During our presentation at the CxO Industry 2026, we asked the audience, “Can you prove the ROI of your organization’s AI projects with actual numbers?” The responses were as follows:
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“Not yet” — 52%
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“In some cases” — 48%
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“Yes, with numbers” — 0%
Where would you place yourself on this scale?
Companies have AI initiatives, but tracking the value they create often gets left out. The lack of tracking and metrics is reflected in the number of AI initiatives that get cancelled. In 2024, 17% of companies abandoned most of their AI projects, and in 2025 the figure doubled, with 42% of companies failing to complete the projects they had started (S&P Global Marketing Intelligence 2025). The rising cancellation rate indicates that technical functionality is not enough when a project’s business value cannot be shown.
Five years ago, when AI projects were launched, the bottlenecks were technology, data, and algorithms. Now none of these are significant obstacles. Technology and models are available as services, and access to data is easier than ever. The market has entered a new phase, where the winners are those who manage to scale repeatable value from AI and turn experiments into a lasting business capability. Only about 5% of companies currently create significant value from AI at scale (BCG). These companies achieve revenue growth benefits up to five times higher and cost savings three times greater than others. At the same time, 60% of companies still report only minor benefits from their investments. BCG calls this the “AI Value Gap”, where the companies creating real value from AI keep widening their lead.
AI initiatives that fail to demonstrate clear business benefits will face tougher scrutiny in the coming years (Gartner). By 2027, AI investments will increasingly fall under the same financial review as any other strategic investment a company makes.
AI investments are now expected to demonstrate value
Boards and leadeship teams are asking what business benefit AI delivers for the company. This is also reflected on CFOs’ agendas, as measuring the ROI of AI is now a priority for more than a third of CFOs (Gartner). Like any other investment, the CFO expects AI initiatives to come with transparent costs, measurable value and systematic monitoring.
Every AI initiative should have a business problem, an expected value, a way to measure it, an annual value in euros, and a validation method. These metrics let you demonstrate the value of AI initiatives and implementation to the CFO.
As AI and agents move toward the organization’s core processes, their impact on the entire business grows. The value of AI is measured by its impact on the costs, quality, and results of the entire business process, not by the efficiency of a single solution.
Proven ROI comes from an AI portfolio that is built and managed systematically. So how do you build a portfolio like this in practice? We’ve put together a guide on building an AI portfolio, verifying business value and scaling successful solutions into the business.
The Chief AI Officer's most important tasks in 2027
The core role of the Chief AI Officer is to ensure that the overall AI initiative is managed with a long-term perspective, that successful solutions are scaled, and that ownership is genuinely transferred to the business.
Manage AI as a portfolio with clear expectations for value creation.
The success of a single project within an AI program does not yet prove the value of the entire program. Identify which projects are working and delivering value, as well as those that are not, and manage this as a whole. When AI projects have clear budgets and expected value delivery, you can justify future investments.
Manage the AI program with a long-term perspective.
Once you have identified what works, commit to those solutions and develop them with determination. Let maturity build step by step, and do not expect early experiments to deliver the results of later stages. Discipline and commitment are what carry a programme through.
Ensure business ownership.
Initially, AI Center of Excellence (AI CoE) owns the AI initiatives. The AI CoE is an internal support function that makes sure AI is used for use cases that create value for the company. As AI moves deeper into core processes, ownership shifts to the business. Define and reinforce ownership.
Competitive advantage comes from proving value
The biggest risk in 2027 is falling behind competitors who succeed in transforming AI experiments into a permanent business capability. The competitive advantage brought by AI stems from the ability to identify value-generating use cases, measure their impact in numbers, and scale successes into the business.
This is precisely why the role of the Chief AI Officer is shifting from technology enabler to leader of business value. When that shift succeeds, next year you can answer the question “Can you prove the ROI of your organization’s AI projects with actual numbers” with: “Yes, with numbers.”
Could we help your company with AI solutions? Send us a message or contact us through our website and let’s continue the conversation!
