Why PE Firms Need an AI Strategy

McKinsey &. Co. found that institutional investors who effectively deploy AI and technology could achieve a tenfold ROI across three areas: investment performance, operational efficiency, and risk management.

Despite this, many private equity (PE) firms remain on the sidelines. While waiting to see how AI develops seems like a safer bet, lost time presents a critical competitive risk. Winning portfolios are moving quickly and executing on real, impact-forward AI initiatives now—not waiting to see where the chips fall.

Why Implementation Matters Now

AI adoption has accelerated over the first quarter of 2026, and current options outpace what was available not only two years, but two months ago, as well. Tools are more accessible, use cases are clearer, and expectations have shifted.

According to a late 2025 survey conducted by PwC, half of PE respondents expect generative and agentic AI to be the most transformative forces in the industry over the next three years. 54% also claimed that these technologies were their top investment priorities in 2026.  More PE companies are integrating AI into their value-creation systems, resetting the baseline for what “competitive” means.

The signal is clear: firms are committing capital and taking action. Those that move early have time to refine their strategies, build capabilities, and scale successful initiatives. Those who wait will inherit compressed timelines, rushed execution, and lower returns on the same tools.

Where AI Is Delivering Results

AI is proving most effective as a tool to support, not replace, human teams across industries. In PE, that means faster pattern recognition, tighter operational control, and decisions based on forward signals rather than lagging data.

“AI is fundamentally reshaping how private equity firms evaluate opportunity,” says Christian Davis, Associate Partner of the global consultancy JMAN Group. “Predictive analytics allows investors to move beyond backward-looking financials and instead model performance scenarios based on thousands of real-world variables.”

A private equity firm can use AI to manage:

1. Operational Efficiency: Reducing execution drag across reporting, monitoring, and transaction workflows.
2. Portfolio Performance: Surfacing growth levers and tracking KPIs in near real time.
3. Deal Evaluation: Pressure-testing deals with forward-looking data, not static snapshots.

While human governance will always be necessary to catch hallucinations and verify insights, these applications allow firms to move faster, replicate successful interventions across portfolio companies, and make more informed investment decisions.

How Firms Are Approaching AI Adoption

Most firms fall into two traps: they either pilot too narrowly to generate real impact, or they overextend without the infrastructure to support it. In both cases, momentum stalls, either because results are too small to matter or too inconsistent to scale.

The default starting point—repetitive, data-heavy tasks—makes sense on paper, but often fails to build a case for broader adoption. Efficiency gains alone rarely justify continued investment, and without a clear path to portfolio-level impact, these initiatives plateau quickly.

Goldman Sachs Asset Management is one such firm. After deploying generative AI assistants, the company enabled relationship managers to achieve a 30% increase in client outreach efficiency through their “next-best-action” tools. Its internal AI tools also improved productivity by automating tasks such as document summarization and knowledge retrieval, allowing teams to spend more time on complex work. 

What’s different in cases like this isn’t the tool; it’s the clarity of where AI drives measurable outcomes. Studies show that roughly 80% of generative AI initiatives fail due to poor data quality, unclear expectations, or misaligned teams. Without proper preparation, the solution can produce flawed outputs, frustrate users, or fail to deliver any meaningful results.

The firms that break through treat AI less like a tool rollout and more like an operational capability, deployed where it directly impacts portfolio performance, not just internal efficiency.

A Smarter Way to Get Started

AI can unlock significant value for PE firms, but the key to success is knowing where to begin. Without guidance, even promising tools can be difficult to implement effectively.

At FullStack, we help firms move forward with confidence. We assess readiness, fix the blockers (data, process, alignment), and deploy where impact is immediate. From there, we design and implement solutions that fit seamlessly with your operations—helping you capture value quickly while setting up long-term success.

Spend less time planning and more time compounding value.

Ready to start building your roadmap? Learn more about our AI maturity assessments and LP-ready reporting just for PE firms.