This article appeared as a partner content supplement in Het Financieele Dagblad (FD) on 20 April 2026. Below is our own piece, as it ran in print.
A year ago, AI conversations in boardrooms were still about tools and training. Now leaders see that competitors using artificial intelligence are eating into their market position. AI is no longer a tool for individual employees — the technology is moving to the core of business operations, where questions arise about productivity, costs, organizational design and competitiveness. And in that gap, a new market of advisors is emerging.
In practice, attention has shifted quickly toward automation, redesigning processes, and the question of how existing business models have to move along. Companies want to grow without hiring people at the same pace. They're looking for ways to deploy scarce knowledge workers more effectively, reduce repetitive activities and prevent errors. Most companies know by now that they need to do something with AI, but not where to start. And only giving a training or a strategy presentation doesn't help. You have to look at people, processes and technology at the same time. Only when those three come together does real movement emerge.
Projects get stuck
We see many AI projects stall because organizations still treat AI as a tool that will be picked up automatically once it's available. In reality, adoption requires leadership, a change narrative, and concrete applications that show results quickly. That's why we tackle it in one motion. With the leadership team, we look at where the company is heading. On the work floor, we investigate where employees are currently losing time and energy.
Within a few weeks, that produces not just a roadmap, but a first application that's already running: concrete proof that AI works in the organization, and employees who know how to move forward with it. If you only automate, you get resistance. If you only train, it stays non-committal. And if you only run a strategy session, all you have to show is a nice PowerPoint. Companies gain more from one working application, plus a plan, plus employees who understand why this is happening.
Human capital
The biggest value often isn't in cost savings, but in freeing up human capital. Think of an experienced fraud investigator stuck in routine research, reporting and internal questions. By taking that kind of standard work off their plate, room opens up for the complex work they were originally hired for. The promise isn't just "doing more with fewer people." Often it's: letting good people do again what they were actually hired for — where their real value lies.
In practice
That approach aligns with examples from the field. At a trainer in the technical sector, we built a system in six weeks that links large amounts of lesson and exam knowledge, so custom learning materials can be composed faster. Elsewhere, we're working on the automatic distribution of incoming messages, generating certificates, and controlling error-prone order flows in production environments.
AI must not live in the shadow of the organization. As soon as people use it secretly, you learn nothing as a company and you don't get a shared standard. You have to put it in the light, with clear frameworks, training and examples from daily work. Then employees start bringing forward improvement ideas themselves.
Risks
With that comes the question of risks. However attractive the technology, companies must determine which data ends up where, which models may or may not be used, and how governance is set up. Especially with sensitive information, that's a precondition — otherwise employees are pasting client files into ChatGPT without anyone knowing. Some organizations therefore choose closed environments or local models, to keep a grip on privacy, confidentiality and compliance.
At the same time, security must not become an excuse to halt development. Reasoning only from prohibitions pushes AI into the informal sphere, where employees start using tools on their own without shared policy or oversight. The art is to organize freedom within clear frameworks. The real question isn't just how to become cheaper or faster, but what you'll do with the time and quality that's freed up. As digital services get ever cheaper, you have to distinguish yourself as a company on humanity, expertise and choices. That's where the real competitive advantage lies.
A necessary task for leadership
For executives, there lies an uncomfortable but necessary task. AI is not an isolated IT project, but an organizational change that touches your structure, your business model, and the role of every employee. Those who start now build a lead while the rules are still in motion.
