Leaving PE for AI
Has anyone here left the IB/PE world to go join tech, specifically in AI? Would love to hear if anyone has any experience. Seems like the AI world is at a huge turning point, while the PE industry is slowing down / facing headwinds.
I have been thinking the exact same thing. I see Hebbia is full of ex PE/IB professionals
Not me, but have a college buddy who left to go chase the AI startup world. Doesn’t seem to be the easiest path but seems rewarding. Probably one of the biggest markets hiding in plain sight - people know it’s going to be a massive opportunity, and we always talk about it, but no one from finance really seems to be jumping at it?
Considering making the transition myself but finding some issues with semi-golden handcuffs. Tail end outcomes in AI seem much more attractive, but being middle of the fairway might be worse off?
I’ve seen some investors with alarmingly strong investment backgrounds going to work at places like OpenAI
Haven’t seen that myself but not surprised. Heard OpenAI comp is quite strong, even compared against top PE/HF shops
What kind of roles for finance folks are there in AI? Ultra lean FP&A Director functions? corpdev/strategy? Interested in knowing how finance fits into the picture with a market that is seemingly hard-nosed machine learning / coding
Exactly this?^
Also capital markets roles to support capital raise activities for data centers
Know someone from BXPE that went to an AI platform like Open AI. I was thinking of asking him and see why he made the move.
I know who this is too lmao
ScaleAI?
What did they say?
Would be interesting to get an insight into how the platforms that are trying to compete in the space Harvey, Hebbia, Rogo, Keye, Capsa, ModelML (and whatever else I’ve missed out 😊) all stack up against each other.
It seems like they all lead with their huge marquee clients (as you would expect) but there is no insights into 1) the actual workflows that there helping with (just information retrieval and storage like a typical LLM) 2) what the retention rate is and whether funds are just trialling different software 3) what the satisfaction is (nps)
None of the interviews I’ve seen have actually been able to test founders because they don’t come from a PE / HF / Legal background. So they really don’t know the important workflows
Bump.
Also wondering about how to transition to AI
There is an apollo associate who left last month to become a software engineer of an ai startup apparently.
Very interesting anecdote. But also there are tons of software engineer in the market already...
I know this is a very high level discussion on the potential transition but if you don’t have any technical background, definitely do your research on the difference between companies like Open AI building both foundational models and applications vs companies like Hebbia which essentially sit at the application layer and are wrappers for underlying technology built by other companies. Both may be successful in the long term but “success” looks a lot different.
I’m personally someone that’s in the camp of this being the same level of excitement around the internet in the early 2000s. AI will be transformational, but there will be winners and losers like in everything.
Will you stay in PE or move? If so, to where?
Yes, debating between chief or start role at a private company or analyst role at a notable Tiger spin out doing publics, Both would be a step down from current all in PE comp which sucks but would be much better work life balance. I’ve enjoyed PE but just feel like I’m in a well paid corp dev role with the insanely long promotion timelines at my firm. Would kill for a role at one of the big AI startups but those jobs feel impossible to land even from a top finance background
There's an old Buffett adage from back during the airline boom that just because there's a lot of innovation and value being created in a sector doesn't mean there's going to be a lot of value capture. There's a ton of exciting stuff going on in AI for sure, but I think the # of companies being started and getting VC $$$ is not representative of how many "good" places there are actually available. OpenAI, Grok, Gemini, all for sure great places to work given the scale and businesses they've built, but I've looked at a number of BD/strategy opportunities for other companies in the space and not gotten the same vibes (and a few have already been made obsolete by new releases from the aforementioned foundation cos).
This isn't to say don't do this, but be very thoughtful about where you leave for and think about what's going to give them staying power. "Moats" can erode much quicker in this sector than I think any other given the pace of change. It sure would suck to leave for a place you thought was the next Microsoft and instead be left holding equity in AI's equivalent of IBM.
