How Claude disrupts deal team structure?
Curious to hear everyone’s thoughts on how AI (particularly Claude) transforms / disrupts private equity deal team structure and workflow in the next 5 years. My guess is AI will make analyst and associate work obsolete (AI can cut data much faster and can scrape across the internet for diligence / research in seconds). If technical skill no longer the core competency of a good junior PE investor, what would it be now?
If you’re a partner, how do you redesign your team for the AI era? Would you chop out analysts and associates or does AI simply compress timelines rather than eliminate headcount?
I think it’s mid levels that get eliminated. Associates spend more time doing VP tasks (straight forward docs, third party advisors, credit agreements etc) and partners pick up some amount of the higher complexity VP tasks that are far easier with AI tools. Firms eliminate expensive and carry dilutive employees and continue to churn and burn through associates who they don’t need to offer high wages or long term incentives to.
Agree. Claude excels at data crunching and VDR digestion and I can now spend more time thinking about the so whats and next steps.
I highly doubt it. Most associates cannot spot a right from a wrong or a complete from an incomplete answer even if it’s in front of them. The partners need assuring that the model doesn’t hallucinate etc.
I’m more afraid that the lowest rungs will be cut because ‘these tasks are so quick and easy with AI’ (they’re not) and I go back to being some souped up associate / snr asso
Same. Not a chance I would trust a 24 year old associate with running docs, doing real biz dev, managing lenders, or driving R&W. I think the most likely outcome is deal team structures remain as is and the level and quality of all outputs (decks, models, calls, deals, portco stuff) goes up.
There's a lot more money on deploying capital and driving up returns than there is in cost cutting.
Remember, most GPs are already effectively 40%+ EBITDA margin businesses. It's not like they are starving for cash flow.
Bro thinks driving R&W and managing lenders is some complicated rocket science hahahaha
I think too many people are jumping to the conclusion that headcount will be eliminated. Was it eliminated when the industry moved from paper to Excel? And when datarooms transitioned from literal datarooms with paper documents (where you couldn't copy anything and had to take notes) to a virtual dataroom where everything is a soft copy and easily accessible from anywhere?
My hypothesis on how this plays out is the industry becomes much more sophisticated, efficient, and capable of a much larger volume of analyses. For anyone who has had enough reps to see this themselves, there is a lot of paper-pushing and low value-add tasks we have to do during a live deal that take up significantly more time than people appreciate. With AI tools, the time dedicated to those tasks should shrink considerably and we'll be able to spend so much more time doing higher value-add work that allows us to have more conviction in our thesis.
I don’t really think it’s jumping to conclusions when Block just cut 40% of staff.
Based on CURRENT deal flow a firm leads way less staff. So in order to believe there won’t be mass layoffs or at least a severe hiring freeze, you have to believe AI will lead to way more deal flow for firms that implement. But there’s a finite number of companies available for LBO, growth funding, VC, etcetera. And they’re currently already being tapped - the market is highly saturated. I think would have to believe AI will create a whole new wave of companies that the industry can go after. So far I see # decreasing as a tiny subset (openAI, Anthropic, etc) creates general tech that can replace a large swath, leading to decrease in opportunities for deals.
That said, the early innings of dot com were similar with small subset of Netscape, AOL, Yahoo, etc. threatening to upend a large swath. Ultimately the ecosystem exploded and created way more companies.
So we have to bank on the idea that will happen with AI. I think that’s a BIG open question. This time could actually be different. AIs capabilities are less support tool and more full replacement, and might actually have tiny subset of winners. Either way, there will be a lag until any potential new wave of companies comes. Hope it works out long term.
This assumes that all we do is process platform deals all day, which isn't the case. A huge part of the job is sourcing, portfolio M&A (especially in 2026 when basically every fund is a buy and build machine), thematic research, and value creation initiatives. Every single one of my management teams are at capacity - if we had more time, we could be helping them on things. We could be further on the learning curve on themes for future deals. We could do more to build our networks.
It also assumes that funds are perfectly and exhaustively diligencing opportunities, which despite lots of industry bluster, is certainly not the case. You could be diligencing your opportunities better, more, and faster. Never admit this internally (for obvious political reasons), but on the anonymous forum, think we can all agree it is the case. If you don't know how you could do more diligence, you need to think more.
