AI Stalls in Plans
According to the CBS, only 22.7% of Dutch companies with ten or more employees used AI technology in 2024. Small organizations (10–19 employees) remain stuck at 17.8%, while large companies with 500+ employees score nearly 60%.
These figures illustrate what we see in practice: many organizations are stuck in plans and waiting. The idea that a blueprint must first be in place slows down progress. Meanwhile, valuable knowledge remains untapped. The spark is there, the engine too, only the road in between is missing.
However, there are also many success stories. In healthcare, the IZA legislation has given a boost to innovation. For example, a chatbot has been developed that collects activities in the area in one place, making them more accessible for residents of municipalities. Another solution in development is software that automatically compares new national guidelines and makes suggestions for adjustments in protocols. This directly leads to more hands at the bedside in hospitals, as specialists spend much less time updating protocols.
'The spark is there, the engine too, only the road in between is missing'
In financial services, AI supports experts in recognizing risks when granting business loans. This clarifies the rules based on which decisions are made, allowing experts to focus on the most complex cases. A similar technology is applied in retail for 'product category management', where AI categorizes products instead of an employee.
These examples arise from challenges on the work floor and deliver tangible results. They do not come from a strategy document. It is important that you, as a middle manager, seize these initiatives with both hands. Start small, measure quickly, share widely. This increases trust and shows that innovation is not just about 'data' or 'IT', but about everyone.
Evidence over Permission
We believe that innovation rarely arises top-down. The key lies with the people in the middle. That’s where the millennials work with AI daily, who are used to trial & error and who build bridges between teams.
This image is confirmed by research from Google Workspace: 82% of young leaders use AI tools weekly, often without explicit instructions from above. They do it because it works, not because someone asks them to.
Exactly that attitude, experimenting and providing tangible evidence, is what organizations need now. No endless pitch decks, but small steps that yield results. Results create support. And support opens the way to scale.
'Focus on results, not on hype'
Our Lessons from Practice
We see that this whispering leadership works. It does require courage and nuance. A few lessons that keep coming back:
- Position innovation as evolution, not as revolution. This way, you take colleagues along without resistance.
- Focus on results, not on hype. No one gets excited about a tool for the sake of a tool. They do about a process that suddenly takes half the time.
- Involve senior leaders early as sponsors. Not to ask for permission, but to show what already works.
- Build trust informally. Choose the right moment to share successes carefully.
- Use AI to accelerate, not to replace people. This alleviates fear and opens the way to collaboration.
Safe Experimentation, That You Can Learn
Experimenting without responsibility is naïve. It is precisely middle managers who dare to set boundaries that gain trust. Ask the right questions: what is safe, what risks are acceptable, and how do we mitigate unintended effects?
Having that conversation at the board table, with the necessary ethics, makes you a credible leader in the AI era. And those who want to set this up seriously will soon come across AI governance: clear responsibilities, frameworks, and checks that actually accelerate innovation.
Safe experimentation does not mean that everything must be set in stone, but that there are frameworks that provide support. We often use three simple steps:
- Define the play area. Determine in advance where the boundaries lie, including the tools, data used, and acceptable security risks.
- Provide some direction. Prevent everyone from brainstorming ideas about everything by pointing to areas with a lot of potential.
- Build feedback in. Let users think along about what is going well and what is not. This prevents surprises.
- Evaluate and scale. Decide after a short trial period whether something will be rolled out organization-wide.
This way, there is room for creativity, but with a safety net that limits risks. Innovation gets the chance to grow in a controlled manner. Exactly the middle ground between hasty experimentation and paralyzing policy. (And those who are still waiting "until the policy is finished" will see in this KVK research how often organizations neglect that preparation.)
Whispering Instead of Shouting
A major misconception is that innovation must be grand and spectacular right away. In reality, it starts small and grows with success (and failure). With an idea that you translate into recognizable language, with a demo that shows how a tool enhances processes, or with a colleague who brings you along in a new way of working.
Those who wait for the announcement over the loudspeaker miss the whisper that has already set real change in motion.
Those who want to strengthen that innovation culture will find practical tools in How to Stimulate Creativity and Innovation Within an Organization?
About Marloes Heijink
Marloes Heijink is a manager in the Data & AI team at consultancy and technology company IG&H. She builds and manages digital data solutions with her team that help organizations gain sharper insights and act faster. She combines a passion for data and innovation with a down-to-earth, practical attitude: coming up with smart solutions is great, but they must primarily work. She earned her PhD in Consumer Behaviour at Hong Kong Polytechnic University.
Marloes Heijink, Manager Data & AI at consultancy & technology company IG&H
