Why Most Enterprises Aren't Ready to Let AI Agents Touch Their Data
For the last two years, the AI conversation inside most enterprises was about output quality — better prompts, better models, better copilots sitting next to human workflows. That conversation is over. The one replacing it is harder: what happens when an AI agent doesn't just answer a question, but goes and queries a database, updates a record, or triggers a downstream action on its own? The uncomfortable answer, for a lot of organizations, is that nobody quite knows — because the systems those agents will touch were never built with an autonomous, tireless, extremely literal user in mind. A Human Analyst Fails Quietly. An Agent Fails at Scale. When a data set has a stale definition, a missing owner, or an undocumented join, a human analyst usually notices something is off. They pause, ask a colleague, or flag the report as "needs review." That instinct — the small human hesitation that catches bad data before it becomes a bad decision — doesn't exist in an agent un...