On the add on side, I'd argue that AI may increase the size of the universe (considerably), as it enables both (i) unsophisticated small time sellers to come up the learning curve on M&A and (ii) allows us to diligence small little businesses at lower time and dollar cost. It allows you to boil the ocean and handle the complexity with ease.
Dude Block was already bloated hence the stock rose and the guy had a bloated corporate structure back when he was in Twitter so it is not really about AI per se. The guy is shit at managing headcount
block had huge covid overhang from hiring tho
"...when Block just cut 40% of staff."
Tell me you have no clue how Dorsey runs his companies without saying you have no clue how Dorsey runs his companies...
Block 2.5-3x headcount during covid. AI is an excuse for over hiring. I hope you do better research on your LBOs.
I think we’re ignoring the “agentic” part of AI, that is setting up agents that will literally do that work without a human in the loop (and faster/better over time). The innovations you named increased productivity. What we will see from AI in the next decade is that agents will be able to completely replace a human’s workload at 1/10th of the cost. This will not end up like anyone in this comment section is predicting it will.
Replace a humans workflow, how exactly?
There still needs to be an author or executor of the workflow of the AI. And you think any seniors at a PE firm would be comfortable with this? Beyond this of course there’s juniors being needed just for the sake of becoming future seniors.
This transition will be gradual. VCs who think this change is happening suddenly are underestimating the stickiness of PE.
Here’s my bet: there will be several first movers that replace all humans with AI and something really bad will inevitably happen due to the AI’s decision making, which will lead governments to regulate the use of AI (e.g., cannot give full autonomy to x or y). I think all of us here forget that humans are not actually proactive creatures, instead we wait for precedent to determine our future actions. See: every regulation known to man.
This probably sounds tuff if you’re a virgin
Disagree first comment above about mid levels being the first to be cut. I think it’s most definitely associates first (and agree with main comment there might not be any headcount reduction at all given there’s simply so much more room to do the job better)
MDs will always find value in a couple high-performing mid-levels they can trust to oversee + quarterback key things. Can’t trust an A1 with something super critical.
Mid-levels will be able to do more with less. And the “need” for extra pair of associate burn/churn hands goes down
We’re already seeing it in lateral associate market last couple years. Firms are saying they can do without it, esp given the deal environment.
Yeah because in the history of corporate America, cutting trust worthy mid levels who oversee the process has never happened… and every company definitely has legions of middle managers for that reason lol
In all seriousness, there is a reason why every company is now shifting to individual contributor vs team models. People in PE completely over exaggerate how difficult their work is, especially when most firms try as much as possible to mirror the exact same set of docs and deal structures across all deals.
The real impact of Claude will be that it will reduce the headcount of the PE industry not because it replaces white collar workers but because the PE industry has too many firms, too much capital, and terrible returns. The industry is past its peak and over time most MM / UMM funds will die zombie deaths. AI will cause disruption to valuations of certain capital-light / services businesses that will put pressure on top-line growth.
You guys see recent UBS news cutting dinner expense? Traditionally I always see the core competency of an associate is technical horsepower, but now that it can be replaced by AI for cheaper, I think our negotiating leverage is diminishing. We may end up doing much more outputs for the same or maybe less compensation.
Every example people have shared of AI impacting headcount have come from companies in decline, which is telling:
1) Block - they are correcting for an 10,000 headcount overhire during COVID mania and made an illogically large bet towards crypto that hasn’t panned out. This was a bloated firm that is employing the Elon acquiring Twitter and slashing 80% of HC strategy. AI makes Jack sound like less of a villain than they made Elon to be.
2) UBS cutting meal stipends as a sign of writing on the wall — let’s be honest, this firm has been hanging on by a thread for the last 5 years. Everyone pointing to them as an omen wouldn’t be caught dead applying to work there. I’ll get scared when D Sol goes on the record with the AI replacing headcount strategy but they won’t do that because successful firms are focusing on employing AI for growth than scavenging for efficiency
3) MM / PE firms replacing juniors - mentioned above but there’s also a necessary overcorrection for a bloated industry. The alpha in PE has been patched, it’s not the same environment that made KKR successful in the 80’s and those golden days are NOT coming back.
