It appears that buy-versus-build has an exciting new option with associated risks: AI. But is that the right way to think about it?
You have a track record, a system, and the knowledge to scale. Now comes everything else: the legal, risk, and operational hurdles to overcome to build a fund or managed account platform. The traditional decision-making process is to determine what to buy and what to build. AI and agentic AI now offer new directions that almost look like an alternative third option.
LLMs can draft investor agreements and pitch decks. Agents can comb through your clearing broker files to find problems and analyze data.
But just because AI can do something doesn’t mean AI should do something. Many have valid concerns about giving their financial data to models. Regulated markets have many requirements that have no tolerance for AI mistakes. Serious financial and reputational exposure could be on the line. Ask an LLM if its legal advice means you can skip a lawyer and see how quickly it tells you to call one.
We’ve been thinking about these same issues and have concluded that the best way to embrace the power of AI is to not think of it as its own option. The known problems and limitations of AI won’t stop us from utilizing it, but we don’t see AI as the end-all solution either. Emerging managers deserve options to incorporate AI intelligently into what they build and buy.
You don’t have to give an AI company your margin requirements to use AI to help you with margin requirements. You can use AI to reduce operating costs without surrendering operational sovereignty.
Download our paper to learn more about what we mean.
AI disclosure: This post is human authored with LLM used for proofing/feedback