AI makes it easier than ever to produce code, models and solution proposals. That does not make architecture less important. It makes it more demanding.
The problem is that different parts of the organisation do different jobs. Some parts need repeatability. Others need coordination under uncertainty. Others require fast action under time pressure. In the same way, different processes try to secure different things: an actual outcome, consistent and legitimate handling, or stable automation. The same architecture logic can therefore not work everywhere.
In this session, Henrik Ekstam shows why we need to distinguish more clearly between planned architecture and emerging architecture. Planned architecture works when the answer is largely known and the change can be realised step by step. Emerging architecture is needed when the problem is not yet fully defined and value must be discovered in reality, together with others.
AI strengthens both needs. To use AI well, we need more structure underneath: data, semantics, governance and operating model. But the easier it becomes to generate answers, the more important it also becomes to understand which logic should dominate in a given situation, and which people need to be involved to create a relevant answer.
After the session, participants will be able to:
Distinguish between when architecture should standardise and when it should enable exploration
Identify which logic a process or problem requires
Understand why AI increases the need for both structure and human interpretation
Use architecture to create clarity in decisions, not only documentation
The core thesis of the session is simple: the role of architecture is not primarily to give answers. It is to create enough clarity for the right answer to emerge in the right context.