Whenever you dance about AI “taking jobs” coming out of a CEO’s mouth, ask yourself: Has this company or industry been absolutely crushing it and growing over the last 5-10 years? Answer is almost always no.
Absolutely this, and also everybody who is not in the industry should just shut their mouth given majority people in this site are not PE.
All the PE professionals ask yourself; for the past 5 years with exponential growth in AI, has your work hours dropped in PE? Are associates twiddling their thumbs because AI is doing all the work?
Until that day comes, I wouldn’t worry. People underestimate the amount of data cutting / analysis Partners want before going to IC (who also demand associate double check figures, so won’t fully trust AI)
Chatgpt is meh but Claude is different. You can dump excels in there and it can cut data much faster than you normally do. At this stage I think it takes more time for me to teach it to build a complex model vs. me doing it myself - but frankly it is just a matter of time until they learn so fast that they can be a better version of us.
my friend, you have never obviously used Claude Code or Cursor
"The alpha in PE has been patched, it’s not the same environment that made KKR successful in the 80’s..."
I would argue this has as much to do with the UMM/MF firms being so larger as it does competition in the space. Once you get to a certain size, you basically become the market. Once you are the market, you are pretty much stuck with market returns.
Remember the deal sizes that KKR started with. Those deal sizes in today's market are very much MM. Hell, many of their best deals from that time would be solidly LMM. Look at the top firms in that space. They are still generating good returns.
It is absolutely much harder to make your return in PE today than back in the 1980s. That's what happens when an industry matures. But you can find similar shops to the KKR of the 1980s today. It is just not the "easy" or "popular" path. Just like how Kravis and co. starting KKR wasn't an "easy" or "popular" path.
People here are so fucking delusional. Frontier models can already work for hours at end. Albeit mostly in coding domain for now. But they can also do reasoning and models being released these days can solve IMO questions in just 30-40 minutes. Reasoning and mastery in coding domain is also what you need to build better and better models and eventually master all other domains (including finance). It's a matter of 1-2 years before juniors and industry professionals are being laid off en masse.
You outed yourself that you don’t even understand what “reasoning” is. LLMs do not “reason”, meaning they cannot “understand” you, they can ingest your words, their syntax, the syntax and words from the documents you share and because humans are more predictable in many cases — the frontier models can predict the next string of words to reply to you in a coherent paragraph.
Language production does not come from reason, we reason and understand - and then have developed language to communicate that understanding efficiently. The LLMs mimic reasoning (as in its only one element of human cognition: statistical pattern recognition from language) because they’ve ingested so much of the world’s language, they are the best pattern matchers in the world so the responses are pretty damn close —but they don’t naturally, continuously “learn” on their own like humans do outside of the very expensive training window + later training periods (Ex: RLHF, RLAIF). They *have* to be “prompted” to do anything, and every action for them has to be somewhat explicitly programmed (trained) - which takes quite literally, hundreds of billions of dollars across the industry. I can have an analyst look over my shoulder for 30 minutes and they can reproduce a product with 95% accuracy. I cannot turn on my AI screen recorder, turn on my mic and do the same thing and the AI produces what I need - the process to input context or whatever into LLMs is really fucking laborious.
It’s a good thing that an analyst only costs $200k / year accounting for all compensation and benefits, they “learn” much faster, don’t need as much handholding, and have a natural 2000 year edge to learn quicker than a LLM: fear of losing a job, and therefore not being able to satisfy your basic needs is Darwinism at its finest. “Get this right or you’re fired” always yields a better one-shot response from a human than from a soulless LLM.
The current frontier has a compute-maximization first approach that is showing diminishing returns at an extraordinary cost. Meta’s “Coconut” model is some of the earliest innings of pivoting the approach to a “Reason 1st” model that performs best on dramatically smaller scales of data - this is still very experimental but the findings here may end up being compelling. If it becomes clear that this methodology is better for development, the entire bubble can, in theory, pop from the ridiculous amounts of overspending done so far. The TLDR is: Large Language Models alone will not produce AGI, and AGI is essentially proof that the model can “Reason” as organically as a human. Humans learn not only from language, but from sight, hearing, experiencing, evolutionary biology etc. which are all avenues models are cannot mimic.
