CFOs face challenges turning AI investments into business profits

New research has found that while CFOs around the world consider monetising artificial intelligence (AI) essential for future business success, a majority are struggling to achieve financial returns from their AI investments.

The study, conducted by DigitalRoute, surveyed 614 Chief Financial Officers across the UK, US, Germany, France, the Nordics, and the Benelux region to capture finance leaders' perspectives on the commercial opportunities and challenges associated with AI implementation.

According to the findings, 71% of global CFOs report difficulty in extracting financial value from AI, despite high levels of adoption across their organisations. The report refers to this as evidence that companies are facing obstacles in capitalising on what it calls "the second digital gold rush".

In contrast to the struggle to monetise AI, the survey revealed that nearly 90% of those questioned see AI monetisation as mission-critical for their company's success over the next five years.

The data shows that a significant gap remains between adoption and commercialisation: only 29% of firms surveyed have an effective working AI monetisation model, while the rest are either still experimenting or operating without clear strategies. The uncertainty surrounding commercial return is further reflected by the 68% of technology firms who believe their existing pricing models are no longer relevant in an AI-driven business landscape.

Board-level attention to AI has increased, with 64% of CFOs stating that AI monetisation is now a formal priority for their board, indicating the issue has moved from experimental projects to the core leadership agenda.

However, just 20% of companies have the capability to track AI consumption at the individual user or feature level. The report argues this lack of visibility leaves finance departments guessing at actual usage, billing, and profitability margins.

Discussing the findings, Ari Vanttinen, Chief Managing Officer at DigitalRoute, said: "AI in the second digital gold rush, but without the usage-level visibility, companies are gambling with pricing, profitability and even product viability. Our data shows CFOs urgently need real-time metering and revenue management to turn AI from a cost line into a genuine profit engine."

Systemic barriers to commercialising AI were also highlighted, with 70% of respondents listing pricing complexity as the top obstacle to scaling AI features. More than half (56%) reported friction between finance and product teams, an internal misalignment that the report says is hindering market readiness. Legacy infrastructure also remains a challenge, as 63% of surveyed organisations are actively investing in new revenue management systems; many current quote-to-cash tools are considered inadequate for the demands of usage-based AI pricing.

Regional differences in AI implementation and monetisation were identified. Nordic companies have made significant progress in technical AI deployment, but are finding profitability difficult to achieve, particularly due to hidden costs tied to generative-AI workloads. Meanwhile, the UK and France are described as already translating robust policy support into initial commercial returns, whereas US firms acknowledge AI's significant potential but face scaling challenges unique to their industries.

The report provides specific guidance for finance leaders aiming to capture value from AI. Recommendations include metering AI consumption at the feature level, combining value-based and usage-based pricing approaches prior to product launches, and integrating product, finance, and revenue operations teams with a unified revenue data layer.

Vanttinen added: "Every prompt is now a revenue event. When businesses can see, price and bill for AI usage in real-time, they unlock the margins the market expects."