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The Most Valuable Resource in Research Is Analyst Time
It is 8:30 in the morning. An analyst has an earnings call at 10, a model to update, three company filings to review and a client note to send before lunch.
A surprising amount of an analyst’s day goes on work that is necessary but not necessarily analytical: downloading filings, extracting numbers, updating trackers and preparing recurring tables. The value of an analyst is rarely in how quickly they can copy a number from a filing. It is in what they do with that number. An automated workflow can monitor results, extract key financials, identify changes from the previous period and flag exceptions. The analyst can then start with what has changed and ask why it changed. Judgement stays with the analyst: whether a variance is temporary, structural or already in the valuation, and whether new guidance alters the investment thesis. The real advantage is not fewer analysts. It is better allocation of analyst time.
The problem is not a lack of information. There is too much of it.
A surprising amount of an analyst’s day is spent doing work that is necessary but not necessarily analytical: downloading filings, extracting numbers, updating trackers, comparing periods, checking whether guidance has changed and preparing recurring tables.
None of this is unimportant. But after years in equity research, one thing becomes clear:
The value of an analyst is rarely in how quickly they can copy a number from page 47 of a filing. It is in what they do with that number.
The economics of research
This is where automation can change the economics of research.
The opportunity is not simply to make the existing workflow faster. It is to remove the recurring work that consumes attention. An automated workflow can monitor results, extract key financials, identify changes from the previous period and flag exceptions. An analyst can then start with what has changed and, more importantly, ask why it changed.
That distinction matters.
If revenue is 12% below expectations, the system can identify the variance. Understanding whether it is temporary, structural or already reflected in the valuation still requires judgement. If management changes its guidance, AI can surface the change. Determining whether it alters the investment thesis is still an analyst’s job.
| Situation | Give machines | Give analysts |
|---|---|---|
| Results | Monitor results and extract key financials | Start with what has changed and ask why it changed |
| Revenue misses expectations | Identify the variance | Judge whether it is temporary, structural or already reflected in the valuation |
| Management changes guidance | Surface the change | Determine whether it alters the investment thesis |
| Recurring work | Download filings, update trackers, compare periods, prepare recurring tables | Challenge assumptions, connect the dots, have better conversations with clients |
Better allocation of analyst time
The real advantage, therefore, is not fewer analysts or more output for the sake of output. It is better allocation of analyst time.
- Give machines the recurring work.
- Give analysts the exceptions.
- Give experienced professionals more time to challenge assumptions, connect the dots and have better conversations with clients.
The next generation of research teams may not win because they process information faster.
They may win because their analysts spend more of their day doing the one thing technology still struggles to replicate consistently:
thinking about what matters.
Where does your analysts’ time go?
If recurring work is taking up your research team’s day, we can help you decide what to give to machines and what to keep with your analysts.
Talk to our research teamFrequently asked questions
Is the goal of equity research automation to reduce the number of analysts?
No. The real advantage is not fewer analysts or more output for the sake of output. It is better allocation of analyst time. Machines take the recurring work. Analysts take the exceptions.
Which parts of the equity research workflow can be automated?
The work that is necessary but not necessarily analytical: downloading filings, extracting numbers, updating trackers, comparing periods, checking whether guidance has changed and preparing recurring tables. An automated workflow can monitor results, extract key financials, identify changes from the previous period and flag exceptions.
What does AI still leave to the analyst?
Judgement. If revenue is below expectations, the system can identify the variance. Whether it is temporary, structural or already reflected in the valuation still requires judgement. If management changes its guidance, AI can surface the change. Whether it alters the investment thesis is still the analyst’s job.
How does automation change the economics of research?
The opportunity is not simply to make the existing workflow faster. It is to remove the recurring work that consumes attention. Analysts can then start with what has changed and ask why it changed. Experienced professionals get more time to challenge assumptions, connect the dots and have better conversations with clients.
