EQT is treating the AI-driven market selloff as a buying opportunity, hunting for software businesses that can convert AI into measurable margin gains without overconcentrating its portfolio. In a recap of its AI Summit by Victor Englesson and William Evensen, the firm said deal teams will prioritise targets with strong data governance, model-evaluation processes and operational readiness to turn AI into lasting cost and revenue improvements.
Dealmakers view a down market as opportunity
Some dealmakers say the broad selloff driven by fears of AI disruption has created attractive sourcing conditions in software. Private equity groups often see market corrections as moments to be active.
While volatility can lower entry prices, EQT emphasised at its AI Summit and in company materials that it wants companies that can convert AI into business improvement, not just flashy technology. The firm also noted portfolio diversification rules to avoid overexposure in any single sector.
Activity in public markets has compressed valuations for some tech names. For PE buyers that keep dry powder, that compression can translate into leverage for negotiating price and structure — if the target's fundamentals still point to long-term adoption of AI features or automation-led cost gains.
Inside the AI Summit: what leaders said about building with AI
EQT convened more than 75 technology and AI leaders at its AI Summit in 2025, according to a recap authored by Victor Englesson and William Evensen of EQT. The meeting gathered founders, CTOs, product leaders and outside experts to compare where AI is delivering value and where it raises fresh demands on teams and processes.
Summit participants returned to a handful of repeat messages, including:
- Culture and leadership amplify AI: AI tends to magnify existing strengths and weaknesses, so organisational culture matters as much as tool choice.
- Model orchestration matters: The next phase of value comes from integrating and orchestrating existing models and turning autonomous systems, or "agents," into operational doers.
- Operationalise agents like staff: Participants recommended onboarding, training and performance-managing agents rather than treating them as one-off tools.
Discipline, governance and safety as deal filters
Both the summit recap and EQT materials emphasised discipline. Englesson and Evensen wrote that organisations winning with AI embed safety, reliability and governance into their DNA, and that clear rules and evaluation frameworks can speed adoption by reducing rollout friction.
For deal teams, that mindset matters: buyers increasingly favour targets with mature data governance and model-evaluation processes to reduce execution risk and unlock faster margin gains when AI is applied to product and operations.
Portfolio diversification rules act as a firm-level safety valve: while private equity cycles can reward concentration when a theme is proven, maintaining selective exposure aims to keep fund-level risk balanced.
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EQT spelled out the approach in its summit recap: the firm will prioritise software targets that combine disciplined governance, culture change and model orchestration so AI drives real margin gains while keeping fund-level risk balanced.
This article was created with AI assistance.
