WorkEm Blog
Enterprise Intelligibility: When More Explanation Does Not Mean More Understanding
The modern enterprise is not short of explanations.
It has strategies, roadmaps, architecture models, dashboards, policies, decision records, operating models, transformation narratives, and increasingly AI-generated summaries of all of them.
Yet people still struggle to answer basic questions.
What actually matters?
What depends on what?
Which decisions are still valid?
Which model reflects reality?
What can be trusted enough to act on?
This is the problem of Enterprise Intelligibility.
More explanation does not mean more understanding.
More representation does not mean more intelligibility.
More generated knowledge does not mean more coherent action.
The article argues that Enterprise Intelligibility is becoming a critical architectural concern, especially in AI-shaped enterprises. AI can explain, summarise, and generate enterprise knowledge at speed. But fluent explanation is not the same as grounded understanding.
The future enterprise will not be governed by the amount of knowledge it can generate, but by the amount of knowledge it can make intelligible enough for coherent action.
Read the full article here
/Anders W. Tell
Reimagining Architectural Understanding
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