CA Siddhartha Dongre  |  April 15, 2026

From equity research to due diligence, AI is reshaping how analysts work — faster models, deeper insights, and a new era for skilled finance professionals.

Workflow in Investment Research Is Shifting Towards AI

Something quiet is happening in investment research. It is not making headlines yet, but if you work in equity research, private equity, or investment banking, you have probably felt it. The tools are changing. The workflows are shifting. And a question that used to feel theoretical is now very real: what happens to analysts when AI gets good enough?

Let us be honest about where things stand today. AI can now read an entire quarter of earnings transcripts in minutes. It can parse 10-Ks, flag material changes in SEC filings, update financial models with new data, and draft first-pass research notes that look remarkably polished. It can screen hundreds of CIMs overnight, score deal attractiveness, and surface patterns across datasets that would take a human team weeks to process.

Here Is the Part Nobody Wants to Say Out Loud

A significant portion of what junior and mid-level analysts do today is already automatable. Data collection, model population, comparable company screening, formatting pitch decks, pulling together morning notes. These are tasks that AI does not just match human speed on — it destroys it. An AI model does not get tired at 2 AM. It does not make formula errors after its fourth cup of coffee. It does not need two weeks of onboarding.

The firms that move fastest on AI adoption will need fewer people for the same output. That is not a prediction. It is already happening. And if your entire value as an analyst is tied to tasks that a well-prompted language model can replicate, your role is on borrowed time.

But Here Is What AI Still Cannot Do

AI is exceptional at processing information. It is terrible at judgment. It cannot sit across the table from a management team and sense that their confidence about next quarter is performative. It cannot read between the lines of a footnote disclosure the way a seasoned Chartered Accountant or CFA can. It does not understand why a particular working capital cycle matters differently for a capital-light SaaS business versus a manufacturing company with heavy receivables.

Investment research has always been about forming a view, not just gathering data. The analyst who survives the AI wave is the one who uses these tools to eliminate the drudgery and spends their freed-up hours doing what actually moves the needle: building conviction, stress-testing theses, and communicating insights that make portfolio managers act.

The future is not analysts versus AI. It is analysts armed with AI versus those who are not. The winning formula is a qualified professional — a CA, CFA, or MBA Finance — with real domain expertise, working alongside AI tools that handle the heavy lifting. That combination produces research that is faster, deeper, and more defensible than either could deliver alone.