Agentic AI Use Cases
If you were to rearchitect a PE firm’s workflow and structure from scratch, what would that look like?
The work streams that can be augmented, the menial busywork that can be avoided, the areas where today’s tools have clear utility, the places where you hope tomorrow’s tools can improve enough to address?
More than a thought exercise, seems right time to have to rethink what the firm looks like and as a result who to hire.
Just to get started because much of the discourse seems focused on “I am a better Excel jockey than Claude”…
DD
Legal - coc clauses, leveraged finance gotchas
Data room - completeness scan
Modeling
Scenario analysis - hybrid approach, Excel for quick definition but quantitative scenario construction
Paperwork
IC memo - this is well understood
Negotiation
Counterparty profiles, historical terms database
Relationship Mapping
Individual profiles, connections, interests, public speeches/persona snapshots
Industry analysis
Export/import data integration with qualitative analysis, overall bull bear analyst research survey
Sentiment
Analyst, public, reddit/forums,
Tax
Standard checklist
Cross border multi jurisdiction issue summaries
Portfolio management
Streamlined data collection (lets be honest, we are chasing financials and operating metrics every quarter )
Immediate benchmarking against comps, macro, rest of portfolio
Fundraising
Continual news flow summary of public pension disclosures, developments at key LPs/targets, new terms trends directions from industry event agenda, media
Also relationship mapping
That’s largely been what I’ve been using it for. On a personal work management level, it’s helpful when linked up to email. Very useful for summarizing a to-do list / keeping up with email. Also way better than outlooks native search function.
Solid list. Where I'd be more cautious is the DD and negotiation items. AI can surface and summarize, absolutely. But the value in DD is in the gaps, what's missing from the data room, where management's narrative doesn't square with the numbers. That still needs human judgment and probably will for a while. The risk is building a workflow where junior people start trusting the AI summary instead of developing their own instinct for when something smells off.
The firms getting real traction are picking two or three of these, getting them working well enough that the team actually relies on them, then expanding. Not trying to build the full stack on day one.
Which two or three areas do you prioritize? Which firms are ahead of the curve?
As always, it depends. But generally portfolio monitoring is the easiest win. Most firms are already chasing quarterly financials manually, so the pain is obvious and the bar is low. Even a basic setup that pulls portco data into a consistent format and flags when something looks off saves a ton of time.
Then IC memo prep or deal screening. Not because AI writes a great memo, but because it handles 60-70% of the factual assembly (market sizing, comp transactions, financial summary) so the deal team can focus on actual thinking.
As for who's ahead, arguably nobody's ahead in a meaningful sense yet. The whole industry is still early enough that any firm that commits to this seriously for 6-12 months can catch up to whoever's furthest along. That said, the firms making real progress tend to share a few traits e.g. they picked one or two workflows instead of trying to boil the ocean, and have at least one partner who actually uses the tools themselves.
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