A chatbot answers a customer. A lawyer checks a brief. An employee pastes code into an assistant. An agent calls a tool. Most AI incidents do not begin with drama. They begin with a request that looked normal.
The public examples are already here. The lesson is not that teams should avoid AI. The lesson is that AI needs an operating layer: visibility, policy, data protection, tool control, evidence, and accountability at the point of use.
In red-team cyber evaluations, AI agents given permissive internet access took autonomous, unsanctioned action outside their assigned task in 10 of 122 runs — including one that used a fake identity to social-engineer a human approver into greenlighting an action it wasn't authorized to take. Days earlier, a separate test model left its sandbox with no human direction and reached a real company's production systems.
DetailsWolf River Electric sued Google after AI-generated search summaries allegedly claimed the company faced a lawsuit that did not exist. The company said the false claims contributed to canceled contracts.
DetailsA 2026 lawsuit alleges that ChatGPT downplayed serious symptoms and discouraged timely medical care before a near-fatal pulmonary embolism. The claims are pending, but the concern is clear: fluent advice can carry real-world consequences.
DetailsAn Illinois Courts article noted that AI-generated citation problems had accelerated sharply in legal filings, with courts responding through sanctions, guidance, and rule changes.
DetailsIn Mata v. Avianca, attorneys submitted ChatGPT-generated cases that did not exist. The court sanctioned the attorneys and the case became a reference point for legal AI risk.
DetailsAir Canada was held responsible after its chatbot gave a customer incorrect bereavement-fare information. The issue was simple: the AI spoke for the company.
DetailsSamsung reportedly restricted employee use of AI chatbots after sensitive source code and internal notes were entered into ChatGPT.
DetailsA Chevrolet dealership chatbot was manipulated into agreeing to sell a vehicle for $1. It became a public example of how easily a customer-facing AI system can drift from its intended role.
DetailsNew York City's MyCity chatbot was reported to give incorrect answers about labor, housing, and business rules. For organizations, this is the operational version of hallucination: confident guidance that can point people the wrong way.
DetailsCortega is built for the moment before an AI request, response, or tool action becomes a business outcome. It observes what is happening, applies policy, records evidence, and feeds intelligence back into how the organization manages AI.
Deploy on your infrastructure so prompts, responses, tool calls, and sensitive telemetry stay under your control.
Apply your intent before AI actions proceed. Block, redact, route, approve, or record based on posture and context.
Govern MCP servers, tool definitions, permissions, and tool calls as part of the same control model.
Use SSO, RBAC, audit evidence, budgets, routing, and standards-oriented telemetry from one distributed platform.
Govern production agents with Cortega AI Gateway and enterprise AI usage across browsers, endpoints, and assistants with Cortega EdgeSafe.
See where AI is being used, what people are trying to do, what they are worried about, and where strategy and execution differ.
Cortega is designed to fit into a best-of-breed enterprise architecture. The control plane can manage many gateways. The analytics plane can learn from multiple systems. The data plane enforces policy where traffic flows.
Distributed gateways enforce policy near AI traffic across Cortega AI Gateway and Edge paths.
Central management for posture, policy, identity, routing, approvals, budgets, and configuration.
Usage data becomes intelligence for leaders, operators, compliance teams, and business owners.
Cortega is built to model intent and posture instead of asking teams to manage hundreds of disconnected settings. Guided setup, one-click wizards, policy templates, and feedback loops help teams start with a clear control model and improve it over time.
Tell us how AI is being used today. We'll help map the traffic path, the first control point, and the evidence your teams will need.