Generic AI models need context to work in your business. The companies winning at AI treat contextualization as infrastructure, not a prompt trick, and the gap between pilots and production almost always comes down to this single capability.
Read moreMost AI write-offs trace to how organizations translate model outputs into decisions, not to the models themselves. Without documentation and clear ownership of this translation layer, companies risk impairment charges and waste their AI investments.
Read moreMost firms skip the work of turning AI outputs into formats their executives can actually act on. That gap between model output and usable decision is where AI value leaks away.
Read morePicking the AI tool before diagnosing the actual problem is why 95% of generative AI deployments produce zero measurable returns. Listen first, decide second.
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