The six-stage journey: Why 62% of organizations are stuck below the AI value line

In the latter half of 2026, the conversation surrounding AI has transitioned from implementation to return on investment (ROI). According to a survey of 1,006 C-level executives from 32 industries across 11 countries, while 90% of organizations report gaining some value from AI tools, only 45% derive a significant amount from it.

This gap, between "some" and "substantial" value, represents the current state of the AI economy. A study published in Harvard Business Review delved into the factors that differentiate organizations that generate real returns from those that merely get by. The study identified two major inhibitors: unready data (cited by 55% of executives) and the lack of a repeatable value framework (47%).

However, the factor that most strongly predicts high value is how organizations measure and report the worth of their AI initiatives. The researchers mapped this process into a six-stage Economic Maturity Model, ranging from unmeasured pilots (Stage 0) to formal reporting of AI value to boards, investors, and public markets (Stage 5).

The share of organizations achieving high value increases dramatically—from 4% at Stage 0 to 85% at Stage 5, a 20-fold difference. This model reveals a non-linear journey between stages, with two significant "cliffs" where the rate of improvement accelerates. The first cliff occurs between Stage 2 and Stage 3, representing a 24-point jump in high-value achievement.

This is where organizations transition from relying on pre-launch business cases to measuring outcomes post-deployment. The second, and larger, cliff occurs between Stage 4 and Stage 5, where a 27-point jump takes place as organizations begin to formally report AI value to external stakeholders. Notably, 41% of organizations get stuck at Stage 3, where they feel they have achieved significant value but fall short of the 58% who report high value at Stage 4 and the 85% at Stage 5.

The primary reason for this stagnation is that Stage 3 organizations struggle to synthesize their diverse AI-related metrics—such as those from finance, operations, risk, and customer teams—into a unified value statement that resonates with decision-makers. The involvement of the CFO in this process is crucial, as finance's ability to translate various types of value into a common unit and validate the number through certification significantly enhances organizational credibility.

This institutional credibility is essential for overcoming the second cliff and achieving widespread adoption of AI value reporting. Organizations that involve the CFO in AI value measurement and reporting see a notable increase in high-value achievement (76%) compared to when the CIO or CTO carries this responsibility alone (53%) or when functional executives alone do so (32%).

As organizations move from Stage 4 to Stage 5, three non-technical factors change simultaneously: increased CIO and CTO involvement in AI value reporting (from 20% to 39%), a reduction in the perceived gap between finance's understanding of AI value (from 40% to 18%), and the resulting boost in investment conviction. Just over half (52%) of Stage 5 organizations plan to substantially increase their AI investments, compared to just 32% at Stage 3.

This shift from private knowledge to public accountability is what unlocks the final 27 points of value realization. To assess where your organization stands, consider three key questions: Can we quantify our total AI value as a single number? Who owns this number—should it be an AI team or an executive accountable to the CEO, with finance at the table?

How can we integrate AI value into our board agenda as a recurring discussion point? If you cannot answer these questions, your organization likely falls into Stage 3 or below, mirroring the experience of 62% of global organizations. The path forward is not primarily a technological one but a managerial decision that can commence this quarter.