Without a control function, AI errors will persist—regardless of how much AI capability improves or how much money organizations spend trying to reduce them.
The Fundamental Principle
Science tells us a simple truth: any process that lacks a control function will unavoidably produce errors and eventually fail. Whether one loses control of a car while driving or of a knife while cutting vegetables, we can reliably predict the result. This fundamental principle is used extensively in operations management, systems engineering, quality, reliability, and many other scientific disciplines. Control is what keeps a process within required bounds despite variation, disturbances, and human error. AI reliability is essential; therefore, AI operations are no exception to this fundamental principle.
Why AI Is No Exception
AI’s probabilistic operation continuously introduces variation and uncertainty. Users add further uncertainty through incomplete, ambiguous, or otherwise imperfect prompts. The combination creates continuously emerging variability that affects AI reliability. Without a control function acting across the full request lifecycle, these perturbations propagate into errors. Better models, more computing power, better prompts, more training, and more human review may reduce error rates, but they cannot, in principle, prevent errors from emerging. AI reliability requires a control function.
AI capability will continue to improve, but without a control function, errors will persist. Broad organizational adoption and diffusion of AI require control across the full request lifecycle. All OpExAI solutions are designed to implement this principle.