MW Why learning to 'speak AI' can help your money manager beat the market
By Saul Cohen
Prompting AI is a language of its own - and finance professionals who are fluent carve a sharp edge
Prompting AI is the first formidable challenger to Excel - the Microsoft $(MSFT)$ formula that's dominated workflows for decades - and a skill needed to succeed on Wall Street and across the investment landscape.
AI tools built specifically for finance are already serving as collaborators for market analysts, portfolio managers and traders. Tech-forward heavyweights such as hedge-fund giant Citadel are going beyond pilots to deploy generative AI across departments, at scale.
AI is infiltrating workflows and becoming essential to jobs in finance. Analysts and portfolio managers who are using generative-AI products daily are improving at their jobs faster than peers who aren't using them. While firms approach this technology differently, it's clear that generative AI plays a role in who is promoted and who is let go.
Soon, AI will shape the financial markets themselves. Gen AI, in particular, will move from a co-pilot to an operating system for finance - engaging with stocks, fixed income, derivatives and other assets. The question becomes: How can market participants use this to augment their work?
The short answer: learn to prompt. Financial analysts fighting for every trade or market move will not rise on the strength of macros alone. Prompting AI - the ability to translate a vague problem into a specific, structured input that yields a decision-guiding output - is the modern version of mastering Excel.
And like Excel, prompting rewards clarity of thought. Traders who can articulate a position in plain language will be skilled at prompting. Traders who lack clarity probably don't understand the trade as well as they think they do.
Prompts are becoming a core part of financial tooling. Instead of spending hours poring over a lengthy 10-K, teams can accelerate tasks with precise prompts and receive structured, defensible outputs powering market-moving decisions in seconds.
In practice, the best results will require specifics about time periods and sources, and must describe what type of output is needed. Here are some examples of prompts from analysts and portfolio managers who are leveraging gen AI to work better and faster:
-- Human-only: Please tell me about Apple.
-- Human x AI prompt: I'd like you to conduct a fundamental analysis of Apple today. Take a look at the top headlines and read through the SEC filings released this quarter.
-- Human-only: How did [public company's] earnings go?
-- Human x AI prompt: I'd like you to analyze today's [public company] Q4 earnings call, summarize the key and/or surprising points, and tie them to recent M&A news or related market shifts. I'm most interested in any specific challenges or shortfalls from the last quarter that may impact stock performance into 2026.
You can't assume the AI knows what you want. The same applies to portfolio construction and risk work: News shocks, once exclusive to bespoke quant infrastructure, can be triggered and iterated through natural-language interfaces.
The firms that treat prompting AI as something to become fluent in - not a gimmick or tertiary function - will win. Prompting design will give them an edge over rivals. Traders, portfolio managers and analysts who embrace prompting in quantitative and qualitative work will uncover insights faster and with greater consistency. People who ignore or undervalue prompting will remain trapped in the drudgery of manual operations, where data points must be located and assembled.
Read: The biggest threat to your job isn't AI. It's that you're afraid of AI.
Is Gen AI flawless? No. Is it consistent? Absolutely.
Finance is a rigorous, always-on industry. Even the best analysts have off-days, caused by either fatigue, distraction or cognitive overload. Every serious trading desk also has redundancy: multiple data providers, multiple risk systems or multiple ways to sanity-check a model.
Gen AI operates with none of those constraints. That makes it the perfect guardrail. Is it flawless? No. Is it consistent? Absolutely. Gen AI won't forget to check liquidity conditions. It won't overlook a line in a footnote. It won't misread a macro data print because it slept poorly or broke up with someone last night.
AI is an alpha driver for financial decision-making today. Its edge comes from speed and breadth - reviewing more scenarios, more counterarguments and more data in much less time. Its value is not omnipresence - it's the ability to unlock decision-motivating data and context in seconds.
For traders, portfolio managers, analysts and other finance operators, the big risk isn't that AI becomes too powerful. It's that firms refuse to use AI for market-facing activity and lose out to tech-savvy peers. Finance professionals need to learn AI's language - or find another line of work.
Saul Cohen is the CEO of Clifton AI. He was the co-founder and CEO of Round, where he built the first actively managed robo adviser.
More: Say goodbye to the 4 p.m. closing bell: Your stocks are becoming 24/7 digital cash
Plus: Don't let AI take your job. Use it to help you and your business thrive.
-Saul Cohen
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(END) Dow Jones Newswires
February 25, 2026 12:30 ET (17:30 GMT)
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