Synthetic intelligence (AI) is right here and the world as we knew is altering quickly. AI instruments have developed tremendously and are complementing workflows in all disciplines. The software program business is an efficient instance. Gone are the times the place data of syntaxes of programming languages was a ability an engineer can be pleased with. With AI within the image now, immediate engineering has change into the extra sought-after ability—whether or not they can assemble sensible prompts to leverage the facility of AI and convey a few leap in effectivity.
How concerning the discipline of non-public finance? Can AI instruments assist a humble retail investor leapfrog his capabilities? It is a tough query to reply, because it includes one’s hard-earned cash. Whereas there is no such thing as a doubt that AI instruments have change into extra mature and highly effective than earlier than, they might nonetheless hallucinate and generate flawed outputs. We tried experimenting with free AI instruments obtainable. In brief, we discovered them to be extraordinarily useful in producing fast analyses, compiling knowledge obtainable on the internet, constructing stock-screeners and making complicated calculations. It is a boon for traders who’re crunched for time. On the identical time, these instruments are liable to be inaccurate that it’s not protected to guess actual cash primarily based purely on an AI-generated evaluation.
One of the best ways then, is to make use of AI-generated outcomes to achieve a fast perspective and deal with them as a launchpad in your additional analyses—and this alone, in our view, makes an excellent case for AI instruments to be a part of one’s private finance arsenal. On this story, we share just a few easy use-cases for elementary traders to get began and in addition spotlight the restrictions of AI instruments with the intention to avoid these pitfalls.
Sector primers
Usually you’ll end up new to a sector and would respect a crisp primer on the sector to get began. We prompted Google’s Gemini to generate a primer on the tyres business. We suggest a pointed immediate as beneath to information the mannequin in getting the solutions you want.
Assume you’re a veteran of the Indian tyres business. Generate a sector primer. Give attention to components such because the incumbents and their market share, the segments they serve, the uncooked supplies, enter price volatility, margins that may be anticipated and the sector’s cyclicality.
Listed below are just a few pointers we learnt from the output.
* MRF, Apollo, CEAT, JK Tyre and Balkrishna Industries collectively management over 85 per cent of the organised market
* MRF has the deepest distribution community, Apollo has a presence in Europe via the Vredestein model and Balkrishna Industries is a pacesetter in off-highway tyres
* Alternative/ after-market gross sales generate increased margins than gross sales to OEMs
* Pure rubber and carbon black (a by-product of crude oil) are key uncooked supplies and their costs influence margins, which might vary between 10 per cent and 17 per cent
* The business is semi-cyclical, given the OEM demand is tied to new car gross sales (cyclical) and substitute demand is tied to put on and tear (non-cyclical)
AI might compile such a primer in seconds, which might have taken days in any other case. You may as well use the ‘Deep Analysis’ characteristic for a thoroughly-researched output, however it takes just a few hours to generate the output relying on the immediate.
Wanting up paperwork
As a elementary investor, you can’t shrink back from studying verbose paperwork like annual stories and earnings name transcripts. AI instruments are right here to make it easy, and that is the use-case we discovered to be probably the most helpful.
We have been curious to understand how Maruti Suzuki’s price construction and margins have been impacted in FY23, when crude oil and commodities’ costs spiked after the outbreak of the Russia-Ukraine warfare. Aside from increased logistics prices, suppliers of solid/ solid and plastic components are depending on crude derivatives and usually go on price inflation again to OEMs like Maruti. Since we’re in the same state of affairs at present, studying the FY23 annual report would give significant perspective.
We uploaded the annual report into NotebookLM, a Google product. The USP of this product is that it largely sticks solely to the paperwork uploaded to generate its solutions and in addition offers citations. We learnt that the corporate did bear commodity price pressures. But, it managed to broaden its EBIT margin from 3.5 per cent in FY22 to 7.3 per cent, pushed by working leverage (19 per cent quantity development) and calibrated value hikes.
Now, going into FY27, can FY23 repeat itself for Maruti? Again then in FY22, gross sales quantity was impacted as a result of semiconductor scarcity, giving the corporate a low base to work with in FY23. The identical can’t be mentioned about FY27, as OEMs have had an excellent 12 months in FY26 publish the GST cuts. Therefore, to guard margin, the corporate is left with the only real choice of climbing costs/ scaling reductions again. This leaves us with intently monitoring value hikes and any resultant influence on demand as key monitorable.
For earnings name transcripts, readers can use Perplexity Finance, the place transcripts of the current 10 quarters are available (underneath ‘Earnings’ tab). It additionally segregates them into matters. You may select a subject from the drop-down checklist. As an example, the administration’s ready remarks, platform synergies and scaling, margins and dangers in modules and polymers phase, technique for aerospace and semiconductor enterprise are among the matters we present in Samvardhana Motherson’s Q3 FY26 earnings name.
Right here’s one other extrapolated use-case. Some ratios equivalent to EBITDA margin and glued property turnover ratio aren’t available in quarterly earnings releases. You may simply add these PDFs into the AI mannequin of your selection and get them calculated in a jiffy. We prompted Claude to calculate mounted property turnover ratio of Samvardhana Motherson for FY23-25. The screenshot of the output may be present in Picture 1.
