Dutch Private Equity Firms Fall Behind in AI Race Despite Recognizing Innovation Potential

2026-03-10 data

Amsterdam, Tuesday, 10 March 2026.
While 88% of private equity organizations use artificial intelligence, only 40% of portfolio companies have successfully integrated AI into multiple business processes, revealing a critical execution gap. Dutch investment firms particularly struggle with this AI adoption challenge, missing opportunities for competitive advantage and value creation. The disconnect between AI recognition and implementation highlights fundamental issues with software foundations rather than the technology itself, creating significant risks for deal analysis and portfolio performance.

The Reality Behind AI Adoption Numbers

The findings from Software Improvement Group’s comprehensive report titled “AI ambition and reality in Private Equity” reveal a stark disconnect between AI aspirations and actual implementation [1]. While two-thirds of general partners report AI pilots in their portfolios, the reality shows that meaningful integration remains elusive [1]. This gap becomes particularly concerning when examining the technical foundations supporting these AI initiatives. In 2025, SIG’s analysis of production systems found that only about 1.5% qualified as actual AI systems, indicating that the industry remains in very early stages of adoption [1]. More troubling, 72% of existing AI systems scored below SIG’s recommended threshold for construction quality, creating significant risks in maintainability, security, and compliance [1].

Software Foundation Challenges Hampering Progress

The core issue facing private equity firms extends beyond AI technology itself to the underlying software infrastructure required to support these advanced systems [1]. Luc Brandts, CEO of Software Improvement Group, explains the fundamental challenge: “AI verandert fundamenteel de manier waarop we zakendoen en vergroot de afhankelijkheid van technologie tot ongekende niveaus…Kunnen we vertrouwen op wat er wordt gebouwd? Investeren we op de juiste plekken? Hoe klaar zijn we voor AI? Dat zijn vragen die elke investeerder mee worstelt en waarop duidelijke antwoorden nodig zijn” [1]. This technological dependency creates unprecedented levels of risk that many firms are unprepared to manage effectively. The quality issues become even more pronounced when considering that AI-supported programming productivity results have shown mixed outcomes, ranging from a 19% slowdown to a 26% acceleration, while AI-generated code demonstrated twice as many security risks in SIG’s experiments [1].

Market Dynamics Reshaping Valuations and Deal Flow

The AI revolution is fundamentally altering how private equity firms approach valuations and deal structures across their portfolios [2]. Technology companies serving industries with high regulatory scrutiny and operational complexity, such as public sector, financial services, healthcare, energy, and aerospace, are finding themselves more insulated from AI disruption due to compliance safeguards [2]. However, this protection comes with trade-offs, as platforms in complex sub-sectors like cybersecurity can experience outsized acceleration from AI due to their proprietary threat intelligence and embedded market positions [2]. The valuation pressure is becoming increasingly evident in secondary markets, where buyers are demanding discounts of as much as 20% to acquire pieces of private equity firms’ technology-heavy portfolios, a dramatic increase from the 5% discounts sought just weeks earlier in February 2026 [5].

Centralized AI Operations Drive Superior Returns

The performance gap between different AI adoption strategies has become quantifiably significant, with private equity firms implementing centralized AI operations achieving a 40% EBITDA advantage over those leaving AI adoption to individual portfolio companies [7]. Firms with centralized approaches are seeing EBITDA improvements ranging from 5-25%, with top performers reaching four times the baseline performance [7]. This stark difference has led to the emergence of entirely new roles within the industry - the AI Operating Partner position, which did not exist five years ago, now comprises approximately 250 roles at scale in private equity, with compensation packages exceeding $1 million annually [7]. Companies like Vista Equity Partners have demonstrated the potential of this centralized approach through their Agentic AI Factory, which has enabled portfolio company Gainsight to reduce customer renewal time from seven days to one day while cutting churn risk by 90% [7]. Meanwhile, EQT’s Motherbrain platform, aggregating 140,000 data points across 600 data sources, has secured over 200 million euros in investments [7].

Bronnen

artificial intelligence private equity