This graphic from a master’s thesis honestly stayed on my mind longer than I expected.
The recommended approach shown is clear, realistic, and absolutely plausible for a small or medium sized company. Start with a pilot project. Then move on to data integration, which simply takes time. After that comes scaling and strategic anchoring. Step by step, with low risk, across processes, and easy to communicate within the team. This is exactly how many organizations work in reality. And that is precisely why this recommendation feels so convincing.
And yet, something about it makes me uneasy.
We are currently experiencing exponential growth in innovation. Many signs suggest that we will see a major performance leap in generative AI this year alone. Against this backdrop, a timeline stretching to 2027 almost feels slowed down. Maybe even dangerously slow, if competitive advantages are created in ever shorter cycles.
At the same time, I know from countless workshops and projects that these timeframes are very real for many SMEs. Not because of ignorance, but because of responsibility. Teams need to be taken along. Processes must not collapse. Trust, acceptance, and skill building do not emerge overnight.
And still, I keep asking myself whether we need to adjust our way of thinking.
What happens if we plan carefully until 2027, but along the way completely new solutions emerge that overtake everything we have planned so far? Do we not need to iterate faster, stop more boldly, decide earlier, and think about this possibility from the very beginning? Maybe not secure everything, but consciously work with uncertainty and build strategies that are more flexible.
For me, this creates an exciting tension: realism versus realistic utopia.
I keep asking myself:
Is it better to move slowly, steadily, and stay compatible?
Or to react faster in order not to miss the real advantages?
Or do we need entirely new time logics for innovation in SMEs that allow both at the same time?