Put up-market temporary
It isn’t sensible for retail traders to observe the market via the day. Perplexity Finance and Google Finance (Beta) may also help remedy this to an extent. As soon as buying and selling for the day closes, you will get a abstract of how your shares carried out. All you want to do is create a customized watchlist. Whereas Perplexity offers you a readymade abstract (underneath ‘Watchlist’ tab), you have to a immediate to do the identical on Google Finance (Beta). We had created a watchlist with shares from the auto sector on Perplexity Finance. A screenshot of the market temporary for March 27 is given for reference (see Picture 2).
Screening shares
Constructing screeners to filter shares is inevitable in bottom-up investing. Although there are free screeners obtainable on-line, they work with mounted syntaxes. It takes a while to learn the way precisely they work and can be tough for some traders who is probably not savvy sufficient. For this particular use-case, an investor can use the ‘Screener’ characteristic of Perplexity Finance. It enables you to body your situations/ parameters in pure language itself. Right here is an easy screener we tried. To establish quick rising auto ancillary shares, we gave the next immediate. The output is given in Picture 3.
Immediate: Filter auto ancillary corporations that had income development of over 20 per cent in FY25
DCF simulations
If you happen to favor the discounted money flows (DCF) mannequin for valuation selections, AI instruments can deal with that too. Merely put, underneath DCF methodology, future free money flows are discounted for time worth to estimate an funding’s price. The strategy requires you to imagine values for the variables concerned and the mannequin itself is barely nearly as good because the logical accuracy of the assumptions. However as soon as finished with this step, you should utilize any of the AI fashions to run simulations. This use-case might very nicely discover favour with traders who is probably not conversant in spreadsheets.
Immediate:
Calculate Infosys’ market worth of fairness per share utilizing discounted money circulate mannequin. Additionally point out if there’s any upside left from present market value of ₹1,275.
Assume the next variables.
Free money circulate to agency (FCFF) for FY26 = ₹30,000 crore.
FCFFs to develop at 5 per cent between FY27 and FY30.
Perpetual development charge for FCFFs at 2 per cent.
The corporate is net-debt free and so, price of debt may be taken as nil.
For price of fairness, assume danger free charge at 4.4 per cent, fairness danger premium at 7.1 per cent and beta of 0.9 occasions.
Variety of shares excellent at 406 crore.
We replicate the output briefly right here, with out the calculation steps.
Output: Anticipated per-share fairness worth = ₹951
At present value, there is no such thing as a margin of security. As an alternative, the market value is about 34 per cent above the DCF‑derived intrinsic worth.
Readers can mess around with the identical immediate by altering variables to simulate a bull case, a bear case and a impartial case.
Caveat emptor
Now we have barely scraped the floor on this story, and we admit that the chances are countless. Nevertheless, the expertise is in its infancy and has some tough edges to be smoothened. When you determine to undertake AI in your funds, you must completely know its limitations as your portfolio could also be one hallucination away from catastrophe. Listed below are among the limitations we noticed throughout our brief time testing the fashions.
Charts with valuation multiples (P/E, P/B for instance) in a time-series are actually helpful. A P/E time-series, primarily based on day by day costs, is a basic instance. Such charts assist put present valuations in perspective, relative to the previous. We tried constructing a day by day P/B chart for SBI with Perplexity. What we acquired as an alternative was a P/B chart as of economic year-ends, additionally not with out errors (see Picture 4).
Be aware that whereas P/B values for FY21-24 are largely correct, that of FY25 and the present P/B aren’t. Precise P/B ratio as of FY25 finish is 1.4x and the present P/B ratio is 1.6x – that are 2x, in line with Perplexity..
Subsequent, we tried evaluating income development (12 months on 12 months) of TCS, Infosys and HCLTech during the last 4 quarters. Perplexity does have quarterly monetary knowledge underneath the ‘Financials’ tab. Ideally, the mannequin ought to have picked up knowledge from right here to construct the output desk. As an alternative, it tapped internet sources to do it. This meant some values have been incorrect (see Picture 5).
Be aware that TCS’ income in Q2 FY26 truly grew 2.4 per cent and HCLTech’s income grew 8.2 per cent and 13.3 per cent in Q1 FY26 and Q3 FY26 respectively.
Subsequent, have a look Picture 3 once more. It contains Olectra Greentech, which is an OEM and never a provider of auto elements.
Shifting on, we tried prompting Google Finance (Beta) to compute internet revenue margin of Maruti Suzuki, Hyundai and Mahindra & Mahindra for the final 5 quarters. Much like Perplexity, Google Finance too, natively homes quarterly monetary knowledge. Nevertheless, it sourced knowledge from internet sources to construct the output desk. Although some numbers come near actuals, some differ extensively (see Picture 6 together with the infographic desk).
Equally, different niggles do exist. Nevertheless, for the use-cases we talked about earlier and past, AI is simply too highly effective a software for retail traders to not make the most of. We advise readers to make use of these AI platforms as a supplementary supply of their common course of investing and maintain experimenting till more practical, dependable workflows are found.
Attribution to AI merchandise within the story are meant neither as endorsements nor as criticisms
Revealed on March 28, 2026
