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34 turns · 18 minThe manager research team job will inherently change. It'll be back to a people business. As much as social media hid us behind a screen and led us to believe these are real things, and this is the real world, I think AI is gonna shift that back to a world of, "I actually need to see it firsthand."
[upbeat music] Welcome to the Agentic Allocator. Today, we're joined by Ryan Kulig from SITFO, the Utah School and Institutional Trust Funds Office, a four point seven billion dollar permanent fund for Utah's public education programs. For the past 16 months, Ryan has been conducting a rigorous AI landscaping exercise, evaluating solutions, building agentic workflows, and integrating AI into the operational fabric of SITFO.
I think having sound support and buy-in from the management and, and the board is super important on the get-go. And then once you have that, then empowering the team to explore and find solutions and acknowledge where there could be automation or agentic workflows in place.
As a member of various industry networks of leading endowments, foundations, and health systems, he found virtually no one else was actively implementing AI, which only deepened his conviction to lead. Today, we find out how.
Another challenge has been integrations, how we get the piping across our CRM, our benchmarking, our performance vendors, how we link it to our G Suite, our emails. Getting those dialed in and permissions controlled has been a challenge, but I think in the end will undoubtedly make the AI so much more powerful.
I hope you enjoy the conversation. [wave crashing] Ryan, thanks so much for taking the time to speak with me today.
Yeah, it's a pleasure. Thanks for having me.
Ryan, would love to start off before we dive into AI, our topic for today, to go back to the inception of SITFO. Can you walk me through how you grew the team and grew the organization?
Yeah. It's, you know, time flies. It's been almost ten and a half years since, uh, SITFO started. We started, uh, with three people, really. Peter, our CIO, was the first hire, and then myself and one of the other investment analysts, uh, were the next hires. So it's been quite the adventure. I remember early days, we were sitting down with our board members, establishing the foundational documents, uh, our investment policy statement, statement of investment beliefs, and I remember it was painful sitting around the board, uh, table and wordsmithing line by line those documents. But those were foundational, uh, to our agency, so it was important to get those out of the way. But we inherited a portfolio basically of seventy-thirty Vanguard mutual funds and some core real estate, value-add real estate partnerships. Um, so from there, we hired an investment consultant, a custodian bank, you know, got the foundations established, and off and running we went.
Incredible. Would maybe love to start from the data foundation, if you don't mind, and hear how you thought about integrating, um, all of the different kind of systems in your tech stacks. You're building that context layer for your agentic AI applications.
Yeah. We, uh, really started kind of naively, where we, uh, thought, "Hey, can we use AI to
Episode notes
Ryan Kulig, Finance and Operations Officer at SITFO, the Utah School and Institutional Trust Funds Office, joins The Agentic Allocator to share how a $4.7 billion-dollar permanent fund for Utah's public education programs became one of the earliest institutional allocators to systematically build AI into the way it operates.
For the past 16 months, Ryan has led a rigorous AI landscaping exercise at SITFO, evaluating vendors, building agentic workflows, and integrating AI into the operational fabric of the agency. As a member of several industry networks of leading endowments, foundations, and health systems, Ryan found that almost no one else in those communities was actively implementing AI, which only deepened his conviction that SITFO needed to lead.
Ryan walks through why SITFO moved past using AI to generate investment memos, which it found to be a commoditized solution, toward a cross functional platform that serves finance and operations, strategy and risk, and manager research. He explains the integration work required to connect AI to the CRM, benchmarking systems, performance vendors, email, and shared document storage, and why that unglamorous plumbing work is what makes the AI powerful. He also shares his view that institutional investors have been slow to adopt AI because they treat it as a productivity tool rather than a transformational technology, and why