"On one side, we have the deterministic model. This is how we have built software and businesses for 50 years. Every piece of software you bought - from your CRM system to a basic spreadsheet - has been precise, rule-bound, and intolerant of error. Input A plus Input B always equals Output C. If it doesn't, you have a bug that needs fixing."
"On the other side, we have Generative AI that breaks this rule. It is probabilistic, creative and context-dependent. The same inputs can produce different outputs. It's a reasoning engine, not a calculator. This allows you to ask questions that deterministic systems can't answer. What will tariffs do to my revenue this year? How would conflict in the Taiwan Strait affect my commodities pricing? Questions like these have no certain answer, but foundation AI models can analyze vast amounts of data and model multiple outcomes to inform your decisions."
"The winners in this new era will be the companies that stop trying to suppress uncertainty and start operationalizing it. Here are three shifts required to re-wire your business and fully capitalize on the AI future. The friction you are feeling right now in your operating model, from compliance to quality control, is because we built our business systems to hunt down and eliminate uncertainty. However, you can't force a probabilistic engine into a deterministic operating model."
Deterministic software operates on precise rules where identical inputs always produce identical outputs, and deviations signal bugs. Generative AI is probabilistic, creative, and context-dependent, producing varied outputs from the same inputs and acting as a reasoning engine rather than a calculator. Probabilistic models can analyze large datasets and model multiple outcomes to inform decisions on uncertain questions like tariff impacts or geopolitical disruptions. Existing operating models create friction because they were designed to eliminate uncertainty and cannot absorb probabilistic behavior. Organizations must stop treating AI like a faster spreadsheet and instead operationalize uncertainty, measuring autonomy as well as efficiency.
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