At Cuesta Partners, after years of supporting PE firms with technology diligence and portfolio strategy, we have seen firsthand how investor perspectives on AI are evolving. Nearly all the mid-market PE firms we work with are actively thinking about AI, exploring use cases across their core business functions in deal sourcing, due diligence and portfolio management.
When it comes to their portfolio companies, PE firms’ views and strategies regarding AI depend heavily on the specific stage of the investment lifecycle. We have observed that the approach shifts from risk assessment and opportunity analysis during the buy-side phase to a focus on value creation and operational improvement during the hold period. In practice, we have begun to see tangible ROI from well-targeted AI initiatives, particularly those tied to analytics, automation, and data enablement. The early results suggest that firms willing to move beyond pilots and operationalize AI are already realizing measurable efficiency gains and portfolio impact.
Buy-Side: Assessing AI Risk and Opportunities
During the initial deal sourcing and due diligence phases, the primary view of AI often centers on identifying risks and opportunities that could impact the investment thesis.
- Disruption Analysis: While PE firms are increasingly focused on whether a target company’s business model is defensible against AI-driven disruption, this has not made them shy away from software investments. Even the software-focused PE firms we work with continue to double down on the sector – they are more carefully scrutinizing AI opportunities and threats.
- Lack of AI Strategy as a “Red Flag”: Companies that have not started evaluating AI integration, lack of the foundational data infrastructure to support it, or have limited decision-science capabilities are increasingly seen as facing “existential threats.”
- AI Due Diligence: Across the market, PE firms are now seeking a dedicated AI scope in traditional technology due diligence. Beyond assessing systems and architecture, investors are examining a target’s AI maturity, data integrity, and compliance readiness to gauge risk and value potential. This shift reflects a growing recognition that AI readiness is becoming as material to enterprise value as cybersecurity or data governance.
- Identifying Opportunities: Investors increasingly look for evidence that AI can reinforce the deal thesis, accelerate EBITDA growth, and strengthen the company’s competitive position post-acquisition. As part of due diligence, we are often asked to identify AI-driven growth opportunities and assess a target’s readiness to capture them. This includes examining how AI can enhance the company’s value proposition through operational efficiency, product innovation, or improved customer experience.
Hold Period: AI-Driven Value Creation and Growth
The traditional PE playbook for value creation is evolving. Historically centered on foundational initiatives like cost reduction and revenue uplift through operational efficiency and market expansion, the current landscape mandates a more dynamic, AI-integrated strategy. AI provides a force multiplier for existing levers and unlocks entirely new pathways to performance enhancement and EBITDA growth. Firms are moving beyond opportunity exploration and taking a structured approach to evaluate high-impact AI use cases. Developing an “AI Value Backlog” – a pipeline of AI initiatives used as an implementation roadmap – enables PE firms and portfolio operations teams to prioritize execution against the highest value-creating opportunities first. Moving swiftly into execution on these strategic projects is a key differentiator for firms seeking a competitive edge.
Where the Smart Money is Moving
Ultimately, AI adoption comes down to ROI. Our PE clients are typically aiming to realize value within 3 to 5 years, which means the AI initiatives attracting investment today are those that can demonstrate tangible financial impact, reducing cost per transaction, shortening cycle times, or boosting margins within the firm’s ownership period . This advantage is particularly pronounced in the mid-market. While enterprise-scale AI transformations often stall under complex governance structures and entrenched processes, mid-market organizations can move fast. Their leaner structures and flatter decision-making models make them ideal testbeds for applied AI, allowing PE-backed companies to pilot, iterate, and operationalize initiatives with agility. For investors, this translates into a structural edge: early AI adoption drives gains in operating leverage, data sophistication, and ultimately exit valuation. In other words, mid-market portfolio companies can not only capture near-term ROI but also build a technology-enabled growth engine that compounds value over the life of the investment.
At Cuesta, we have seen this firsthand. One logistics client implemented AI-driven dynamic pricing and transaction optimization, resulting in a 2% increase in gross margin per transaction which equates to a 10% lift in net margin. That kind of performance story resonates in both diligence and exit narratives. By contrast, generic chatbot deployments rarely survive the ROI test unless they deliver measurable savings or conversion gains.
While the degree of adoption varies depending on a confluence of factors from deal cycle, regulatory environment, portfolio maturity to data readiness and leadership appetite, the direction of travel is clear: AI is no longer at the periphery of the conversation. Whether assessing a target’s defensibility during diligence or accelerating value creation during the hold period, PE firms must intentionally decide how AI fits into their investment thesis. Those that embrace AI with discipline and strategic clarity will not only create more resilient portfolio companies but also set a new standard for value creation in the next decade.
What PE Firms Should Be Asking
As AI moves from buzzword to business imperative, mid-market PE firms must begin asking questions about how it fits into their investment strategy and value-creation playbook:
- Where can AI create defensibility?
Proprietary data, domain-specific models, and technology-enabled processes are fast becoming the new competitive moats. Understanding where AI strengthens a company’s core differentiation is critical to sustaining value. - Is AI an existential threat to the business model?
The most critical question is not if AI will disrupt legacy business models, but when. For many companies, failing to integrate AI into core operations is an existential risk that will become apparent over the next two to five years. PE firms must urgently assess whether a company’s current value proposition can survive against AI-native competitors that operate with a fundamentally lower cost structure and hyper-personalized offering. - How quickly can the impact be realized?
With a 3–5-year investment horizon, tangible ROI remains the north star for adoption and capital allocation. The most successful firms are proactively identifying use cases that deliver measurable financial outcomes within that window. - Is the portfolio ready to scale AI?
True value creation requires more than pilots. It demands strong data foundations, technical capability, and a culture that embraces experimentation and automation. Leadership alignment and team readiness will ultimately determine whether AI becomes a growth accelerator or a threat. - What AI investments should the firm avoid, and how is ROI ensured?
The temptation to chase the AI hype and deploy capital without a clear strategy is a major risk to value creation. Firms must avoid investments that look innovative but lack a credible business case, have no clear path to measurable ROI, or depend on data and process maturity the company simply does not have. The focus must be on a disciplined value backlog approach, prioritizing only those AI initiatives that show the highest commercial value and have a clear, measurable impact on key financial levers.
The key question for investors is not whether to adopt AI, but how deliberately and decisively they can embed it into their investment thesis today.