I lecture you to say this: stop being a fucking sheep regurgitating the doomerism talking points of AI company management teams. You’re a smart boy, read the research papers yourself and ingest different opinions from leaders across AI, cognitive neuroscience, hell even the researchers who’ve moved onto “World Models” to understand what this current wave of AI can and cannot do.
Our $160k jobs are just fine and if you fucking lose yours in the next 12-18 months it was because you’re an abject low performer who didn’t make the cut, not because “wahhh the AI God took my job :(“. Remember there’s hundreds of thousands of offshore jobs in foreign countries up first, and they’re still even having a hard time automating them entirely fast enough.
This isn’t an “old man shakes fist at cloud” or “luddite” response either, we will all need to update our priors to stay competitive vs. the work AI can figure out how to do - but if you let AI catch up to the neuroplastic brain God gave you, you’re a fucking idiot who stood still so the AI machine could catch it, which is fundamentally a personal problem.
This is an elite response that everyone should read. Thank you.
I’m genuinely confused what the obsession with AI eliminating junior roles is. It genuinely seems like people on WSO and just in general have begun manifesting it in a sense. Which I really don’t understand. Aren’t most of these people in the same careers and roles that they’re saying are going to be cut? Like, do these people want to get replaced by Ai? I think there is an unidentified fetish of oneself being replaced by Ai.
.
All I can say is you have such strong views it’s blinded you to the progress since January. Try out any of the harness frameworks that have been developed. OpenClaw, give it a try
It does learn, not by training or finetuning but by delivering work product, getting feedback from a human, committing that to memory in plaintext natural language. We have replaced large portion of the work you raise iteratively teaching it like an intern. Unlike an intern, it can package what it has learned as a skill which you can directly copy over to another agent.
The frontier is moving so quickly that unfortunately intelligence and being well read like you are means that you are behind. You really have to try it for yourself. Do that before forming such strong opinions
You can choose to believe it or not, but while my firm is way ahead of others on this, we are only a quarter or two earlier to this realization. The pace of progress has been that dramatic. I have no doubt that 2026 is when it’s widely recognized that the white collar singularity is here
You understand that most coding applications of LLMs address questions that effectively have closed-form answers, right? That is a fundamentally different class of questions.
The least you can do is be honest in your analysis.
How does that change my analysis at all? Coding ≠ Finance. Coding is only ~80 years old while finance is over 5,000 years old.
I don’t think it’s rocket science to see which horse to bet on for longevity. Now obviously this isn’t as fair because coding ≠ all of engineering, which is something AI also can’t do today, and maybe that’s the more apples to apples comparison, but again LLMs will never be able to do many forms of engineering completely autonomously by nature of observation being done through all 5 senses.
Aren’t you basically confirming that coding doesn’t require as much human reasoning as tech bros posture it to be - which is why LLMs are so apocalyptic for their careers?
[duplicate. Please see previous response]
Do you tech bros ever tire of spewing your marketing nonsense on this site
No they don’t. There is no group of people currently more insufferable than Ai tech bros.
Theoretically speaking, if analyst level and associate level positions are cut out, where do new VPs and partners come from? I mean eventually younger people will just start their own firms with Ai assisting them - leading to more competition (even if they lack the experience). Curious to hear what people think about this. I’m speaking regarding the general economy and financial services sector.
The real bottleneck to starting your own fund is fundraising (something AI can't assist with), not lack of analysis ability
I meant lack of experience as in lack of management and general seniority experience that can be beneficial when starting your own fund. In terms of fundraising- yeah that would be the hardest part. But again, I’d so many associates get laid off - what exactly do you expect them to do or where do you expect them to go?
you are talking as if all 10 associates from the same class will get promoted to VPs... instead of hiring 10 they can save cost and just hire 3-5 of the brightest and raise them to be the next gen of leaders.
I’m not sure if this was in response to my comment - but if it was, I’m not saying that all of the associates get promoted to VP or Partner. But, I mean, they’re going to go do something else for work. Possibly, as I mentioned, start their own thing. Or move to a company that isn’t downsizing. Either way, this can just lead to more competition in the market.
