This is something I currently see in many companies. AI is being tested everywhere, but far too rarely does it become an integral part of everyday operations.
A recent Lünendonk study highlights the scale of the problem: In 66% of the companies surveyed, fewer than one in four AI pilot projects make the transition into production. Only 1% manage to move more than half of their pilots into regular operations.
So the key question is no longer: Are we using AI?
It is: Why do so many AI pilots generate so little measurable business value?
The Real Problem Starts Before AI
Of course, data quality, technical infrastructure, data protection and costs all play an important role. But in my experience, many projects fail much earlier.
There is no clear ownership. There are no defined metrics. The underlying process has never been properly documented. Or the company starts with a tool and then looks for a suitable problem to solve.
That is the wrong order.
AI does not automatically improve a poor process. In the worst case, it simply creates a poor process that now runs faster.
My most important principle is therefore: process first, AI second.
Four Factors That Determine Success
If you want to move AI from pilot status into regular operations, four things need to be clear:
1. Choose the right process:
Start with a frequently recurring and clearly defined workflow – such as standard proposals, meeting minutes or recurring customer inquiries.
2. Define ownership:
A specific person within the relevant business unit must be responsible for the outcome. AI should not be treated solely as an IT project.
3. Measure before you start:
How long does the process take today? What is the error rate? How many follow-up questions arise? Without a baseline, you cannot demonstrate improvement later.
4. Define the end of the pilot:
After 90 days, for example, a decision must be made: scale it, adjust it or stop it.
A Typical Example From Practice
Imagine a sales support team: 20 employees receive access to an AI assistant and attend a prompt-engineering workshop. Three months later, only four of them are still using the tool regularly.
The problem is not necessarily the AI.
A closer look might reveal that proposal templates are outdated and important information is scattered across several different systems. Only after these underlying issues are addressed can AI provide meaningful support.
Now, AI takes over one clearly defined step, results are measured and one person is responsible for implementation.
An experiment becomes a productive process.
AI Implementation Is a Leadership Responsibility
Executives do not need to become AI experts. But they do need to make the right decisions.
Which process do we want to improve? What exactly should change? Who is responsible? And how will we know after 90 days whether the project has been successful?
For me, this is the key difference between companies that simply experiment with AI and companies that actually become more productive with it.
The biggest mistake in AI pilot projects is often not choosing the wrong technology – it is expecting technology to solve an unclear process.
Companies that clarify processes, responsibilities and objectives first create the foundation for turning AI pilots into measurable business value.
Helga Boss – AI Takes Over Routine. People Create Value.
How can companies successfully integrate artificial intelligence into their daily operations, make processes more efficient, and at the same time engage their employees in the transformation?
Helga Boss is an entrepreneur, AI efficiency expert, management consultant, and keynote speaker. She supports companies across the DACH region in implementing artificial intelligence in a practical way, optimizing processes, and turning new technologies into measurable business value.
With her approach “Process First, Then AI,” she combines technological innovation with sustainable transformation. As a lecturer, she shares her expertise in a practical and accessible way. In her keynotes, she demonstrates how companies can use AI effectively, engage their employees in the transformation process, and actively shape the future of work. She is also committed to empowering and promoting women in business and society.
