We are at a genuine crossroads. Not because of any single budget or policy decision, but because of a structural shift that no government can meaningfully halt.
US hyperscalers alone are expected to spend roughly $646 billion in capex this year. That is around 2% of US GDP and broadly equivalent to the entire GDP of countries such as Singapore, Sweden or Argentina. That level of capital deployment signals that this transition is structural, not cyclical. Governments can shape the edges, but they cannot stop the direction of travel.
That does not make me pessimistic. Quite the opposite.
History suggests we have been here before
Major technological shifts, from the democratisation of the desktop computer to the rise of the web, initially created friction and short-term displacement before unlocking significant productivity and GDP growth. There was often a lag of close to a decade before the full economic benefit materialised.
We are likely in the early stages of a similar productivity cycle now.
The key risk is not AI itself. The risk is how we respond. If we concentrate AI power and economic gains in too few hands, the outcome could be destabilising. If we combine innovation with broad-based access, skills development and responsible governance, the upside for productivity and living standards could be significant.
The UK economic picture is more nuanced than headlines suggest
A tight fiscal stance is unlikely to boost hiring confidence in the short term. But the underlying picture is more complex.
January saw the UK record a £30.4 billion budget surplus, the largest monthly surplus since records began in 1993, supported by stronger than expected tax receipts. Self-assessed income tax and capital gains tax receipts reached £46.4 billion, materially higher than the same month last year. Retail sales and private sector activity have also shown signs of improvement.
That tells us there is resilience in the system. The question is how that fiscal headroom is used.
With GDP growth of just 0.1% in the final quarter of 2025, annual growth of 1.3%, inflation still at 3% and unemployment edging up to 5.2%, the UK is operating in a cautious economic environment. Add to that higher employer National Insurance costs, and it is difficult to see the conditions for broad-based hiring acceleration.
We do not expect to see widespread hiring growth.
From headcount growth to capability growth
What we are seeing is a fundamental shift in how businesses think about workforce planning.
Boards are no longer asking how many people they should add. They are asking what capability they need to compete in an AI-enabled economy.
Any hiring expansion will be targeted. The main areas of growth will be technology and AI-led businesses racing to build capability and secure competitive advantage. Across the wider economy, hiring will be concentrated in areas that directly support productivity improvement: AI, data, cyber security and automation.
We are not seeing a dramatic overnight shift in roles, but there is a gradual move towards greater specialisation. Organisations are looking for individuals who can apply AI and automation in specific commercial contexts rather than broad, generalist digital profiles.
There is also rising demand for transformation leadership, both interim and permanent, to embed these capabilities into operating models at scale.
Within engineering teams, AI-assisted development tools are beginning to influence workforce planning. While demand for some traditional UX and UI roles has softened, there is growing interest in strengthening core engineering teams with developers leveraging AI tools to increase velocity and output.
In short, growth in hiring will be strategic and capability-led, not volume driven.
The real challenge is skills, not wages
I do not think the central challenge is wage inflation. It is skills inflation.
We are already seeing demand for AI-literate talent outpace supply. Employers are not simply bidding up salaries across the board. They are competing hard for a relatively small pool of individuals who can design, deploy or commercially exploit AI-enabled systems. That creates capability gaps rather than broad-based wage pressure.
Youth unemployment remains materially higher than the national average, with 16 to 24-year-old unemployment sitting in the mid-teens as a percentage. This is a major systemic issue. At the same time, businesses are struggling to find AI, data and automation capability.
Bridging that gap through modern, AI-focused apprenticeship and training routes is a clear economic opportunity.
The direction of travel on apprenticeship flexibility is encouraging. Giving businesses greater freedom to use their apprenticeship levy to upskill existing employees, as well as create alternative pathways for early career talent, is exactly the right lever to pull.
Where I would like to see more urgency is in scale and speed. AI adoption is not a five-year transition. It is happening now. The policy framework needs to move at the same pace as the technology.
What is missing from the policy agenda
If anything is missing, it is a more ambitious productivity agenda linked to capital investment.
Businesses have already shifted from headcount growth to output growth. Boards are asking how to deliver more value with the same or fewer people through automation, AI deployment and process redesign. That structural shift is happening irrespective of policy.
What would materially accelerate UK productivity is stronger and more targeted incentives for capital expenditure, particularly in digital infrastructure, AI systems and automation.
One of the very few clear economic advantages of the UK operating outside the European Union is greater flexibility over fiscal and regulatory decision making. That autonomy gives us the ability to move faster and more decisively in support of productivity and investment than many of our peers. From a business perspective, it can be frustrating if that flexibility is not fully utilised.
If we want to unlock sustained GDP expansion, we need to make investing in productivity-enhancing technology as attractive as possible. Without that, we risk talking about growth without fully enabling it.
The public sector cannot afford to wait
The public sector employs around 6.18 million people, roughly one in six UK workers. Public sector pay alone represents close to 10% of GDP, and broader government, education and health output accounts for somewhere between 12% and 19% of GDP. That scale means even marginal productivity gains have significant economic impact.
In that context, automation is not optional. It is necessary.
The real challenge is not pure AI talent volume. It is leadership, delivery capability and operating model redesign. The public sector needs the right senior sponsorship and execution expertise to modernise effectively. In many ways, this is about catching up with transformation that has already been underway in the private sector for several years.
A note on CEO responsibility
My broader reflection would be this: in a fast-moving and AI-accelerated environment, it is every CEO’s responsibility to learn, adapt and lead thoughtfully.
There is a real risk of knee-jerk decision making driven by fear of missing out on the latest AI tools that promise transformational results. In reality, meaningful productivity gains rarely come from technology alone. They require business process re-engineering, clear workforce planning and disciplined execution. That is one reason why, despite substantial investment, aggregate productivity gains from AI have so far been limited.
Careful planning matters. A clear data strategy matters. Understanding what genuinely moves the needle for your specific business matters far more than adopting tools because competitors are doing so.
This is easier said than done. The pace of innovation is extraordinary, and leaders must immerse themselves in the learning curve. But the goal should not be to chase every wave. It should be to apply AI responsibly, deliberately and in a way that enhances human capability rather than replaces it indiscriminately.
The balance we need to strike
It is not the government’s primary responsibility to protect specific roles or slow technological progress. Its responsibility is to create the right conditions for sustainable growth.
Protecting employment in the long term is a shared responsibility between the public and private sectors. Businesses must invest in their people, reskill their workforce and design operating models that generate opportunity. The public sector must modernise responsibly. The government’s role is to provide clear governance, sensible guardrails and competitive tax and policy incentives that enable both sectors to grow.
If we focus too heavily on protecting existing roles, we risk constraining productivity. If we focus solely on efficiency without supporting transition, we risk social friction.
The right balance is about enabling growth while accelerating skills development, not attempting to freeze the labour market in its current form.
If we can combine ambition with discipline, and maintain a human-first mindset rather than concentrating power and wealth in too few hands, the long-term opportunity is significant.