Bridging AI research and institutional investment strategy.
I advise sovereign wealth funds, central banks, and pension funds on:
- Manager evaluation & AI due diligence
- AI governance & board oversight
- Research & proprietary frameworks
In the press
Cheap Tokens, Costly Chips and a Missing AI Payoff
Taking Stock, 27 August 2026
Cheap AI, costly chips: Wall Street hunts for a missing payoff
Business, 27 August 2026
Inside Sovereign Wealth Funds' AI Push
12 August 2026
“A study by Milos Maricic, founder of the AI advisory firm Maximand, went looking for it in a sector where the productivity story should be easy to prove.”
What I Do
Manager Evaluation and Due Diligence
Quantitative managers increasingly claim to use AI. Most allocators lack the tools to verify those claims. I help institutional investors ask the right questions and interpret the answers, distinguishing genuine machine learning integration from repackaged factor models with an AI label.
AI Governance and Board Oversight
Boards and investment committees face a growing challenge: overseeing AI-driven strategies they may not fully understand. I work with governance bodies to build the knowledge frameworks and oversight processes needed to make informed decisions about AI integration in their portfolios.
Proprietary Frameworks and Tools
I develop practical instruments that translate academic AI research into actionable guidance for allocators. These frameworks, starting with SPEC, are designed for the meeting room, not the research lab. Each one addresses a specific gap in how institutions evaluate and integrate AI.
Research and Thought Leadership
I publish at the intersection of causal inference, machine learning, and institutional investment strategy. My work bridges the gap between what AI researchers develop and what allocators need to know, with a focus on what is practically relevant for capital allocation decisions.
Quarterly Research Report
The State of AI Alpha
The industry's leading quarterly report on AI in institutional investing. What works, what doesn't, and the portfolio risks most allocators cannot yet see, grounded in evidence from 164+ papers, live fund data, and practitioner interviews. Built for CIOs, manager selectors, and investment committees.
Free to read. No signup.
SPEC Framework
Every quant manager says they use AI. Most allocators have no structured way to test that claim.
Standard due diligence focuses on what a model does: returns, Sharpe ratios, attribution. It rarely tests why the model is built the way it is. That gap is where the largest undiagnosed risks hide. The SPEC Process Assessment diagnoses your evaluation process in five minutes, identifies your structural blind spots, and gives you specific questions to use in your next manager meeting.
11 questions. No registration required.
The Full Body of Work
See everything in one place
The SPEC protocol and the research behind it, the AIMI index, The State of AI Alpha, the practitioner tools, and the company it became. They connect, and they sit on a single page.
Featured
The SPEC Test
A four-part diagnostic for evaluating AI claims in quantitative investment strategies. No technical background required.
Read moreAIMI, the AI Maturity Index
SPEC Research
The first index ranking the world's largest sovereign wealth and pension funds on AI capability. 53 institutions scored from the public record and from evidence funds have shown us directly, with the reason and source behind every sub-score.
Read moreWould the Backtest Survive a Different Specification?
CFA Institute Enterprising Investor
The closing piece of a four-part series on quantitative due diligence. The same strategy, rebuilt with equally defensible settings, can produce a different track record. What to ask before you trust the one you were shown.
Read moreMaking allocation decisions where AI is a factor?
I work with a small number of institutional clients. If AI is shaping your allocation decisions, governance, or manager selection, let's talk.
Work With Me