AI gave every employee a copilot. The enterprise got nothing.
Every department has adopted a different AI tool. Marketing uses one platform, engineering uses another, operations uses three. Each tool has its own context, its own ingestion pipeline, its own security posture. The enterprise spent a year deploying AI and ended up with fragmentation at scale — the same problem it had before, but now with more data moving in more directions.
No AI tool has the company-level memory that makes the difference between a useful assistant and a genuine intelligence layer. When an analyst asks a question that spans departments, they get department-scoped answers. When a new leader joins, there's no way to get them up to speed on five years of institutional decisions. The knowledge exists — in documents, in emails, in meeting notes — but it's trapped in silos the AI tools can't cross.
And the compliance picture is a mess. HIPAA, SOC 2, data residency requirements, shadow IT risk — every new AI tool the enterprise deploys adds surface area. Security teams are playing whack-a-mole with data governance. The promise of enterprise AI was efficiency and intelligence; the reality is a growing audit liability and no clear owner of what the organization actually knows.