Agents Unsupervised: Confidence Without Control
Ready to see whether your AI agents are actually as safe as your team believes? Our comprehensive report reveals the surprising gap between confidence and control in agent DLC, based on insights from 700 engineering leaders and practitioners across the United States, the United Kingdom, France, Germany, and India. This study uncovers a pattern that repeats across every stage of the agent lifecycle: organizations feel confident, but the controls that would justify that confidence usually aren't there.
While 75% of organizations already have AI agents running in production, the real story is more nuanced. Confidence in testing, security, inventory, cost, and rollback readiness all landed in the mid-70s. But, the actual controls behind that confidence come in 30 to 55 points lower, and in some domains, confidence doesn't track reality at all.
What You'll Discover:
- The enforcement gap: 74% of organizations are confident their evals would catch a bad release before production, but only 19% actually have a gate that blocks every release automatically.
- The security blind spot: 87% of organizations had at least one agent-related security event this year, and confidence didn't predict who had incidents.
- The maturity roadmap: 76% of organizations have plans to close the confidence gap within the next six months.
Download your copy now to see where your organization's agent program actually stands before the incident data makes the case for you.
Bonus: Can you spot our confidence vs. control interactive game? Read the report, find the game, and play along.
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