Key Takeaways
- • Private equity and middle-market firms are stuck in "pilot purgatory," having invested capital in AI experiments without operational playbooks to scale isolated deployments into compounding portfolio value, according to Accordion's "PE AI Adoption Benchmark" survey.
- • The majority of PE firms operate in an expensive middle ground—past casual experimentation but lacking genuine operating leverage—creating a critical execution gap that requires systematic deployment strategies rather than isolated prototyping.
- • Portfolio company CFOs occupy a unique structural position to drive PE AI deployment, given their exposure across value creation areas and direct connection to PE sponsors, positioning them as essential executors rather than passive participants.
- • AI deployment in finance functions like P&L and forecasting can free accounting teams from routine work to focus on strategic initiatives, potentially increasing company exit valuations and creating measurable returns on AI investments.
- • CFOs must follow a clear, value-driven deployment plan rather than pursuing AI adoption for its own sake, with Kyle Roemer (Accordion) and Shawn Cole (Cowen Partners Executive Search) emphasizing that strategy and accountability structures are critical to converting pilots into operational leverage.
Summary
Private equity and middle-market CFOs face a significant execution challenge in AI deployment: while experimentation has proliferated across portfolio companies, most firms remain trapped in what Accordion's recent benchmark survey calls "pilot purgatory." The research, titled "The PE AI Adoption Benchmark: From scaling to systematizing," reveals that many organizations have deployed capital into isolated AI projects but lack the operational infrastructure to transform these experiments into scalable, value-creating systems. Kyle Roemer, managing director and US head of data, analytics, and AI at Accordion, articulated the core problem: prototyping an AI use case differs fundamentally from deploying it "into your system…and into everyone's workflow, so they can start leveraging it."
The broader market dynamic reflects what Accordion characterizes as "the expensive middle"—a transition zone where PE firms have moved beyond casual experimentation but have not yet achieved genuine operating leverage. This positioning creates both capital inefficiency and opportunity cost, as firms struggle to convert high-potential pilots into systematic business value. The challenge is not technical capability but rather organizational discipline and execution planning.
Portfolio company CFOs occupy a uniquely advantageous position to navigate this deployment gap. Their visibility across value creation areas, combined with their direct relationship to PE sponsors, positions them as critical executors. As AI expands into finance-specific use cases—particularly in P&L analysis and forecasting—CFOs can reallocate accounting team resources from routine, repetitive tasks toward higher-impact strategic work. This functional shift, when executed effectively, can materially enhance company valuations at exit.
However, success requires more than enthusiasm or technological capability. Shawn Cole, president and founding partner of Cowen Partners Executive Search, emphasized that AI deployment must follow a clear value plan and execution pathway. Without structured accountability and measurable ROI frameworks tied to business outcomes, AI investments risk remaining in the experimental phase indefinitely. The distinction between PE sponsors seeking portfolio-wide AI scaling and individual CFOs uncertain about deployment sequencing suggests that standardized decision-making frameworks—such as PwC's lead-lag-exit matrix—may prove essential for moving beyond the current stalled state.
The broader market dynamic reflects what Accordion characterizes as "the expensive middle"—a transition zone where PE firms have moved beyond casual experimentation but have not yet achieved genuine operating leverage. This positioning creates both capital inefficiency and opportunity cost, as firms struggle to convert high-potential pilots into systematic business value. The challenge is not technical capability but rather organizational discipline and execution planning.
Portfolio company CFOs occupy a uniquely advantageous position to navigate this deployment gap. Their visibility across value creation areas, combined with their direct relationship to PE sponsors, positions them as critical executors. As AI expands into finance-specific use cases—particularly in P&L analysis and forecasting—CFOs can reallocate accounting team resources from routine, repetitive tasks toward higher-impact strategic work. This functional shift, when executed effectively, can materially enhance company valuations at exit.
However, success requires more than enthusiasm or technological capability. Shawn Cole, president and founding partner of Cowen Partners Executive Search, emphasized that AI deployment must follow a clear value plan and execution pathway. Without structured accountability and measurable ROI frameworks tied to business outcomes, AI investments risk remaining in the experimental phase indefinitely. The distinction between PE sponsors seeking portfolio-wide AI scaling and individual CFOs uncertain about deployment sequencing suggests that standardized decision-making frameworks—such as PwC's lead-lag-exit matrix—may prove essential for moving beyond the current stalled state.
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