According to recent figures from Statistics Netherlands, one in six Dutch companies now uses AI. That is a doubling compared to two years earlier. Especially applications around marketing and sales stand out: of the companies that use AI, 35% use it for that purpose. Text mining, natural language generation and speech recognition are also clearly on the rise.
That’s good news. Because AI is coming out of the experimentation phase.
But there is also an important warning in the same CBS study: companies that have considered but not yet used AI mainly cite lack of experience as the reason. In addition, privacy and legal uncertainty play a major role.
And that is precisely where we believe the real challenge begins.
Not with the question, “What can AI do?”
But with questions like, “What specifically will AI help our employees with tomorrow?” “Which customer questions should we automate and which ones should we not?” “How do we ensure that AI remains secure, controllable and understandable?”
At Pegamento, we see that organizations often don’t get stuck on ambition. There is plenty of that. They get stuck on the translation to practice.
Because “AI in customer contact” sounds interesting, but quickly remains abstract. Employees, team leaders and managers need more concrete knowledge such as:
3 customer queries you’re better off not letting AI handle entirely. For example, complaints with emotional overtones, questions with legal implications or situations where customer data needs to be interpreted.
5 moments when AI does help an employee directly. Consider summarizing conversations, recognizing customer intent, preparing a response, routing emails or retrieving relevant knowledge from internal sources.
A practical decision tree: automate, support or escalate? Not every question needs to be answered by AI. Sometimes AI is especially valuable as a co-pilot: quickly analyzing, summarizing and making suggestions while the employee remains in control.
A knowledge base suitable for AI. Many organizations already have a lot of information, but it is often fragmented, outdated or not written in question-and-answer form. AI becomes reliable only when the source information is correct.
Clear ground rules for privacy, logging and human control. Especially in customer contact, it is often about personal data, context and nuance. That’s where you don’t want to automate blindly, but design consciously.
That’s where Pegamento can support: not by making AI bigger than it needs to be, but by making it smaller, more concrete and workable.
We help organizations translate AI applications in customer contact step by step into processes, content, training and governance. From use case selection to setup. From knowledge models to employee instructions. From compliance questions to practical workplace adoption.
CBS figures show that AI use is growing. The next phase revolves around something else: learning to apply AI properly.
Not as hype. Not as a loose experiment. But as practical support for better customer processes, faster responses and employees who get a better grip on their work.
Because the question is no longer whether AI will have a role in customer contact.
The question is: how do we ensure that AI does what it is supposed to do and no more than that?
