AI in Switzerland: Focus on Governance
The release of the Data & AI Observatory report in Switzerland is always an eye-opening event, as data often has the power to debunk some of our most deeply held assumptions.
This study, which focuses on the year 2026, compiles responses from more than 100 Swiss companies of all sizes and across all sectors, surveyed on their maturity, usage, and expectations regarding artificial intelligence. Conducted by Colombus Consulting, Oracle, and the Geneva School of Business Administration, it is particularly noteworthy because it has been tracking the same indicators for three years. The result: rather than a snapshot, it reveals a trajectory. This year, three themes particularly caught our attention.
Insight: Written by Delphine Seitiee, Secretary General of Alp ICT; Cédric Fischer, Partner at Agence Index; and Jean Meneveau, founder of Colombus Consulting Switzerland and an expert in digital transformation, data, and AI.
It's not a question of resources
Launching an AI pilot project is no longer a major challenge for the organizations surveyed. With some data and a generative model, it’s possible to produce a compelling use case in just a few weeks. But the challenge arises when it comes to moving from a prototype to widespread adoption. And that milestone can’t be bought.
This is the paradox highlighted in the 2026 edition: budget remains the most frequently cited barrier—57% of companies rank it among their top three obstacles—even though the level of investment alone does not predict the ability to deploy AI at scale. In other words, even when the tools are available, the ability to work with reliable data remains the main barrier to scaling up.
Establishing a data governance framework isn't something that can be decreed at the end of the quarter. It requires clear rules, clearly defined responsibilities, and ongoing oversight.
Lack of Governance: 3 Figures & 1 Paradox
Typically, major strategic directions are decided by senior management, and then implemented at all levels.
With AI, however, the opposite trend has been observed. Employees were the first to adopt generative assistants to free themselves from certain repetitive tasks, sometimes well before any official approval. This spontaneous adoption presents an opportunity, but it has its limitations.
Three figures illustrate this and reveal a paradox. 82% of companies acknowledge that change management is critical to the success of their AI projects. However, 46% limit their response to training and skill development, and only 11% have undertaken a concrete redefinition of roles and responsibilities.
And that is precisely where the challenge lies. An ambitious AI project does more than simply speed up a task: it transforms a process—and thus a profession or a way of working. Refusing to adapt roles means confining AI to a use that serves individual convenience and, by default, giving up on its collective potential.
Sovereignty is no longer just a slogan
For a long time, digital sovereignty was more a matter of rhetoric than of practice. That is no longer the case.
Today, 72% of companies incorporate ethical considerations into their AI-related decisions, and 62% actively monitor their data sovereignty or view it as a roadblock.
Few companies will abandon the dominant platforms overnight. These transitions are slow and are not decided on a whim. However, the issue of jurisdiction—under which laws is data stored, and to which legislation is it subject?—is now one of the criteria for making a choice. This is a relatively new topic that deserves close attention in the coming years.
What these three findings reveal
Data maturity, evolving roles, and data sovereignty are all issues of organizational governance. That is where the real gap is widening today.
It no longer distinguishes between companies that use AI and those that don’t, but rather between those that have transformed their organizations and those that have merely added a layer of technology. In fact, 10% of them are still content to simply add AI tools to processes that remain unchanged.
Technology is advancing rapidly. Organizations, on the other hand, move at the pace of the decisions they are willing to make.
Sources & References
- White Paper: Data and AI Observatory in Switzerland – 2026 Edition
