AI adoption is becoming a strategic necessity for CFOs
The hype around AI often drowns out the signal. But on Day 2 of London Tech Week, the message from the main stage was unusually clear: AI is already changing the way governments operate, public services are delivered, and decisions are made at scale.
And if CFOs don’t start engaging with AI as an operational and strategic lever — not just a technological one — they risk being left behind by faster, leaner, more adaptable peers.
In a keynote session moderated by The Guardian’s Dan Milmo, Matt Clifford CBE (Prime Minister’s Advisor on AI) and Jean Innes (CEO of the Alan Turing Institute) mapped the current state of play.
They weren’t speculating about AI’s potential. They were reporting live from the frontline.
“AI isn’t coming — it’s already embedded,” Clifford said. “We’re not waiting for breakthrough use cases. They’re happening inside HMRC, the NHS, and departments handling everything from asylum applications to air traffic control.”
It’s not just pilots and proofs of concept. Innes pointed to the NHS’s digital twin trials — 50,000 patients, real-time wearable data, and machine-learning models built to predict cardiovascular risk with far greater precision than any manual method.
At this scale, AI isn’t just saving time. It’s setting new baselines for accuracy and accountability.
For finance leaders, these developments signal a shift. AI investment isn’t an R&D experiment or back-office optimisation play anymore — it’s becoming part of core financial infrastructure. That includes how organisations model risk, allocate resources, and plan for regulatory change.
Yet scaling AI requires more than budget. It demands skills — and a strategy for how existing teams can work with AI, not against it.
Innes was candid about the practicalities: “We need to retrain and support people through this transition, not just at the grassroots level, but across the workforce.”
Clifford backed this with examples of AI being used not only to enhance complex decision-making — as in air traffic control simulations — but to train and upskill human staff with better, real-world data environments.
Finance functions aren’t exempt. Training budget owners, controllers, and risk managers to operate alongside AI systems won’t just improve productivity. It will become essential for auditability, assurance, and business continuity in an increasingly automated operating environment.
The environmental debate around AI wasn’t ignored. In fact, both speakers tackled it head-on.
Innes referenced modelling showing the AI sector could consume as much energy annually as Japan by 2030. But Clifford reframed the question: “The problem isn’t energy use. It’s the source of that energy.”
He pointed to the UK’s strategy of powering data centres and AI infrastructure with small modular reactors (SMRs), and the alignment between tech investors and government on clean energy adoption.
For CFOs, this raises the bar. Tracking AI’s cost-to-serve won’t be enough. Finance teams will need to understand the carbon footprint of their models, data storage, and computational intensity — and make informed decisions about the infrastructure behind them.
The session returned repeatedly to one underlying theme: productivity. Not just labour substitution, but augmentation — tools that allow teams to do more, faster, with better data and fewer mistakes.
“AI has huge potential for economic growth,” Clifford noted. “But we need to adopt it fast, or we’ll fall behind.”
This was perhaps the most pointed takeaway for CFOs. Over the past 50 years, the UK’s productivity growth has lagged behind peers — in part, Clifford argued, due to slower technology adoption.
That can’t continue. Especially not when the next wave of economic competitiveness will be driven by which countries — and companies — build, adopt, and export AI tools fastest.
Both panellists emphasised that innovation alone isn’t enough. Governance needs to be built into AI’s expansion — not bolted on.
Here, the UK may have an advantage. Clifford highlighted efforts across the public sector — from regulators to civil servants — to embed AI literacy and ethics from the top down.
The AI Safety Institute, launched with cross-party support, is one example of how the UK is trying to lead not just in capability, but in credibility.
“We don’t talk about electricity companies as ‘electricity-powered businesses’ anymore,” Clifford said. “Soon, we won’t talk about AI businesses. We’ll just expect every business to use AI — responsibly.”
That responsibility will increasingly fall on CFOs. To make the right calls on investment. To demand transparency from vendors. To build internal controls that can scale with the tech. And to ask harder questions about the balance between value and risk.
The clearest insight from this panel wasn’t about algorithms or training tokens. It was about intent.
For organisations that view AI through a narrow lens — as hype, risk, or optional digital upgrade — the coming years will be uncomfortable. For those that treat it as a foundational shift in how work gets done, value is created, and services are delivered, the opportunities are considerable.
Either way, as the panel made clear, this isn’t a theoretical future. It’s already budgeted, deployed, and transforming the way the UK economy operates.
The only question left for CFOs: where are you in that curve?