AI Has A Consumption Problem—And Your Organization Is Feeding It Poorly

InnovationAI Has A Consumption Problem—And Your Organization Is Feeding It PoorlyBySean Nathaniel,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)Jun 03, 2026, 07:00am EDTSean Nathaniel is CEO of Upland, a leader in AI-powered knowledge and content management software trusted by 1,100+ enterprises worldwide. gettyEvery enterprise I talk to has an AI story and most of them sound the same. Leadership approved the investment. A team was assembled. A use case was identified. A tool was deployed. And then...not much happened. Outputs were unreliable, employees stopped trusting the system and the initiative quietly stalled as the next one was announced. We've been conditioned to blame the technology. Wrong model. Wrong vendor. Wrong prompt engineering. But in my experience, that diagnosis is almost always wrong—and it's costing enterprises real money to keep getting it wrong.The problem isn't what AI is doing. It's what we're feeding it.Three Assets, One Unsolved Problem Enterprises have spent decades building three distinct categories of intelligence assets, often without thinking of them that way. The first is knowledge: the curated, deliberate capture of human expertise. Consider your company policies, processes, taxonomies, best practices and institutional memory. This is what your most experienced people know, the hard-won institutional intelligence that took years to build. The second is content: the living output of your organization's daily work. Content like proposals, reports, presentations and contracts all fit this as they’re created continuously by end users without much governance. However, it’s full of implicit intelligence, such as decisions made, patterns established and lessons learned. The third is data: the structured transactional record of your operations. This is the layer m...