This. OpenAI can release a single feature and render a hot startup obsolete. Tread carefully.
OpenAI's agent day reveal was a bloodbath for this exact reason.
Saw this thread got bumped. Hilarious because OpenAI just did it AGAIN and nuked half the high flying AI agent workflow startups that raised a bunch over the last 6-9mos. What a world.
What can finance people do to break into AI besides studying coding from the beginning??
Delete
I left PE in the last couple of years and am now working as a data scientist but still within financial services, though I appreciate you may be specifically referring to those working at the frontier AI labs.
For business/customer facing roles at these firms, as they pivot towards commercialising their products and services they are hiring more sales personnel (less relevant for IB/PE) and customer success managers which can be a way in.
What process did you undergo to upskill to a data scientist? And how do think about long term earnings relative to PE?
I had a STEM background from college so was familiar with concepts and ideas but my coding ability needed work. I (quite naively) underestimated how tough the hiring market was and so quit my role and took a while off to practice, build projects etc.
My PE background helped me a lot in getting my current role as I was viewed as someone who could understand business needs, communicate and present well while also being able to do the DS work.
Earnings potential is a tough one. In the short term I would earn way more in PE (not including investing the bonus etc) but the promotion pathway was foggy and I wasn't thrilled about the wlb. Long term, if my plans pan out I think the DS route could potentially pay me more while also being more fulfilling, as I genuinely love the problem solving and analysis.
Would you mind sharing what your day to day looks like? And did your interview prep involve mostly leetcode?
The day-to-day varies depending on if we are on a deployment or not but overall we have a very 'techy' culture.
A deployment is an engagement of varying length with one of our portco's where we will be delivering a pre-defined data science or analytics project linked to an identified lever we are trying to pull. In between deployments we do in-house data science and engineering work to improve our internal tools & processes.
Once on deployment consist of 3-4 people including a deployment manager and then data scientists / engineers. We have daily stand ups to see what everyone is doing & check progress toward goals and the rest of the time is pretty focused on delivering the project. We will also do biweekly meetings with portco exec teams to update on our progress.
Hours are 9-5 mostly which is great.
On interview prep, it depended on the role I interviewed for. PE firms didn't hand out leetcode but instead gave take-home DS assessments which I found more fun. I did prep leetcode for a few hedge fund DS roles though.
I looked at doing this and unfortunately you are working in sales at most of these “ai for finance” companies. Basically what I did was try to start something myself as an engineer - self teaching myself everything. Then now I am hopefully going to cofounder something that overcomes the issues. I interviewed at all these “ai for finance” firms and frankly they are selling office furniture or art sort of — it just makes the company look good to have good furniture but they don’t actually use the ai products. My own suggestion is to work for the ai labs directly. My own view is that none of these enterprise software companies selling into financial firms will really do something transformative except maybe for a slight compliance reason. The labs themselves are the only place that anything interesting is happening.
I completely agree - this is also my view.
I've seen a handful of unicorn growth / stratfin folks at AI companies that have IB / PE backgrounds.
Care posting some LinkedIns or at least job title names?
Bump
The better question is: where does your finance / investing background actually create an edge inside an AI company? For PE/IB people, that is probably not core ML research. It is more likely corp dev, strategic finance, business ops, GTM strategy, partnerships.
I made a similar jump myself last year after 10 years in MBB. I hesitated for a long time because the golden handcuffs are real, and giving up a prestigious, high-paying path feels irrational on paper. In hindsight it was absolutely the right decision. The biggest surprise was not just comp, but comp per hour / stress-adjusted comp. In my case I’m effectively making MD-level money per hour.
That said, I’d be very picky on company. “AI” is not one asset class. Foundation lab, infra company, vertical AI app, workflow wrapper, AI-enabled services business, and random SaaS company with “AI” in the pitch deck are very different bets. Some will be incredible places to work, some will suck.
I’ve been writing about my own consulting-to-tech transition - you can find link in my signature.
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