What exactly should happen if Ai eliminates most entry level work? Do you really think that most of these people will just say “Ah fuck it - let’s just not do anything and end our careers here”? There would be strong regulations imposed on AI, sanctions against certain companies/industries eventually, or some sort of compensation from the government if too many people are out of work.
Incompetent managers will force it into their organization which will lead to layoffs and inferior performance.
Putting in my two cents here. My firm recently implemented Claude and, so far, it performs materially better than OpenAI when working in Excel and PowerPoint. When it comes to language and general reasoning, however, OpenAI still appears to lead the market. I also know someone working at a startup focused on training models that will eventually be capable of building full financial models autonomously. Their approach is essentially to train the models until failure. The model is pushed to complete complex tasks, for example constructing an LBO, and when it reaches a bottleneck or produces an incorrect output, the person prompting it, typically someone with real investment experience, identifies the precise point of failure. The startup then develops a solution for that specific instance, retrains the system, and the process repeats. Over time this creates a compounding improvement cycle. Given the pace of development, I have little doubt that within five years these models will be extremely sophisticated. There will be less hiring at the lower levels and the mid-levels that can’t adjust to AI will get fired. The guys training these models are top dogs. Think ex: HF, MF, Quants, etc.
That sounds like it's just RLHF? That's happening at every major AI company right now and some massive businesses have been built super quickly to provide this service (Scale AI, Mercor, Handshake, Surge AI, etc).
Putting it loosely under RLHF is fair, but what they’re doing is a bit more specialized. The feedback loop is being driven by people with actual investment and modeling experience who are pushing the system through real financial tasks until it breaks, for example building an LBO, linking statements, or handling edge cases in a model. When the model fails, they isolate the exact failure point and train specifically around that bottleneck.
So the feedback isn’t just general preference alignment. It’s domain-specific correction tied to real workflows in finance. Over time that creates a very dense dataset around how financial models are actually constructed.
My view is that once enough of those edge cases are solved, you end up with systems that can produce fairly sophisticated models end-to-end. At that point the value shifts from mechanical model building to judgment, interpretation, and capital allocation.
I think there is a lot of junior level cope in here (understandably) - I can give a frame a reference as the group head & owner of hiring plan.
The high level summary is: we are trying to remove the need of all analyst/associate work almost entirely, and run our teams with VP/Principals primarily, using automation layers for data analysis and aggregation. Of course this requires a ton of AB testing and continuous iterations, but our end state would be a team of Partners and mid-level, outsourcing all heavy lift deal work to third party providers or within AI tools (likely a combo for a couple years).
Nice LARPing dude - your post history shows you couldn’t get VP promotion 3 years ago and then 8 months ago posted a comment saying your peers are “VP/Principal”. Slow day huh? Yea for sure LLM will definitely not make any mistakes and VPs should get in the weeds rather than sourcing new investment through more networking, negotiating legal docs, etc.
He's the group head, man. Out here posting on WSO.
Ah yes, the Associate who is so well versed in the VP>Principal>MD career trajectory.
Damn, the salty response is all-time lol. You do you buddy, just giving a perspective that is shared amongst my peer set and in my own firm. If anyone understands the junior to mid-level scope better, its me exactly because of the 3 years ago - the need for armies of juniors is fading. I'm fortunate to have ended up in the perfect role that lead to an executive position, pure luck - but you my friend, you are fucked.
Surreal levels of cope in this thread lmao holy hell didn't realize you guys had your heads so far up your a**es
Gonna be a rough few years
I don't know man. It's obvious that it's gonna change the team structure probably with smaller analyst classes but making predictions about how there's gonna be no analysts/assocs in 1 year is also kinda optimistic. When ChatGPT came out people where claiming its over in 6 months and im hearing that every two weeks again for the past 3 years. Maybe we underestimate that jobs are more complex than we think even if they only consist of putting bs together? Many here make predictions about the systems without knowing the slightest about them and their limitations. Nobody can predict the future but I would guess its like always in history we underestimate the impact in long term and way overestimate in short term
Something that keeps getting glossed over in these threads is the training pipeline problem. Everyone's debating whether AI eliminates the analyst seat, but nobody's asking what happens to your VP bench in 7 years if it does.
