Agentic AI systems don't wait for instructions—they decide and act independently
When an agent makes a bad decision—books the wrong vendor, approves an improper expense, shares sensitive information—who owns the outcome?
OpenAI's Operator navigates websites autonomously. Other systems approve purchases, schedule meetings, route support tickets. Gartner predicts a jump from under 1% adoption now to 33% of enterprise software by 2028.
The shift creates an accountability problem. Traditional automation followed scripts you could audit. Agentic systems improvise based on their assessment of the situation. That's what makes them useful and what makes them risky.
When an agent makes a bad decision—books the wrong vendor, approves an improper expense, shares sensitive information—who owns the outcome? The developer who built it? The company that deployed it? The product team that configured its parameters? Traditional liability frameworks assume humans made the consequential choices.
Product teams now need to design decision rights for software that acts autonomously. That means defining what agents can decide without human review, building audit trails that explain their reasoning, and creating override mechanisms that don't defeat the purpose of autonomy. The technology works. The governance models don't exist yet.
