TLDR: ChatGPT is great for brainstorming, but business decisions need structure: a recommendation, a confidence score, identified risks, and citations you can verify. A chat thread is useful for five minutes; a structured decision brief is useful for five years.
ChatGPT changed how we research. You can type a question and get an answer in seconds. For brainstorming, drafting emails, or explaining concepts, it's extraordinary. But when the decision you're making carries real consequences — a product launch, a vendor contract, a strategic initiative — the gap between "helpful answer" and "documented decision" becomes a liability.
The answer isn't the decision
When a VP of Operations asks "Should we switch from supplier A to supplier B?", they don't need a conversational answer. They need a structured analysis: what does the evidence say about reliability, cost trajectory, compliance risk, and switching costs? They need that analysis in a format they can share with their board, attach to a procurement record, or revisit when they need to recall the reasoning.
ChatGPT gives you an answer. It doesn't give you a decision brief with cited sources, a confidence score, identified risks, and exportable documentation. And in many industries, an undocumented decision is indistinguishable from no decision at all.
The citation problem
Large language models generate plausible-sounding text. They sometimes cite sources that don't exist. For casual use, this is a minor nuisance. For a business decision with real consequences, unverifiable claims undermine credibility.
Evidence-backed decision support requires real sources. Not "according to studies" — actual papers from Semantic Scholar, actual search results from the web, actual expert commentary. Every claim traceable to its origin.
Structure matters more than intelligence
The most sophisticated language model in the world still produces a wall of text. Decisions require structure:
- Recommendation — what does the evidence support?
- Confidence — how strong is that evidence?
- Risks — what could go wrong?
- Unknowns — what couldn't be determined?
- Sources — where did each claim come from?
This isn't a format preference. It's the difference between a chat transcript and a decision record. One is useful for five minutes. The other is useful for five years.
The question matters as much as the answer
ChatGPT answers whatever you type. If your question is vague, your answer is vague. There's no mechanism to push back and say "this question isn't researchable yet — let's tighten it."
A decision support tool needs a Decision Coach: something that takes "should we expand into Europe?" and turns it into a bounded, researchable question with clear criteria, constraints, and stakeholders defined. Better questions produce dramatically better research.
When is ChatGPT the right tool?
ChatGPT excels at brainstorming, first drafts, code generation, and exploratory research. If you're thinking out loud or need a quick conceptual overview, it's the best tool available.
But when the decision has consequences — financial, reputational, or operational — and when someone might ask "how did you arrive at this conclusion?", you need more than a chat thread. You need documented evidence, structured analysis, and a brief you can stand behind.
The question isn't whether AI should help you decide. It's whether your decisions will have evidence behind them when it matters.