Private Market Expansion and AI-Driven Transformation in Asset Management

The asset management industry is undergoing a seismic shift as private market expansion collides with the transformative power of artificial intelligence (AI). This convergence is redefining strategic value creation, particularly through going-private deals and operational AI integration. The result is a new paradigm where private equity firms and asset managers are leveraging both capital and technology to unlock unprecedented returns and efficiency gains.

The Resurgence of Going-Private Deals

The past year has witnessed a remarkable rebound in going-private activity, driven by macroeconomic normalization and improved financing conditions. According to a report by EY, take-private deal value in Q3 2025 reached a record $310 billion, with year-to-date (YTD) totals already surpassing the full-year figures of 2024 and 2023. This surge is fueled by the easing of interest rates, which has reduced borrowing costs and narrowed valuation gaps between public and private markets. Additionally, alternative exit mechanisms-such as continuation funds and sponsor-to-sponsor transactions-are gaining traction, providing private equity firms with liquidity solutions as traditional IPOs remain subdued.

Private equity's role in asset management has also evolved. Firms are not merely financing acquisitions but actively structuring mergers-of-equals and trade consolidations to enhance operational scale. For instance, Titan Wealth's multiple acquisitions in the UK and Channel Islands, and Söderberg & Partners' equity investments in financial advisory services, exemplify how private equity is driving structural changes to boost efficiency and market share. These transactions underscore a broader trend: private equity is becoming a catalyst for industry consolidation, enabling firms to achieve critical mass in fragmented sectors.

AI as a Strategic Value Lever

While capital remains central to value creation, AI is emerging as a third pillar-complementing financial engineering and operational excellence. A 2025 survey by Grant Thornton found that 73% of asset management executives view AI as critical to their future, with 71% planning to adopt generative AI (GenAI) within three years. AI's applications span the investment lifecycle, from automating compliance and risk monitoring to enhancing due diligence and portfolio management.

In private markets, AI is streamlining deal processes and enabling data-driven decision-making. For example, AI-powered tools can analyze vast datasets to identify high-potential targets, assess risks, and model exit scenarios. PwC highlights that AI-driven simulations allow investment committees to stress-test deal theses and prepare for due diligence questions with precision. Beyond deal sourcing, AI is reshaping portfolio company operations. In manufacturing, predictive maintenance and logistics optimization have delivered EBITDA improvements of 5–25%, while healthcare firms leveraging AI for diagnostics and administrative workflows have seen cost reductions and improved patient outcomes according to Neueon's 2025 insights.

Case Studies: AI in Action

The tangible impact of AI in going-private deals is evident in recent case studies. CapitalGains Investments reported a 20% increase in annual returns for clients using AI-driven platforms. Similarly, a healthcare analytics firm with a proprietary machine-learning engine secured a 12x revenue multiple in a private equity deal, demonstrating how AI can command valuation premiums through competitive differentiation.

Another compelling example is the use of AI in mid-market portfolio companies. Accenture notes that firms adopting AI for back-office automation and customer engagement have achieved EBITDA uplifts of 2–4x annually. In logistics, AI-driven cost-to-serve reductions of up to 20% have directly enhanced exit multiples, aligning with private equity's typical investment horizons according to FT Consulting insights. These outcomes highlight AI's scalability and its ability to deliver quick, measurable returns-a critical factor in an industry where time-to-value is paramount.

Challenges and the Road Ahead

Despite these advancements, challenges persist. Fragmented technology ecosystems, regulatory uncertainty, and data quality issues hinder AI adoption, as noted in a Deloitte report. Moreover, only 27% of asset managers surveyed by EY reported substantial business impact from GenAI, underscoring the need for strategic alignment and governance frameworks.

Looking ahead, 2025 is shaping up as a transition year. With dry powder at record highs and macroeconomic conditions stabilizing, the groundwork is being laid for a robust M&A cycle in 2026. Firms that integrate AI not as a tool but as a strategic partner-embedding it into core processes like R&D, manufacturing, and regulatory compliance-will be best positioned to capitalize on this shift according to E78 Partners analysis.

Conclusion

The intersection of private market expansion and AI-driven transformation is redefining asset management. Going-private deals are unlocking liquidity and operational scale, while AI is accelerating value creation through automation, analytics, and innovation. As these trends converge, the firms that succeed will be those that view AI not as a peripheral enhancement but as a foundational element of their value proposition. In this new era, strategic value creation is no longer a choice-it is a necessity.