When we talk to firms about their AI strategy, the question we hear most almost always starts the same way: “How are other firms…?” How are other firms using AI in sourcing? How are other firms handling their data? How are other firms getting their teams to actually use it?
It’s a fair question. If you’re going to invest time, money, and people into something new, you want to reduce as much risk as you can. Knowing what’s already working in the industry is one of the best ways to do that.
We don’t think there’s only one right way to do this. In fact, we think every firm should be doing it a little differently. Your sourcing model, your investment criteria, and the way your team works are part of your edge, and your AI should reflect them. Still, patterns are emerging, and they’re worth knowing.
There are strong use cases across every function at a PE firm, but this post focuses on the deal team. Private equity deal teams are using AI with their CRM data in three areas: deal sourcing and screening, document intelligence, and deal evaluation. The goal is less grunt work and faster screening, so the team spends its time on judgment instead of data entry.
What do deal teams actually want from AI?
Ask any VP, associate, or analyst where their week goes, and you’ll hear a familiar list: logging inbound deals, re-keying numbers from a CIM, cleaning up contacts after a conference. None of it is the work they were hired to do. When it falls behind, good deals sit in the inbox and the CRM stops reflecting reality. AI helps by taking on the repeatable steps, so the team gets to a decision faster, with better information in front of them.
What data does AI use for deal team work?
The most useful AI for deal teams starts with your CRM, because that’s where your firm’s history lives: every company you’ve looked at, every relationship, every deal you passed on and why. Off-the-shelf AI doesn’t know any of that. AI that runs on your CRM data does.
From there, the firms we work with layer in other sources:
- Data providers like PitchBook and Preqin for company, fund, and transaction data
- Public sources like news, filings, websites, and job postings
- Your firm’s tech stack, including email, document storage, and the other tools your team already uses
Put together, that gives AI the same picture your best analyst would build by hand, without the hours of pulling it together. It also means the output reflects how your firm thinks, not how a generic model thinks.
How are deal teams using AI for deal sourcing and screening?
Deal teams use AI to sort inbound deal flow faster and keep a closer eye on targets before they come to market. Three workflows stand out.
Screen inbound deals against investment criteria.
When a teaser or banker email comes in, AI tells you quickly which deals to advance, which to pass on, and which need a decision first. Each call is judged against your firm’s investment criteria and what your firm has actually closed, with the evidence behind it.
Maintain a pre-deal watchlist.
Many of the best deals come from companies you’ve tracked for years, but watchlists go stale fast. AI flags which companies are no longer realistic targets, which just changed hands or raised capital and deserve a call, and which are ready to become a deal.
Screen a target for red flags.
Before a deal goes to IC, AI checks for open questions about who you’re buying, who you’re buying from, and what it would join. It also shows whether the numbers look out of line with similar deals your firm has seen. Each finding says whether it’s confirmed or still a signal, where it came from, and who should close it out. It’s a first screen, not a replacement for formal diligence.
How are deal teams using AI for document intelligence?
Deal teams use AI to turn the documents they receive every day into clean, structured data in their CRM, without re-keying it by hand. Three workflows come up again and again.
Turn any document into a record.
A teaser, term sheet, NDA, or engagement letter holds most of what you need to log a deal. AI reads it and maps the details to the right places in your CRM.
Parse an attendee list into contacts and companies.
After a conference, the attendee list usually sits in someone’s inbox. AI matches everyone to existing contacts and companies, adds the ones that are new, and links them all to the event. Follow-up can start right away, not weeks later.
Parse portfolio financials into KPIs.
Portfolio company financials arrive monthly, quarterly, and annually, in every format imaginable. AI turns them into structured KPI records in your CRM, so portfolio monitoring runs on data instead of PDFs.
How are deal teams using AI for deal evaluation?
Deal teams use AI to get a deal from first look to an informed discussion faster, with the groundwork already done. These are the workflows we see most.
Build a deal screening summary.
AI brings a deal’s profile, financials, funding structure, comparable deals, and decision history together on one page. It grades the price, size, margin, and funding against your firm’s thresholds and past closes, then ends with a clear screening call. The team walks into the discussion ready to decide.
Draft or validate a capital stack.
AI can draft a capital stack sized to the deal, with pricing shown, or review the stack already on record. Either way, it checks the structure against how your firm’s past deals were funded and against current market terms. Your team sees how much debt the deal can carry, what it will cost, and how much equity the firm needs to write.
Run a conflicts check from a record.
Before a deal moves forward, AI identifies every company and person tied to it, along with their affiliates, and checks them against your firm’s relationships, holdings, and live deals. Each party gets a clear call; anything that can’t be checked is flagged, and the results go to your compliance owner. It supports your conflicts process without replacing legal clearance.
We’ve built AI skills for these exact workflows
Every workflow in this post is already built as skills in the Monarch AI Skills Library. The library works with Claude and includes 78 skills (and counting) across 11 modules, covering the work deal, BD, IR, and operations teams do every week.
Here’s why that matters.
You don’t start from a blank page. Building AI skills one at a time takes real time, and building a full set for every function at a PE firm takes much longer. With the AI Skills Library, nearly all the skills your firm needs already exist. You start from a library, not from scratch.
You save on the cost of building. Developing a large set of skills quickly also takes a lot of tokens, and that cost adds up while you test and refine. Starting from a proven library means you spend those resources putting AI to work, not reinventing it.
It runs on your data. The skills run on your firm’s own CRM data, along with the data providers, public sources, and tools you already use.
It’s built around your firm. The library comes with a firm intake process your team completes. It captures your investment criteria, sourcing model, deal process, and how your team works. It also gives you the tools to customize the skills to match. The output reflects your firm’s approach and protects what makes it different.
The AI Skills Library is built and implemented by Monarch, an independent partner with 4,500+ projects across 1,500+ private capital firms and investment banks since 2018. We know the data model, the workflows, and the people behind them.
Frequently Asked Questions
- What is an AI skill? An AI skill is a ready-made workflow that handles a specific, repeatable task, like screening an inbound deal or turning a CIM into a CRM record. Unlike a general chatbot, a skill follows a defined process built for that job.
- Does the AI Skills Library only work with one CRM? No. The AI Skills Library is CRM-agnostic and runs on any CRM with an MCP server.
- Will AI replace my deal team? No. AI handles the repeatable steps, so your team can spend more time on judgment, relationships, and decisions. Your people still make the calls.
- What if our CRM data isn’t ready for AI? That’s a common starting point. The AI Skills Library includes a Data Quality & Migration module to help clean up and organize your data first. An AI readiness assessment can also show where your data stands and where to start.
- How is the AI Skills Library customized to our firm? The library includes a firm intake process that your team completes, covering your investment criteria, sourcing model, and deal process. It also gives you the tools to customize the skills yourself, so they fit how your firm works and your team stays in control of the setup.
See what the AI Skills Library can do for your deal team
Your CRM already holds what your team needs. The AI Skills Library puts it to work.
If you’re weighing how AI fits into your deal process, we’d be glad to walk you through the skills that match your team’s biggest time drains and show you what they look like on real workflows.
Talk to an expert about the Monarch AI Skills Library →
