- Bosses are seemingly confused that mass AI in favor of human workers isn’t always a success
- AI operating costs are often higher than expected
- However some firms are happy to adapt and refocus where needed
Bosses are being left confused at the high cost of moving to AI-centric models, with many seemingly baffled that replacing human workers with agents isn’t instantly saving them huge amounts of money, new research has claimed.
A new KPMG report found nearly a third of business leaders reported some difficulties with getting to grips with AI operating costs in their organizations.
The news comes as several major AI providers, including the likes of Anthropic and OpenAI, have moved some services toward usage-based billing, rather than flat-rate subscriptions, in recent months.
Making AI effective
The report saw KPMG survey 2,145 senior leaders across 20 countries, finding 29% were struggling to understand the rise in operating costs as they looked to scale AI across their business, with a similar proportion also highlighting a limited understanding of AI costs and economics as a major challenge to deploying AI agents.
“As usage-based pricing models become more common, many organizations are still building the capabilities required to forecast, monitor, and manage AI spending effectively,” KPMG said.
When things do go wrong, the report highlighted how leaders were often unclear who should take responsibility, particularly in the case of hallucinations or errors by AI models.
It noted that why having human leadership be accountable is important, “governance ultimately succeeds or fails through day-to-day operating practices.”
“Organizations need clear rules for when employees can intervene, who owns AI-related costs, how AI outputs are reviewed and what happens when systems fail. While most organizations report having at least some governance mechanisms in place, relatively few describe these practices as fully embedded,” the report said.
When costs have outweighed the expected value, the report found a surprising amount of contrition from its participants, with nearly half of organizations saying they had rephased AI deployments in that case.
“These actions do not signal reduced confidence in AI,” the report warned. “Rather, they suggest a growing willingness to evaluate where AI creates meaningful value and where it does not. Organizations appear increasingly focused on concentrating investment where expected returns are strongest.”
“We’re seeing a clear divide between organizations with leadership accountability at the top and those without,” added Steve Chase, KPMG Global Head of AI and Digital Innovation, KPMG International.
“These companies are seeing materially better results across the board such as greater confidence, higher value realization and established ROI.”
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