How should we structure teams working on AI projects?
Avoid the common anti-pattern of a centralized 'AI team' that serves the whole organization. This creates bottlenecks and disconnects AI development from domain expertise. Instead, embed AI capabilities within product teams - give them access to ML engineers or AI-literate developers who understand the business context.
A small central AI platform team can provide shared infrastructure (model serving, evaluation pipelines, cost monitoring) without owning every AI feature. This follows Team Topologies principles: the platform team enables, the stream-aligned teams deliver. The biggest risk isn't technical - it's organizational.
AI projects fail more often from misaligned incentives and unclear ownership than from model accuracy problems.
This question reflects common advisory themes. It is editorially curated, not sourced from individual conversations.
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