Amid heightened investor curiosity in cutting-edge tools and diversified exposures, BlackRock’s Global Head of Systematic Investing, Raffaele Savi, is warning: artificial intelligence (AI) is poised to fundamentally transform how capital flows into private markets. In a recent appearance on the Goldman Sachs Exchanges: Great Investors podcast (recorded July 29, 2025), Savi laid out a vision where AI-driven, algorithm-based strategies move beyond liquid public equities into less transparent private assets—a potential game-changer for asset allocation and risk management.
Why This Matters for Investors
- Scale Meets Sophistication
Savi highlights that generative AI and large language models (LLMs) are lowering the barriers to systematic investing—making it scalable, versatile, and interactive. These tools can sift through vast and diverse datasets, from product reviews to social media trends, expanding analytical horizons beyond traditional metrics. - From Public to Private
Historically, quant-driven investing stayed within liquid markets—stocks, bonds, and ETFs. Now, Savi believes AI could extend those systematic strategies into private equity, credit, and infrastructure—asset classes once considered too opaque or illiquid for algorithmic approaches. - Backing by Infrastructure
BlackRock’s operations are anchored in powerful platforms such as Aladdin, its risk and portfolio analytics engine now increasingly powered by AI, and eFront, which supports private markets data workflows and integration with Aladdin. Augmenting these are acquisitions like Preqin (private markets data) and HPS Investment Partners (credit manager), reinforcing the firm’s data heft and private markets reach.
Future Trends to Watch
- Data Multiplicity
Savi predicts that over the next 10–15 years, systematic models will ingest unconventional data—such as Instagram activity, search trends, product feedback, and human capital networks—creating a richer, multi-dimensional lens on private companies. - Portfolio Resilience Through AI
Drawing an analogy with safety engineering in aviation and automotive, Savi suggests AI won’t predict crises but can add layers of safety—designing portfolios that resist shocks through proactive risk modeling. - Expanding Private Allocation
BlackRock is targeting 30% of its revenue from private markets and technology by 2032, signaling long-term institutional commitment to this strategic shift.
Key Investment Insight
AI-powered investing presents a tactical opportunity for forward-looking investors—but it comes with caveats:
- Opportunity:
The integration of AI in private markets promises improved efficiency, broader data capture, and more dynamic portfolio construction. Early movers in private markets could benefit from structural advantages in deal sourcing, valuation, and risk assessment. - Risk:
AI systems are not infallible. Model risk, overfitting, and reliance on poor-quality or biased data can destabilize outcomes—especially in opaque markets where transparency is limited. - Actionable Strategy:
Investors should monitor how asset managers deploy AI within private asset strategies. Consider allocations to funds or platforms that combine systematic rigor with robust human oversight. Evaluate managers’ technology stacks—Aladdin, Preqin, data integration, AI tooling—and their track record managing quant-driven products across cycles.
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