The grunt work that people want to automate (spreading comps, building the initial model, grinding through CIMs at 2am) is also the work that teaches you how to spot when something's off. That intuition partners rely on when they push back in IC didn't come from nowhere. It came from years of manually building the muscle memory of what "normal" looks like in a revenue bridge or an EBITDA adjustment.
I've seen firms go heavy on automation for portfolio reporting and board pack generation. The output quality is fine. But about 18 months in, the associates on those teams started having real trouble doing any independent analysis when they rotated onto deal teams. They could operate the tools but couldn't tell you when the tools were wrong.
The firms doing this well aren't eliminating junior roles. They're restructuring them so the AI handles the mechanical stuff while the analyst still has to understand and validate the output. That takes longer to implement and it's way less sexy than "we cut headcount 40%," but it's the only approach I've seen that doesn't quietly hollow out your talent development.
What exactly does a VP do today? Mostly coordinate emails between different 3rd parties, keep the process “on track”, check work. Of those three things, only one is not replaceable by AI in 6-12 months. All three will be in the end state. If you disagree, then you aren’t staying up to date with the leading edge of capabilities.
Yep, I argue AI is already very capable if set up right. There's just different stages of replacement.
The discourse here is wrong I think. Analysts / Associates are probably best positioned to take advantage of AI. The ppl who will struggle are going to be the millennial VPs who are a little too far away from being partner. 1) PE industry is shrinking, 2) partner promotions are far harder to come by at a firm that’s not growing AUM unless someone leaves (ppl leave less often if the industry is not growing) and 3) most VPs / Directors only know how to do the one thing. Riding an interest rate cycle to the lows.
If you are under 30, spend your free time learning how to use the AI tools & the fundamentals to check your work. Wherever the world ends up in 5 years, you’ll be in a good spot to take advantage of the new industries & opportunities that pop up.
I have a hard time believing the 33-38 y/o VPs, Directors, Principals are hungry enough to figure it out. Partly because you look and sound crazy as an AI fanatic. By this age / stage of life & a decade of living in NYC, their self-identity won’t let them change. If you aren’t willing to make a few mistakes & look a little foolish, you have no chance in adapting to a world that’s changing every month. The 21st century started in 2023. Decades are happening in 2025. Don’t fall asleep at the wheel.
Lol at your premise that "VPs won't know how to figure it out". We are talking about a technology that has an incredibly simple user interface and literally figures it out for you. "Claude, here's some financials, make me a model". Every mid-level I know is a Claude power user. They've already "figured it out".
I highly doubt it. Using Claude for Google Search =/= power user.
Answers to this question will depend heavily on group dynamics.
In my group, Associates are on a finite timeline. We have more than enough Junior Director talent who is capable of managing AI output. We also don't have much of a "pyramid" structure which in recent years I'm beginning to think may be by design.
i think we will all be replaced. check out IB Copilot AI. Does everything for you from almost nothing.
Been using Claude heavily in live deal work for the past few months. The biggest shift isn't replacing people — it's compressing timelines. A 3-week diligence workstream now takes 10 days because you can draft diligence question lists, summarize data rooms, and build first-pass memos in a fraction of the time. Where it genuinely changes team structure is at the junior level. You need fewer bodies doing the grunt work, but the associates who know how to use AI effectively become 3x more productive than those who don't. The skill gap between AI-literate and AI-illiterate juniors is already massive and it's only getting wider. My advice to anyone early in their PE career: learn to prompt engineer for deal work. It's the single highest-ROI skill you can develop right now.
Interesting question — I don’t think AI like Claude fully replaces analysts/associates, but it definitely changes what they do. A lot of the grunt work (data scraping, first-pass diligence, basic models) gets automated, so juniors become more focused on judgment, storytelling, and actually understanding the business, not just building slides.
Feels more like team compression than elimination — leaner teams, faster timelines. The real edge will be knowing what to ask AI and how to validate it.
I’ve seen a similar shift using tools like Phonexa — automation handles the heavy lifting, but the value still comes from how people interpret and act on the data.
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