Good stock research is not a race to collect the most facts. It is a process for deciding which facts matter, how they interact, and what would prove your idea wrong. AI is useful because it can quickly organize filings, price action, news, analyst commentary, and risk factors into a readable structure. The danger is that a polished answer can feel more certain than it really is.
Start with a thesis, not a ticker
Before asking an AI tool to analyze a stock, write one sentence explaining why the stock might be mispriced. The sentence should include the business driver, the timing, and the market's possible mistake. For example: "The market is underestimating margin recovery because it is focused on last quarter's revenue slowdown." That gives the model a frame to test instead of a blank canvas to fill.
Ask for the bear case first
AI research becomes more valuable when it challenges you. Ask for the strongest reasons the thesis could fail: valuation pressure, customer concentration, decelerating demand, balance sheet risk, weak insider activity, competitive pricing, or a technical breakdown. If the bear case is vague, the research is not finished.
Separate facts, interpretations, and decisions
A clean workflow has three layers. Facts include revenue growth, margins, cash flow, guidance, valuation multiples, and price levels. Interpretations explain why those facts might matter. Decisions translate the work into a plan: entry zone, invalidation, target range, position size, and review date.
Gross margin expanded while revenue growth slowed.
Management may be prioritizing quality revenue and operating discipline.
Only consider the setup if price holds support after the earnings gap.
Make the model show its work
Do not stop at a rating or price target. Ask what evidence would raise conviction and what evidence would lower it. Ask which data is stale. Ask which assumptions carry the most weight. The goal is not to make the model sound confident; the goal is to expose the structure behind the answer.
Write invalidation before sizing
Every AI-generated setup should include a failure condition. That might be a close below a technical level, a guidance cut, a liquidity problem, a margin reversal, or a catalyst that fails to materialize. If you cannot name the invalidation, the setup is not ready for capital.
Use Sigma Terminal as a second analyst
Sigma Terminal is designed to produce structured stock research: bull case, bear case, entry zone, target, stop loss, and multi-horizon forecasts. The output is most useful when you bring your own thesis, verify the inputs, and use the analysis to sharpen your plan.