If organizations want to succeed with AI, the most important investment is not only new technological solutions – but perhaps to an even greater extent capability development and knowledge about how data is used in organizational and strategic development.
That is the conclusion I draw when reviewing this year’s preliminary responses in the DI2X Tool – Organizational Capabilities (completed from January 1 onward).
The ambition is strong. Organizations want to be digital. They want to be close to the end customer. They want to transform.
But when asked about their broader ability to understand and work with data, the assessment drops significantly.
This is not alarming in itself. But it is – in my view – strategically significant, especially at a time when AI is gaining momentum and regulation, governance, and responsible use are being intensely debated.
When we aggregate this year’s data across organizations, a clear pattern emerges.
Capabilities related to strategy and leadership are rated highly. End‑Customer Focus scores 4.4 on a scale from 1 to 7. Transformational Leadership scores 4.2, and Digital Visionary 4.1.
In other words, the strategic intent is strong. The direction is set.
But when we look at the capability Data‑Driven, the picture changes. The overall score is 3.4 – placing it among the lowest‑rated capabilities in the assessment.
In the DI2X framework, Data‑Driven refers to the organization’s ability to understand the value of data and to lead, govern, use, and present data as both an organizational and strategic resource. Organizationally, as support for decision‑making and insight – and strategically, as the ability to use data to develop new services and business opportunities.
The capability consists of three sub‑capabilities:
This year’s benchmark shows the following averages:
The most striking finding is that Data Literacy, at 2.9, is the lowest‑rated sub‑capability among all 48 in the framework.
This tells me something important.
Many organizations are working to establish decision structures and policies around data use. But broad familiarity with data – and the ability to translate data into new solutions – is rated significantly lower and appears to be lagging.
A cautious conclusion could be this: Be careful that structures and policies do not become ends in themselves, while opportunities to use data – and AI – for decision support, new services, and new business opportunities are missed.
At the same time, executive teams and boards are asking questions such as:
What should our AI strategy look like?
Who should own it?
How fast should we scale?
What if we do not act now?
These are understandable questions. But they primarily concern technology and speed.
The question is also: Does the organization actually have the necessary capabilities to create real value with AI?
Our data suggests that this may not fully be the case.
When organizations rate their strategic direction and transformation power highly – but their broader data understanding low – a tension emerges. The ambition to be digital is strong. But working data‑driven is not yet fully integrated into daily practice.
AI does not primarily expose technological gaps – but organizational ones.
AI amplifies the foundation it encounters.
If data understanding is broad and integrated, AI can accelerate innovation and decision power.
If it is narrow, AI easily becomes an isolated project – without lasting impact on the organization and the business.
In my view, one of the next – and important – steps, if we are to unlock the full value of data and AI, is to make data something we share – not something we leave to specialists.
Imagine an organization where data is not only used for reporting, but for reflection and learning – and where AI is applied to identify new patterns, make more precise forecasts, or develop entirely new services.
Where data analyses are actively requested and discussed in leadership teams.
Where employees across functions are familiar with the data they can use to improve decision‑making, automate processes, or discover entirely new correlations.
At DI2X, we refer to this as the digital mindset: curiosity, critical thinking, and courage.
In a time when AI is accelerating, real competitive strength may prove to be a matter of mindset and the ability to be data‑driven – rather than yet another new technological solution.
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