Miloš Maričić

Why organisations work with Miloš Maričić

• He gives investment boards a working diagnostic for distinguishing real machine learning from AI marketing, anchored in his SPEC framework and his CFA Institute Enterprising Investor work on weak quant models.
• He chairs Executive AI, the network of CEOs of major European institutional investment organisations, and represented that industry in the EU Artificial Intelligence Act standardisation process. Few speakers can describe AI regulation from inside the room where the rules were written.
• He has co-edited the Routledge Handbook of Artificial Intelligence and Philanthropy with the University of Geneva, the standard reference for AI in the social sector. That gives foundations and philanthropic boards a credible voice on the same subject.
• He has built and exited two AI companies and ranks in the top five per cent of the Numerai global leaderboard for market prediction models, so the technical claim is matched by personal track record.
• He is an OECD AI Expert and a World Economic Forum contributor, which means his framing is already calibrated for senior policy and regulatory audiences.

Biography highlights

• Founder of the Altruist League, Geneva, a philanthropy consultancy whose network reports AUM above USD 10 billion.
• Chair of Executive AI, a network of CEOs of major European institutional investment organisations.
• AI Expert at the OECD and contributor at the World Economic Forum.
• Co-editor, The Routledge Handbook of Artificial Intelligence and Philanthropy, Routledge, 2024.
• Co-author, Fixing Philanthropy: Six Principles for Actually Improving the World When Giving Away Money, 2021.
• Educated at the London School of Economics, New York University and Harvard Business School.

Biography

Most institutional investors now have AI somewhere in their portfolio, their managers, or their operations. Very few have a working method for telling genuine machine learning from a factor model dressed up for a board meeting. That is the gap Maričić has spent his career filling, first inside his own AI ventures, now as Chair of Executive AI, the network of CEOs of major European institutional investment organisations.

His SPEC framework, developed for capital allocators and published through CFA Institute’s Enterprising Investor, gives investment committees a short diagnostic for evaluating quantitative managers who claim AI capability. It is the kind of practical tool a CIO can take into a manager meeting on Monday morning. He represented the institutional investor industry in the EU Artificial Intelligence Act standardisation process, and serves as an AI Expert at the OECD and a contributor at the World Economic Forum.

Maričić founded the Altruist League, a Geneva-based philanthropy consultancy that pioneered the use of AI in sourcing investments, distributing funds and managing portfolios, and whose network now reports AUM above USD 10 billion. With Giuseppe Ugazio at the University of Geneva, he co-edited The Routledge Handbook of Artificial Intelligence and Philanthropy, the 2024 reference work for foundations and social sector boards thinking about AI governance.

He is educated at the London School of Economics, NYU and Harvard Business School, ranks in the top five per cent of the Numerai global leaderboard for market prediction models, and writes The Specification, a newsletter that translates frontier AI research into practical tools for institutional allocators.

Key speaking topics

• AI governance for investment boards and fiduciary committees
• Due diligence on machine learning in quantitative investment strategies
• AI regulation, the EU AI Act and institutional capital allocation
• AI in philanthropy and the social sector
• Causal inference and the limits of factor investing
• Geopolitics of AI for sovereign wealth funds and central banks
• Trust-based giving and systemic-change philanthropy

Ideal for

• Chief Investment Officers, investment committees and manager-selection teams at pension funds, sovereign wealth funds, central banks and endowments
• Boards of foundations and philanthropic organisations setting AI strategy and governance
• Risk, audit and fiduciary committees taking responsibility for AI-driven strategies they did not build
• Senior policy and regulatory audiences working on AI in financial services

Audience outcomes

• A clear diagnostic for distinguishing real machine learning from AI marketing inside quantitative managers
• Specific questions a board or investment committee can put to managers and internal teams about AI claims
• A current read on the EU AI Act and what it means for institutional allocators in practice
• A grounded view of where AI is genuinely changing philanthropy and where it is hype
• A working vocabulary for fiduciary AI oversight that does not require a technical background