What Happens When You Apply AI with a Private-Equity Mindset

Private equity has long been about spotting undervalued assets, optimizing operations, and compounding value over time. Now imagine applying that same mindset to AI adoption. The thesis is simple: buy established, “boring” businesses and use AI to make them run better.

At first glance, that might not sound revolutionary. But consider how most small-to-mid-sized businesses actually operate. Many still rely on spreadsheets, manual processes, and a patchwork of outdated tools. In that environment, AI isn’t a futuristic add-on—it’s a leap forward.

Three Ways AI Creates Value in “Boring” Businesses

1. Automate Incrementally, Not All at Once

Instead of trying to overhaul entire workflows overnight, focus on 10–20% at a time. Automating even small portions of a process creates immediate wins—savings in time, fewer errors, faster outputs. Over time, those singles and doubles add up to a transformed operation.

For example:

• Automating invoice reconciliation before tackling the entire finance stack.

• Streamlining customer support responses before building a full AI service desk.

This lowers risk and builds trust with teams, while compounding value steadily.

2. Build Micro-Solutions, Not Generic SaaS

Traditional software adoption meant waiting for the right SaaS product to solve your need—or bending your workflow to fit someone else’s template. AI changes that equation.

Now, companies can build lightweight, tailored solutions to match their exact process.

• A custom model for analyzing niche industry documents.

• An AI agent designed around a company’s specific sales funnel.

• Automations trained on proprietary data, not generic datasets.

The result: solutions that fit like a glove instead of forcing adaptation.

3. Rethink Incentives Through Outcomes

PE has always been about aligning incentives, and AI unlocks new models for doing so. With outcome-based pricing or even equity partnerships, efficiency gains don’t just benefit the client or the vendor—they benefit both.

This structure reduces friction, builds trust, and ensures AI adoption is tied directly to measurable business impact.

The Leapfrog Analogy: From Banking to Mobile Money

A helpful analogy comes from Kenya’s M-Pesa story.

In 2007, Safaricom launched a mobile-money platform that allowed people to transfer funds and pay bills without a bank account. At the time, Kenya lacked extensive landline or banking infrastructure. By skipping straight to mobile, M-Pesa leapfrogged an entire stage of development.

Today, M-Pesa serves more than two-thirds of Kenyan adults and processes roughly 31% of Kenya’s GDP.

The same leapfrog moment exists for “boring” businesses today. They don’t need to slog through a decade of SaaS rollouts and ERP upgrades. With AI, they can skip directly to modern, automated, insight-driven operations.

Why This Moment Matters

For many private-equity backed companies, this is an inflection point:

• The technology is mature enough for practical deployment.

• The value proposition is clear: lower costs, higher efficiency, better insights.

• The risk is manageable with incremental rollouts and aligned incentives.

The harder part is cultural. It requires the willingness to rethink how work gets done—challenging long-held processes, retraining teams, and making bold operational bets.

Closing Thought

AI applied with a private-equity mindset isn’t about hype or futuristic visions. It’s about taking solid, established businesses and unlocking hidden value through steady, strategic automation.

The leapfrog opportunity is here. The question is not whether the technology is ready—it is. The question is whether leaders are ready to rethink how work gets done.

Those who make the leap now will define the next generation of operational excellence.