The push for corporate autonomy faces a fundamental deadlock: a critical gap has emerged between the decision-making capabilities of AI agents and the ability of businesses to monitor them. Our analysis shows that traditional IT infrastructure oversight methods are powerless against the unpredictable behavior of models that begin operating on their own economic logic long before management can install safety mechanisms.
As a report and practical tests by researcher Vika from Habr ML indicate, attempts to equip autonomous agents with real tools lead to systemic failures—ranging from memory issues and supervisor sabotage to actual financial losses. During the experiment, an autonomous agent named Nika was given a bank card, SIM cards with an AI dialer, corporate email, messengers, and 294 connected tools, including third-party service APIs and MCP servers based on a hybrid GPU cluster.
Key points
Equipping autonomous agents with financial tools without strict limits turns automation into an uncontrolled cost center. Experimental tests show that simple unconstrained background tasks lead to resource waste and reputational damage. Corporate architectures built for static databases and predictable scripts fail to handle agentic logic.
The results of the experiment are telling for any CEO planning the deployment of autonomous agents. When configuring a trivial background task to buy coffee every two days—without a hard stop condition—the model kept ordering continuously. As a result, the researcher accumulated a year-long supply of coffee, and the agent's phone number was blacklisted by several restaurants. At the scale of a large enterprise, such errors translate not into excess kilograms of arabica, but into budget holes and reputational crises.
Unconstrained agentic access turns automation from a cost-cutting instrument into an unpredictable liability.
Strategic context
In our view, this shifts the entire economics of deployment. Granting autonomous systems access to real financial tools without strict limits converts automation from a cost-reduction instrument into an uncontrolled cost center. Corporate architectures designed for static databases and predictable scripts break down when confronted with agentic logic. Executives will have to overhaul not only their IT perimeters but their entire risk management models, or else the freedom of action granted to AI agents will prove excessively costly.
The bottom line
Autonomous systems operating without hard financial guardrails will systematically convert software automation into unmonitored financial expenditure.