UK business leaders are struggling to manage AI costs and turn investments into measurable returns, with 42% reporting only partial visibility into AI spending and 30% grappling with usage-based pricing models, according to KPMG's latest Global AI Pulse report. That limited understanding is undercutting confidence in AI strategy as enterprise adoption accelerates-26% of UK companies now use AI in daily work, up from 18% earlier this year.
Where cost blind spots hit hardest
Usage-based costs, such as token-based billing, pose a particular challenge. One-third of UK leaders cited a "limited understanding" of AI cost structures as a barrier to deploying AI agents. "AI is moving rapidly into everyday work, but scaling it responsibly brings a new set of challenges," said Dr Leanne Allen, head of AI at KPMG UK. "Leaders now need to show not just that AI can be deployed, but that it can be trusted, financially controlled and clearly linked to value. Cost visibility is central to that."
Without that visibility, companies risk budget overruns. Uber used its entire annual AI budget in four months after encouraging staff to use the technology, prompting a $1,500 monthly cap per employee and internal dashboards. Accenture similarly urged employees to stop using AI for low-value tasks to contain mounting costs.
Governance and CEO accountability make the difference
KPMG found that organizations where CEOs own AI decisions report higher confidence in their strategy and are more likely to see strong returns. "Clear accountability, practical governance, and workforce adoption must move together if businesses are to turn AI momentum into sustained value," Allen said. For executives seeking to build that foundation, an AI Learning Path for CEOs can help leaders understand how to govern AI initiatives without oversteering.
More than half (57%) of UK leaders now use AI cost monitoring dashboards, and 61% embed cost reviews into AI approval processes. Firms with stronger cost visibility are four times more likely to report established ROI-25% versus 6%.
The push toward financial discipline
"AI cost management cannot sit as an afterthought," Allen said. "If businesses want to scale AI responsibly, they need to build financial discipline into the way AI is approved, monitored and governed from the start. The organizations that can see their AI costs clearly are better placed to understand what is working, what is not and where to keep investing."
Analysts at Gartner recommend context engineering techniques to optimize AI spend and ensure tools are used for tasks where they deliver clear value, rather than indiscriminate experimentation.
Why this matters for executives and strategy
The data shows that visibility and accountability are not just compliance checkboxes-they directly correlate with ROI. For senior leaders, building a framework that ties AI spending to business outcomes is now a competitive necessity. The companies scaling AI most effectively are those where financial controls and executive ownership are designed in from day one. For deeper analysis on governance models and strategic AI cost management, see AI for Executives & Strategy.
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