If you’re in private equity, you have a well-oiled machine for value creation. You pull the levers of financial engineering, operational improvements, and strategic M&A with ruthless efficiency. Now, there’s a powerful new lever to pull, one with the potential to multiply EBITDA across your entire portfolio: artificial intelligence.
But let’s be honest. For many PE professionals, AI feels more like a risky venture capital bet than a disciplined value creation tool. It seems messy, speculative, and full of hype.
This view misses the real opportunity. When you strip away the hype and apply it with the same operational rigor you bring to everything else, AI isn’t a speculative bet. It’s a powerful tool for driving efficiency, making smarter decisions, and de-risking your investments. For the modern PE firm, a clear, repeatable AI playbook is no longer a “nice to have.” It’s a critical tool for generating alpha in a competitive market.
The Thesis: AI as an EBITDA Multiplier
An AI strategy for a portco has to be grounded in one thing: driving measurable financial results. This isn’t about “innovation theater.” It’s about deploying AI in ways that directly and quickly impact the bottom line.
The smartest approach is to focus on a few high-impact use cases with a proven ROI:
- Back-Office Automation: This is the low-hanging fruit. Use Intelligent Process Automation (IPA) to streamline finance, HR, and admin functions. This delivers fast, significant cost reductions and an immediate margin improvement.
- Predictive Analytics in Operations: For your manufacturing or distribution companies, implement AI for demand forecasting and predictive maintenance. More accurate forecasts reduce costly inventory, and predictive maintenance cuts downtime. Both go straight to cash flow.
- Dynamic Pricing for SaaS & Retail: For your software or retail portcos, AI-driven dynamic pricing can boost revenue by 20% or more. And we know that SaaS products with embedded AI features can command price premiums of 27% or higher.
By focusing on these proven plays, you can treat AI as a reliable EBITDA multiplier, not a science project.
The Playbook: A Repeatable Framework for Your Portcos
To scale the benefits of AI, you need a standardized playbook you can run at every company in your portfolio. This ensures a disciplined approach and creates a powerful learning loop across your firm.
- The AI Readiness Assessment (First 60 Days): During diligence or the first 60 days post-acquisition, run a quick AI readiness check. How good is their data? What’s their tech stack look like? Are the people ready for change? The goal is to quickly identify 2-3 “quick win” AI opportunities.
- The “Quick Win” Pilot (Months 2-6): Launch a tightly scoped pilot project focused on one of the identified quick wins. The key is to choose a project with a high likelihood of success and a clear, measurable KPI. Success here builds momentum and creates internal champions for the broader AI strategy.
- Build the Security and Governance Guardrails: From the outset, implement a strong security and governance framework for AI. This includes clear policies on data security, privacy, and ethical use. For your portcos in regulated industries, this is non-negotiable and requires a focus on explainable, auditable AI . This de-risks the implementation and protects the firm and the portfolio company from potential liabilities.
- Scale and Share the Learnings (Months 6-18): Once the pilot has proven its value, develop a plan to scale the solution across the organization. Simultaneously, document the process, the challenges, and the results, and share these learnings across the entire PE firm’s portfolio. This creates a powerful knowledge-sharing flywheel that accelerates adoption and value creation at all portfolio companies.
De-Risking Your Own Deals: AI for Better Diligence
Beyond driving value in existing portfolio companies, PE firms can also leverage AI to improve their own investment processes. AI-powered analytics can supercharge the due diligence process, allowing firms to:
- Analyze vast datasets on target companies to identify hidden risks or opportunities that might be missed in a manual review.
- Conduct more accurate market analysis by scraping and analyzing data on competitors, customer sentiment, and market trends.
- Model future performance with greater accuracy using predictive analytics.
By integrating AI into the diligence process, a PE firm can make smarter, more data-driven investment decisions, improving the overall quality and performance of its portfolio.
Conclusion: The New Frontier of Value Creation
For the private equity industry, AI represents a new frontier of value creation. It offers a powerful set of tools to drive operational efficiency, accelerate revenue growth, and mitigate risk. The firms that succeed will be those that move beyond a speculative mindset and develop a disciplined, repeatable playbook for deploying AI across their portfolios. By treating AI as a core component of the value creation process, PE firms can unlock significant returns and build more resilient, more profitable, and more valuable companies.
To see how we’re putting these ideas into practice, learn more about Chiri’s approach.