AuthorNovember 4, 2026Categories
- AI in Accounting
- Business
- Technology
Just 3% of FTSE 100 companies disclose a specific financial return or outcome from artificial intelligence (AI), despite more than a third reporting substantive deployment of the technology, according to new research from technology intelligence company Flexera.
The analysis, published on 4 November 2026, examined the 2025 annual reports of FTSE 100 companies and found that while 36% reported meaningful AI deployment, only 32% connected its use to identifiable business outcomes.
Financial transparency was considerably more limited. Just 2% disclosed a specific AI expenditure figure, while none identified AI investment as a separate budget or cost.
The findings expose a growing challenge for corporate finance teams as AI becomes embedded in business operations: demonstrating whether investment in the technology is delivering measurable financial value.
AI adoption outpaces financial accountability
As businesses expand AI capabilities across operations, customer services and internal processes, measuring their financial contribution is becoming increasingly important.
Flexera’s analysis suggests that while companies are becoming more comfortable describing how AI supports their operations, relatively few are translating those benefits into financial disclosures that shareholders can evaluate.
Marlon Oliver, Senior Vice President, EMEA, at Flexera, warned that rising AI expenditure and the emergence of autonomous agents could further complicate financial oversight.
“Companies are burning through annual AI budgets in months, and always-on agents will put those budgets under even more pressure. Having visibility of that spend and controlling it is essential, but it is only the starting point,” he said.
Oliver argued that measuring technology consumption alone is insufficient to demonstrate commercial success.
“Token consumption, compute, and license numbers tell you what AI costs and how much it is being used. They do not tell you whether it is creating value.”
For accountants and finance leaders, this distinction is significant. While businesses may report improvements in productivity or operational efficiency, these benefits do not automatically translate into identifiable cost savings, increased profitability or stronger cash flow.
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The findings do not necessarily indicate that companies are failing to measure AI returns internally. Rather, they highlight the limited financial information currently available in public reporting.
AI risks receive greater attention than financial returns
The research also found that 54% of FTSE 100 companies identify AI as a material or company-specific risk in their annual reports.
This suggests that corporate reporting is placing greater emphasis on the potential risks associated with AI than on quantifying its financial contribution.
The findings come as the Financial Reporting Council (FRC) places increasing attention on AI governance and corporate reporting standards.
In its Annual Review of Corporate Reporting 2025/26, the regulator emphasised the importance of effective oversight and control when AI is used in financial reporting processes.
Separate FRC research published in July 2026 found that AI adoption in corporate reporting was increasing, although implementation remained cautious and concentrated in lower-risk activities.
Together, the findings highlight the challenge facing finance functions as businesses expand their use of AI while maintaining accountability over spending, performance and reporting.
The growing complexity of AI expenditure
Unlike traditional technology investments, AI expenditure can be distributed across software licences, cloud infrastructure, computing resources, data platforms and consumption-based services.
This fragmentation can make it difficult for finance departments to establish the full cost of AI initiatives, particularly when spending is spread across multiple business units.
Steve Daheb, Head of AI GTM Strategy at Flexera, warned that autonomous AI agents could further complicate expenditure management as they initiate workflows and consume additional computing resources.
“Agents make those economics more complex because they can initiate their own workflows and consumption. A single instruction can set off repeated attempts to complete the work, each drawing on more computing power and adding to the bill.”
This creates additional challenges for budgeting, cost allocation and financial forecasting, especially where AI usage fluctuates significantly between departments or individual employees.
Daheb argued that businesses must connect technology consumption and expenditure with the outcomes AI produces, rather than treating implementation itself as evidence of success.
What this means for accountants and finance leaders
For the accountancy profession, the findings reinforce the importance of financial oversight as AI investment becomes a more substantial component of corporate technology strategies.
Finance teams have an opportunity to establish clearer frameworks for evaluating AI expenditure, including tracking the total cost of implementation, identifying measurable operational improvements and assessing the financial returns generated over time.
This could involve closer collaboration between finance, technology and operational teams to establish consistent performance indicators and distinguish between productivity gains, cost reductions and revenue improvements.
For auditors and reporting professionals, the findings also raise questions about the evidence supporting corporate claims of AI-driven efficiency, particularly where these claims influence financial forecasts or management assumptions.
Oliver suggested that companies should connect AI investments directly to business performance indicators, including operational efficiency, service delivery and revenue generation.
“When shareholders are told AI is improving productivity, they should be able to see what that improvement is worth, what it cost and whether the economics are improving.”
As AI becomes more deeply integrated into business operations, the pressure to demonstrate its financial contribution is likely to increase.
For finance leaders, the next stage of AI adoption may be defined less by how extensively the technology is deployed and more by whether its value can be reliably measured, scrutinised and communicated to investors.
Sources
- Flexera, FTSE 100 AI financial disclosure analysis, press release, 4 November 2026.
- Financial Reporting Council, Annual Review of Corporate Reporting 2025/26.
- Financial Reporting Council, Corporate reporting remains human-led amid growing adoption of artificial intelligence, July 2026.
- AI in Accounting
- business
- technology
