GIB Perspectives on AI
Published: 13 May 2024
- Operational Efficiencies for the Investment Teams: Many starting to leverage AI to process manager research letters, store internal memos, track investment decisions and summarize macro views from economists.
- Portfolio Management: Still early in internal implementation and while asking about the impact to external managers and portfolio companies, not requiring any specific integration from them.
- Front and back office alignment: Internal teams need to get comfortable with AI and agree how it can be implemented. Often, alignment can be best achieved by integrating back-office staff into the investment front office to enhance real-world understanding of potential implementation.
- Denominator effect: AI exuberance driving public market stock performance is consequentially creating a denominator impact for investors where they are out of sync with long-term asset allocation targets, not only by a measure of public vs. private allocations but by geographical (U.S.) and sectoral (tech) concentrations. It is hard to predict if strong performance will persist and what will be a reasonable longer-term return expectation.
- AI Providers: ChatGPT and Co-Pilot most implemented, though some investors are building customized solutions in-house and testing out other vendors.
- Data privacy: Many still grappling with what data can and cannot be uploaded within an AI system and for what end benefit.
