Milos Maricic
AI Strategy Advisor for Institutional Allocators
Milos Maricic is an AI strategy advisor working with sovereign wealth funds, central banks, and pension funds across global institutional markets. He specialises in helping institutional allocators navigate AI's impact on investment management, from manager evaluation and portfolio construction to governance and regulatory strategy.
His work spans manager selection and due diligence, portfolio construction with AI integration, AI governance and board oversight, and strategic advisory on the geopolitical dimensions of AI development. He is the creator of the SPEC Test, published by CFA Institute, which provides allocators with a structured approach to evaluating whether quantitative models are built on genuine economic relationships or statistical accident.
Milos Maricic serves as an AI Expert for the OECD and the World Economic Forum, and chairs Executive AI, an industry group of more than 100 institutional investor CEOs. As a hands-on practitioner, he has ranked in the top 5% of Numerai's global leaderboard, a live, competitive platform where quantitative researchers test models against real market data.
He has served as CEO of Altruist League, overseeing the company's successful sale to a sovereign wealth fund.
His academic background spans artificial intelligence (LSE) and finance (NYU Stern, Harvard Business School).
Speaking Topics
AI's Impact on Institutional Investment Management
How AI is reshaping manager selection, portfolio construction, and governance for institutional allocators. Practical frameworks for investment committees navigating this shift.
AI Governance for Investment Boards
What boards and investment committees need to know about overseeing AI-driven strategies. Practical frameworks for non-technical decision-makers.
The Geopolitics of AI and Institutional Allocation
How sovereign AI initiatives, export controls, and data governance regimes are reshaping the quantitative investment landscape, and what it means for allocation strategy.
Causal Inference and the Future of Factor Investing
How advances in causal discovery research are challenging traditional approaches to factor analysis and what this means for how we evaluate quantitative managers.
Speaking Enquiries
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