PE firms face growing gap between AI expectations and realised returns: Coforge

Private equity firms are confronting a critical execution challenge: the returns anticipated from artificial intelligence investments are substantially outpacing the measurable business outcomes being generated across portfolio companies. According to a new white paper from Coforge titled "AI in Private Equity: Driving Value Through AI Execution," this gap between expectations and realized results has emerged as a defining challenge for institutional investors attempting to convert AI investments into tangible returns including revenue growth, margin expansion, and improved portfolio performance.

The fundamental issue stems from AI's evolving role in PE investment frameworks. As Preeti Singh, Executive Vice President and Head of North America at Coforge, explained, "AI is no longer a source of optional upside, but a core assumption that underpins revenue growth and margin expansion expectations in many PE investment models." This shift has elevated the stakes: AI is now embedded in investment theses and value-creation plans at many firms, making execution quality directly correlated with deal performance and investor returns. However, many PE firms continue to struggle with translating these ambitions into operational reality.

Coforge's research identifies execution and governance as the critical differentiators between firms capturing AI value and those falling short. The firm argues that winning PE investors are those that develop repeatable, scalable rollout models capable of deploying AI across multiple portfolio companies rather than confining AI initiatives to isolated experiments or single-company pilots. The white paper outlines a structured framework spanning the entire PE investment lifecycle: AI-based due diligence during deal evaluation, repeatable execution programs during value creation, and portfolio-level governance capabilities that provide visibility, accountability, and autonomy across multiple AI initiatives simultaneously.

The broader market backdrop underscores the urgency of this challenge. Research shows that 41% of PE firms remain in nascent stages of AI adoption, while over half of surveyed North American firms predict AI restrictions within 12 to 18 months due to governance concerns—suggesting regulatory and board-level scrutiny is intensifying. Additionally, market demand is substantial: 84.5% of channel decision-makers expect AI software to drive growth in 2026. The combination of high expectations, governance scrutiny, and execution maturity gaps creates substantial downside risk for PE firms that fail to close the expectations-versus-outcomes divide. Coforge's launch of a dedicated Private Equity Business Unit earlier in 2026 reflects institutional demand for specialized expertise in bridging this execution gap at scale.