generic awareness and define the capabilities people actually need.
Second, fluency must be built around sectors and roles. AI in banking is not the same as AI in healthcare, education, legal services, manufacturing or public administration. The workflows, risks, accountability structures and professional norms are different. The future belongs to AI-bilingual professionals: bankers, clinicians, civil servants, teachers, regulators and entrepreneurs who understand both their field and how AI transforms it.
Third, capability must be embedded into responsible deployment. Organisations should not be assessed only on whether they use AI, but on whether they have the skills, governance, auditability and oversight to use it well. Procurement, regulation and institutional strategy should reward responsible implementation, not just technological novelty.
Fourth, inclusion must be designed into the system from the start. Women, underrepresented communities, workers outside major technology hubs, SMEs and professionals in roles most exposed to automation must not be treated as an afterthought. AI fluency cannot be a privilege for the few. It must become a capability distributed across the economy.
This is the human-capital layer of AI leadership that has been missing from too many AI strategies. At CFTE, our work has shown that responsible AI adoption is not a one-off training exercise. It is institutional readiness built as a system: defined through proficiency frameworks, delivered through role-based pathways tied to real workflows and measured through capability diagnostics.
Technology will continue to advance. Models will become more powerful, cheaper and more autonomous. But the countries that lead will not simply be those that move fastest. They will be those that build the deepest capacity to adapt, govern and create value responsibly.
For the UK, the real opportunity is not only to be a global AI innovator. It is to become a global model for responsible AI implementation.
That means recognising capability as infrastructure. It means treating AI fluency as seriously as compute, data and regulation. And it means ensuring that the people who power the economy are not passive recipients of technological change, but active shapers of it.
The future of agentic AI will not be determined by technology alone. It will be determined by people. The choice for the UK is whether we shape this shift, or are shaped by it.
