What’s happening inside ops teams right now feels very familiar. A decade ago, we had the Shadow Analytics crisis. Employees didn’t want to wait for IT reports from SAS or Cognos, so they pulled proprietary data into rogue Excel sheets. It worked until the data got corrupted, leaked, or gave conflicting “truths.” We spent years unwinding that mess. AI is following the same pattern. I’m seeing sales and ops teams using “unauthorized” AI tools to summarize meetings or analyze spreadsheets. The employee wins 10+ minutes of productivity, but the company loses: Data Sovereignty: Proprietary NDA company/customer/partner info is fed into 3rd-party AI models that the company doesn’t own. Decision Provenance: If an AI makes a logic call in a silo, and that logic isn’t logged or repeatable, your business operations are officially “off-book.” In my experience, the fix isn’t “banning” the tools (that failed in 2010 and it’ll fail now). The fix is defining where AI belongs in the actual workflow rather than just “vibing” it. Is your org actually setting guardrails, or are employees just ‘Shadow AI-ing’ it until something leaks? submitted by /u/Glittering-Young8692
Originally posted by u/Glittering-Young8692 on r/ArtificialInteligence