I've seen how e-commerce was celebrated as a revolution and how many early projects failed by underestimating cultural factors. I've watched cloud adoptions that were technically brilliant and organisationally chaotic. And today I observe how AI is producing similar patterns in many organisations.
- Technology waves always follow similar patterns: hype, disappointment, mature use
- Organisations systematically underestimate the cultural and communicative effort
- The wish for fast results often leads to worse results
- Clarity, language and a safe frame are timeless success factors
- AI is different in some dimensions today, but the core questions stay the same
A pattern that repeats
Anyone who has lived through several technology waves recognises a basic pattern. It begins with attention. Then comes the hype. Then the disappointment of the first wave. What comes after is often the most important: a more mature engagement with the technology.
I have lived this pattern with the internet, with e-commerce, with cloud, with mobile. I observe it today with AI. The cycle accelerates. But the pattern remains.
What has held up over decades
From that experience I have drawn a few insights that have proven durable:
- People need language before they can accept technology. If people can't explain in their own words what a technology does, they won't use it.
- Pilots without decision criteria are not pilots. A pilot is a structured experiment with a clearly defined scope and success criterion.
- Leadership has to clarify the why before IT clarifies the how. Organisations that start with the how build infrastructure without direction.
- Fast introduction without preparation creates resistance that slowly brakes. Speed in the introduction phase is often bought with friction in the use phase.
What's different with AI
AI is different in one central point. Cloud adoptions changed processes. E-commerce changed sales channels. Mobile changed access paths. AI does something else: it intervenes in thinking processes.
Knowledge work is exactly what people define as particularly valuable about themselves. When AI intervenes precisely here, it triggers stronger emotional reactions than any process automation before.
That doesn't mean AI is threatening. But its introduction requires more communicative care than introducing a new CRM software.
„Every technology introduction is ultimately a communication task. The question isn't: which tool is the best? The question is: which language gives us orientation, and which frame gives us safety to really learn?"Stefan Junge
What organisations can learn from this
- Introduce technology only when the why is clear
- Design pilots with a clear learning goal and defined success criteria
- Take communication as seriously as the technology
- Leadership needs its own understanding, not just an IT recommendation
- Systematically collect and share experiences from early phases
- Take the emotional context of knowledge work seriously, especially with AI
What does this mean concretely for organisations?
AI introductions will become one of the central leadership tasks in the coming years. Not as an IT project, but as organisational change. The organisations that will succeed are those that shape the change process with clarity, communication and a safe frame.
What has impressed me most in 30 years: the organisations that have used new technologies best were not the ones that adopted earliest. They were the ones that knew most clearly what they wanted.
Frequently asked questions
What is the biggest mistake in AI adoption?
The most common mistake is trying to change too much at once, without sufficient orientation.
Is AI really different from earlier technologies?
In depth of impact, yes. AI intervenes in knowledge work, which touches people more strongly than process automation.
How long does a typical AI adoption take?
First experiences can be gathered in a few weeks. Sustained integration usually takes 6 to 18 months.