Enterprise CFOs just rewrote the AI investment playbook. KPMG's Global AI Pulse Survey reveals that 65% of UK enterprises now invest in AI regardless of whether they can prove traditional return on investment. At the same time, only 14% feel confident measuring the business value AI delivers to C-suite decision-making.
This isn't reckless spending. It's a fundamental shift in how finance teams value technology that replaces intellectual work that was never quantified in the first place.
The ROI Disconnect
KPMG surveyed global enterprise leaders and found three out of four will prioritize AI investment despite economic uncertainty. But the confidence gap tells the real story.
AI leaders vs. everyone else:
- 82% of AI leaders say AI delivers meaningful business value
- 62% of their peers report the same results
- Only 14% confident in measuring C-suite analytics value
The gap isn't just about AI maturity. It's a performance divide between organizations treating AI as enterprise-wide transformation versus those bolting AI onto existing models and seeing incremental gains.
Average annual AI spend hit $207 million in 2026—nearly double the prior year. Yet finance teams can't use traditional ROI frameworks to justify it.
Why Traditional ROI Frameworks Break
The challenge isn't that AI doesn't create value. It's that AI replaces tasks that were never measured to begin with.
What AI automates:
- Time reclaimed from manual research and analysis
- Decisions made faster with better context
- Gaps plugged before they become problems
- Insights extracted from unstructured data
Ben Grant, managing partner at Lambton Capital Partners, summarized it: "Traditional ROI wants clean input-output. AI doesn't do that yet in most businesses. The value shows up in time reclaimed, decisions made faster, and gaps being plugged before they become problems. Try putting that in a spreadsheet."
Gartner VP Analyst Nader Henein went further: "Some AI investments like AI assistants are becoming standard office tools, like the office suite. No one calculates ROI by counting the number of Word documents or presentations produced."
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When intellectual work becomes a commodity through AI automation, finance needs new measurement frameworks.
The New AI Investment Logic
Leanne Allen, KPMG's head of AI, called this shift a "milestone" in how business leaders view AI investment. "This shift in mindset by business leaders from viewing AI as something that must deliver an immediate return to one that sees AI as a long-term investment, recognizing it as a strategic enabler for enterprise-wide transformation, is an important milestone."
But she added a critical qualifier: "That shouldn't translate into investing in AI blindly, without a clear strategy."
What changed:
- Old logic: AI must prove immediate ROI to justify budget
- New logic: AI is a strategic enabler; falling behind costs more than experimenting forward
Manish Jain, principal research director at Info-Tech Research Group, explained the dual-mode operation: "Enterprises are simultaneously operating in two modes: exploratory, where learning velocity matters more than ROI, and industrialized, where value realization is expected, but maturity is still evolving."
Before focusing on ROI, organizations need to mature AI capabilities. When a new engine arrives, wise operators don't ask first what it earns. They ask what happens if they're the only ones without it.
What Finance Teams Should Measure Instead
If traditional ROI doesn't work, what should CFOs track?
Operational metrics:
- Productivity gains (hours saved, throughput increases)
- Cycle time reductions across key processes
- Error and defect rate improvements
- Time-to-market acceleration for new products
Client-facing metrics:
- Net Promoter Score changes
- Conversion rate lifts
- Customer satisfaction improvements
- Resolution time decreases
Deployment metrics:
- Percentage of workflows deployed or scaled
- Time from pilot to measurable value
- Adoption rates among employees
- Ratio of production use cases to pilots
Michael Leone, VP/principal analyst at Moor Insights & Strategy, noted that one in ten enterprises he's spoken to has the talent, governance, and operating discipline to get compounding returns from AI spend. "Everyone else is spending and hoping. That's the real story."
The blockers aren't budget anymore. They're security, privacy, and talent. Organizations have done the math on what falling behind costs, and they don't like the answer.
The Leaders vs. Followers Gap
KPMG's survey revealed a widening performance gap. This isn't simply an AI maturity gap—it's an execution gap.
What AI leaders do differently:
- Treat AI as enterprise-wide transformation (not departmental pilots)
- Build governance and operating discipline from day one
- Measure deployment velocity and adoption rates (not just ROI)
- Invest in talent, security, and privacy infrastructure
Organizations still in the experimentation phase can't capture the same business value as those that moved beyond pilots to fully scaling AI agents.
The 82% vs. 62% value realization gap reflects structural advantages in how leaders deploy, govern, and scale AI.
Decision Framework for CFOs and CIOs
For CFOs:
- Accept that traditional ROI frameworks won't work for AI (yet)
- Shift focus to deployment velocity and adoption metrics
- Quantify the cost of falling behind competitors
- Allocate budget for governance, security, and talent (not just tools)
- Demand clear strategy even without immediate ROI proof
For CIOs and CTOs:
- Build operating discipline and governance from day one
- Focus on moving from pilots to production at scale
- Track deployment metrics (adoption rates, time-to-value, production ratio)
- Invest in security, privacy, and compliance infrastructure
- Treat AI as enterprise-wide transformation (not IT project)
For business leaders:
- Recognize AI value shows up in time reclaimed and faster decisions
- Support exploratory mode (learning velocity) and industrialized mode (value realization)
- Prioritize talent and governance over tool proliferation
- Accept that measurement frameworks need to evolve with the technology
The Bottom Line
65% of UK enterprises now invest in AI regardless of traditional ROI, and three out of four global leaders prioritize AI investment despite economic uncertainty. Average annual spend hit $207 million—nearly double the prior year.
This isn't reckless spending. It's a calculated bet that falling behind costs more than experimenting forward.
The measurement challenge is real: only 14% feel confident quantifying the business value AI delivers to C-suite analytics and decision-making. Traditional ROI frameworks break when AI automates intellectual work that was never measured to begin with.
Finance teams need new frameworks focused on deployment velocity, adoption rates, and operational metrics (hours saved, cycle time reduction, error rates). The gap between AI leaders (82% see value) and followers (62% see value) reflects execution discipline, not just technology maturity.
CFOs should accept that AI ROI won't fit traditional spreadsheets. But they should demand clear strategy, governance, and talent investment. CIOs should focus on moving from pilots to production at scale, building operating discipline from day one.
The real question isn't whether AI delivers ROI. It's whether your organization can mature capabilities fast enough to capture value before competitors pull ahead.
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Sources
- KPMG Global AI Pulse Survey Report
- KPMG UK: AI No Longer Needs Traditional ROI
- CIO: KPMG Report Finds Enterprise Disconnect Between AI and ROI
- The Register: Suits Won't Quit AI Spending Without Proving ROI
- KPMG Q4 AI Pulse: AI at Scale
- KPMG Quarterly AI Pulse Survey (Asset Management)
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— Rajesh
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