Most firms fail to measure real financial returns on AI

Only 15% of organisations quantify the financial impact of their data and AI work in pounds or dollars, according to a new report from data and AI consultancy Cynozure.

The research highlights a gap between rising AI adoption and leadership teams' ability to demonstrate commercial returns. It also points to uneven accountability for AI strategy, with ownership often split across multiple executives or not formally assigned.

The findings come from Cynozure's 2026 State of the Industry Report, The Next Horizon: Data, AI and Impact, based on responses from 60 senior data and AI leaders across sectors including retail, financial services, consumer goods, technology and non-profits. Nearly half of respondents reported revenue above £1 billion.

Measurement gap

As boards and executive teams increase scrutiny of AI spending, many organisations still struggle to measure outcomes consistently. The report found that 30% do not measure the value of data and AI consistently, and only 15% quantify financial impact in monetary terms.

This measurement weakness sits alongside widespread activity in both traditional and generative AI, which the report describes as mainstream among respondents. Interest in agentic AI is also growing, with 52% of leaders using it or planning to do so.

Despite expanding adoption, impact is still concentrated in operational improvements. Organisations most commonly focus on automating routine tasks and improving productivity, rather than using AI to drive growth initiatives.

Jason Foster, Cynozure's founder and CEO, said the next phase of AI adoption is a commercial test rather than a technical one.

“AI has propelled data into the boardroom. The challenge now is not whether organisations can use data and AI, but whether it is making a meaningful difference to the P&L. Many teams have invested heavily in platforms, teams and experimentation, but still struggle to evidence impact. The organisations that pull ahead in 2026 will be those that treat data and AI as a portfolio of products, tied to outcomes and measured with strong investment and commercial discipline.”

Who owns AI

The report also points to fragmented ownership of AI strategy. While 80% of organisations assign data strategy ownership to a Chief Data Officer or Head of Data, only 28% assign AI ownership to the same role.

AI governance is often dispersed: 40% of organisations split ownership across multiple executives, and a further 17% report having no clear AI owner. Cynozure argues this slows alignment and delivery.

These findings come as organisations reorganise leadership responsibilities around AI. Some have expanded Chief Data Officer remits to include AI, while others have created new roles spanning technology, operations, risk and product. The report suggests this transition remains incomplete, even where AI tools are in active use.

Priorities and blockers

Data culture and literacy emerged as the top priority for 2026, cited by 43% of leaders. The report links this to a view that investments in analytics and AI fail to deliver results when employees do not understand or trust data.

Budget and resource constraints were the biggest blocker overall, cited by 25% of respondents, and were particularly acute for smaller organisations.

Larger organisations reported different barriers. Legacy technology was cited by 20% of leaders, while 17% pointed to a lack of executive or organisational buy-in.

Data products

The report emphasises data products as a practical way to operationalise data and AI work, describing them as increasingly central to translating technical work into sustained organisational performance.

More than 70% of leaders expect data products to drive the most value in operational excellence and autonomy. Respondents also ranked customer experience and growth, and financial performance, as major value areas.

Tim Connold, Cynozure's chief client officer, linked data products to decision-making and board-level reporting on returns.

“Data products, and increasingly decision products, are how leaders are turning strategy into reality. By framing data and AI as products that support specific decisions, organisations can focus investment on what matters most and track Return on Data Investment (RODI) in a way that resonates with boards and investors.”

The survey was conducted between late October and late November 2025. Respondents included Chief Data Officers, Chief Data and Analytics Officers, Chief Data and AI Officers, VPs and directors of data, heads of data and other senior executives.

The report suggests leadership expectations are shifting as organisations move from experimentation to proof of impact, with measurement discipline and clear ownership expected to play a bigger role in how AI programmes are funded and governed through 2026.