Anmol Goel, CEO and Managing Partner of GACS Family Office, joins The Agentic Allocator for a practical conversation about AI adoption inside a family office. GACS invests over $1 billion across venture, private equity and private credit from London and India, and Anmol runs it in public, speaking at conferences and building a personal profile in a historically discrete community. Anmol walks through how GACS is using AI within the investment office: a tech due diligence tool trained on the firm’s own past investment memos that has taken analysis from two months down to 2-3 weeks, an internal database that cross compares deals and surfaces unique portfolio connections, and a personal knowledge base built from roughly 10,000 contacts, past conversations and notes that he queries whenever a founder needs an introduction. He is equally direct about the challenges and what has gone wrong. Team members have put sensitive documents into public tools. Work has gone out without being checked. He is clear that they are still working through where the AI privacy line sits, and that the answer will be different for every family. For an industry where most AI conversations only cover the wins, it is an important reality check. What You'll Learn: How he got his family comfortable with a public profile in a historically private industryHow GACS built a tech due diligence tool on its own past investment memos, and why analysis went from two months to 2-3 weeksWhat happened when a new pitch deck went into the system and it surfaced a link to an existing portfolio company nobody had spottedHow a personal knowledge base of roughly 10,000 contacts answers questions like which fintech regulators do I knowThe two adoption challenges he has lived throughWhy he thinks an extra 30 to 60 seconds on a prompt removes most of the hallucination problemWhy he worries the next generation will lose the knowledge of knowhow, and what first principles have to do with AIWhat AI adoption looks like across the 30 to 35 family offices he co invests with, and why the split is generational rather than by sizeHis starting point for families: repetitive tasks, a cost test, and ignoring vendors who use big numbers to create urgencyAbout Anmol Goel: Anmol Goel is CEO and Managing Partner of GACS Family Office, a family office operating across the UK and India with over $1 billion in assets under management, investing across venture, private equity and private credit. He founded his first company at 17 and exited his second at 20 before moving into investing. He holds a degree in mathematics and economics and began his career at JP Morgan and Marsh McLennan. He has backed more than 80 companies and funds, co-invests alongside a syndicate of over 30 family offices, and has beta tested AI models ahead of public release. Episode Highlights: [01:42] Building in PublicFamily offices have historically operated quietly. Anmol’s view is that a public profile was the fastest route to a network, because if you know something worth sharing, people will take the call. His grandparents’ investment knowledge was land, real estate and gold, so what he was doing looked alien to his family at first. What settled it was a stack of proof. [05:35] AI Inside the Family Office Most significantly, GACS built its own tech due diligence tool, trained on past investment memos and structured around what the firm looks for in a founder, a market and technology. It is not perfect and human intervention is still required, but analysis that used to take two months now takes two or three weeks. [06:43] When the System Spots What the Team Missed As the database grows, GACS can cross compare deals and identify smaller M&A opportunities across the portfolio. Anmol describes putting a pitch deck for a company the firm was about to back into the system, which immediately flagged how it linked to an existing portfolio company. The team had not made that connection themselves. [07:14] Ten Thousand Contacts and One Searchable Base With close to 10,000 contacts on his phone, Anmol is compiling everything into a single base: contacts, past videos, conversations, and notes. When a fintech founder comes to him, he can ask which fintech regulators, policymakers, operators, founders and investors he already knows, and get back a list with context on how each one could help. For a firm that invests hands on, that is the difference between remembering a useful contact and not. [09:20] Where It Has Gone Wrong: Privacy and Unchecked Output Two challenges stand out. The first is compliance and privacy. It can be hard to know with confidence what is being stored, and members of the team have put highly sensitive documents into public systems. The second is cutting corners. Output passed on without proper checking has been wrong highlighting the need for a human-in-the-loop. [10:32] Prompt Engineering and the Two Week to Two Hour Shift A new hire in a team meeting that morning had been hesitant about using AI at all. Anmol’s response was that work which used to take two weeks now takes two hours, and the skill that closes the gap is prompting. Being precise about what you want, and spending an extra 30 to 60 seconds specifying it, removes a large share of the hallucination risk. [11:22] First Principles and the Knowledge of Knowhow Anmol has a background in mathematics, taught to derive an equation rather than just use it. His concern is that the models will keep improving while the underlying knowledge of how something works quietly disappears from the next generation. He considers himself lucky to have been on the cusp, having learned it just before it became optional. [12:48] The Adoption Split Across Family Offices Across the 30 to 35 family offices GACS co invests with, the divide is generational rather than by size. Families rooted in agriculture, manufacturing or real estate, with principals in their fifties and the next generation not yet in seat, are still some ways behind. Founders who exited in their early thirties and now run a few hundred million are often far ahead, to the point where Anmol asks them how they built it. [14:15] Where to Start, and What to Ignore Start with the most repetitive tasks and see whether AI can take them. Run a cost analysis and check that one plus one makes two, because families understand numbers. Be skeptical of vendors who use big terminology and big numbers on an audience they know has a knowledge gap. Start small, understand what is actually making it work, and do not buy on FOMO. [15:23] People Analysis Over Market Analysis Anmol argues qualitative analysis matters more now. His own work has shifted from technical, financial and market analysis towards people analysis: how hungry the founder is, how driven, what the why is. That is the part he does not believe AI will pick up, so he lets the models handle the rest and spends his time travelling to meet people. [16:22] Why He Meets Everyone Before Investing Of roughly 80 funds and startups backed over the past two to three years, Anmol cannot think of one he invested in without meeting them first, even where that meant waiting a month or two. He accepts that this costs him deals. The trade is that the ones he does write are...
