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The question is how fast you want to unlock the value.
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AI is everywhere but it's unclear which investments will actually move your metrics and which are expensive experiments.
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Most AI projects fail at the data layer. Pipelines, quality, access all need work before LLMs can deliver value.
Internal teams are stretched
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Legacy systems block everything
Aging, undocumented codebases make AI integration slow, risky, and expensive. They need to move first.