Is AI finally starting to kill Equity Research?
Yeah I get the usual tropes of its connectivity to management and everything else and that is true
But who needs to ask some of the basic views around a stock anymore
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As far as I know our call volumes are not down.
BB ER.
I would say that simple client data requests are down at the margin though.
While lots of clients are using AI, there are also many that aren't. I mean many clients are old. They don't really understand AI. There have been so many news events recently that I've been able to more quickly deduce with AI within a short amount of time (something that wouldve taken much more effort some time ago). Many clients still aren't doing this work though - you still get calls like "can you explain what's going on". So what I'm saying is 1) clients aren't using AI as much as you might think outside of CMP. 2) theres probably a lot more room left for SS research to fall in importance (or at the very least, need to change how it operates and markets itself) as clients learn to use AI or as old employees get replaced with new.
AI is certainly reshaping the landscape of equity research, but it’s not outright "killing" it—at least not yet. Based on the most helpful WSO content, here’s the breakdown:
Automation of Basic Tasks: AI is already automating many of the repetitive and foundational tasks in equity research. For example, drafting earnings notes, collecting data, building models, and even generating ESG reports are increasingly being handled by AI systems. This trend is particularly evident in asset management, where entry-level roles like research associates are expected to diminish significantly within the next five years.
AI as a Research Assistant: AI is being used as a "research assistant" to synthesize large amounts of data, highlight key changes in financials, and even identify risk phrases in earnings calls. It can also generate summaries of 10-Ks and other filings, making the process faster and more efficient for analysts.
Limitations of AI: Despite its capabilities, AI struggles with unstructured and nuanced data, such as management tone during earnings calls, commentary in SEC filings, or unique company-specific events like royalty agreements or international expansions. These are areas where human judgment and experience remain critical.
Connectivity to Management: As you mentioned, connectivity to management and qualitative insights from meetings, diligence calls, and conferences are still areas where AI cannot fully replicate human interaction and intuition.
Future Outlook: While AI is simplifying and automating many aspects of equity research, it’s not replacing the core decision-making process. Analysts still play a vital role in interpreting data, making investment decisions, and providing insights that go beyond what AI can currently achieve.
In summary, AI is transforming equity research by automating routine tasks and enhancing efficiency, but it’s not eliminating the need for human analysts—especially for higher-level analysis and nuanced decision-making.
Sources: https://www.wallstreetoasis.com/forum/hedge-fund/machine-learning-taking-over-hf-research-analyst-roles-in-near-future?customgpt=1, Q&A: AI will automate many roles in the IB/PE world. A live Q&A with Arctic, who are recruiting finance professionals to help manage that change, Work at top AM -- AI will virtually kill of entry-level roles in AM over the next 5yrs, Work at top AM -- AI will virtually kill of entry-level roles in AM over the next 5yrs
Easier to imagine buy-side and SS both going away / getting disintermediated in a convergent way, if not necessarily a simultaneous way, than for buy-side to survive AI disruption while SS goes away. If you can do away with SS, why not have human PMs + AI buy-side analysts or even just a human CIO + AI PMs/analysts?
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