How AI Is Reshaping Private Equity
Artificial intelligence is transforming how firms source deals, conduct diligence, and optimize operations. We examine the practical applications delivering real returns today—and separate hype from reality.
Every private equity firm claims to be "data-driven" and "technology-enabled." Most aren't. They use Excel for modeling, email for deal flow, and gut feel for most decisions. That's changing, but slowly.
AI is not magic. It's a set of tools that, when applied correctly, can accelerate deal sourcing, improve diligence, and optimize portfolio operations. The key phrase is "when applied correctly." Most AI projects in private equity fail because firms try to automate before they systematize.
Deal Sourcing: Finding Needles in Haystacks
The best deals never hit the market. They come from relationships, proprietary networks, or proactive outreach. But what if you could monitor thousands of potential targets simultaneously?
We've built systems that scrape public records, track business filings, monitor job postings, and analyze web traffic patterns. Machine learning models score companies based on growth signals, operational efficiency metrics, and acquisition readiness indicators.
Does this replace human judgment? No. It creates a shortlist of high-probability targets that a human team can evaluate. Instead of chasing every inbound pitch, we focus on proactive sourcing of companies that fit our criteria.
Due Diligence: Speed Without Sacrifice
Traditional diligence is slow. Teams spend weeks reviewing financial statements, contracts, customer lists, and operational reports. AI accelerates this without cutting corners.
Natural language processing extracts key terms from hundreds of contracts in minutes. Computer vision analyzes property condition from drone footage. Anomaly detection flags inconsistencies in financial data. The output isn't a "yes" or "no"—it's a prioritized list of items requiring human review.
This matters in competitive processes. The firm that can move fastest while maintaining diligence quality wins the deal. AI provides that edge.
Operations: Where Real Value Gets Created
Buying well is important. Operating well is essential. Most value creation happens post-acquisition through revenue growth and operational improvement.
AI-driven dashboards surface inefficiencies that management teams couldn't see. Predictive maintenance reduces downtime. Dynamic pricing maximizes revenue. Workflow automation eliminates waste. These aren't theoretical benefits—they're measurable improvements to EBITDA.
The firms that win in the next decade will be those that deploy technology across the entire investment lifecycle. Not as a buzzword, but as infrastructure.
What Doesn't Work
Most AI initiatives in private equity fail for predictable reasons:
- • Lack of clean data (garbage in, garbage out)
- • Trying to automate chaotic processes instead of systematizing first
- • Relying on vendors instead of building internal expertise
- • Treating AI as a replacement for judgment rather than an enhancement
The solution: start small, focus on high-impact use cases, and build technical literacy across the team. Technology should serve strategy, not the other way around.
Final Thoughts
AI won't replace private equity professionals. But professionals who use AI will replace those who don't. The competitive advantage goes to firms that build technology as core infrastructure, not peripheral tooling.
At Mossback & Co., we're building these systems from day one. Not because it's trendy, but because it compounds over time.
Have thoughts on this topic? We'd like to hear from you.
Get in Touch