Should Your Buy-Side Firm Hire a Head of AI?

Your investment firm’s POV on AI 

In our view, it is more important to have an authoritative point of view (POV) and clear plan for AI than to have a head of AI. Every buy-side firm is moving toward agentic AI and large language model (LLM) technology. And, in this technology-heavy business, clients, investors, job seekers, and partners all expect firms to be on the cutting edge. The baseline for any firm in 2026 is to have a strategic view on AI so they can answer client inquiries. However, that POV should be substantive, as substantive as their level of maturity. If a firm is a late adopter or a follower that sees AI’s potential but proceeds cautiously with small investments, its POV should reflect that sincerely. In today’s environment, investors may lose confidence in a fund if the manager cannot articulate a solid plan for AI initiatives. 

Fear of missing out (FOMO) is rampant and can cause a pressure cooker environment in which one fund might have deployed AI agents in a sexy use case and suddenly competitors rush to do likewise. Or worse, a firm just wants to generate some kind of AI credibility and pressures middle management to come up with a use case without much holistic forethought. Even if a firm is a laggard in the AI race, if it has a POV and a future roadmap, it will be fine, especially in this early stage. Subsequently, when a meaningful use-case need arises that is solvable, the firm can throw some real dollars and talent at the rollout. At that point, somebody needs to take charge of AI transformation. 

An AI steering committee: aligning investment, data, and technology teams  

At Arcesium, we have a team of leaders from various departments who spearhead the planning and strategy for AI innovations. Firms that appoint an AI steering committee can leverage the existing roles that are already in place, like CTOs, chief information officers, and heads of data science. Further, a steering committee makes room for important input from the firm’s subject matter experts from operations, accounting, front office, and investor relations, who are already working on a particular problem or use case. Morgan Stanley has a “Firmwide AI team” working to unify the organization's efforts and steward the technology’s use in line with its core values.^v  

The steering committee can collaborate to decide how to allocate AI spending, govern AI risk, run change management, and communicate to stakeholders, among other things. Moreover, as WTW wrote, the AI leadership team will also need to “ensure the CEO, management team and workforce have the technological competence to execute the company’s AI agenda.”^vi  

Do I need to hire an AI prodigy? 

While it is crucial that its technical leaders should have some degree of AI experience, firms can also rely on their network of partners, whether they are administrators, consultants, or solution providers. A good mix of vendor support and in-house R&D to drive the roadmap is sensible in terms of spending since the vendors absorb the cost of innovation. While vendors provide the technical engine, the firm’s internal lead must focus on understanding the business use case and how AI will augment specific operations. 

McKinsey advises that firms use vendors while insourcing certain capabilities to “enhance execution speed and ensure access to key technologies.” But they should retain ownership of their technology roadmaps.^vii     

AI capabilities that endure, not just impress 

AI is markedly different than previous shifts like the cloud. While cloud migration was about security and cost reduction, AI is perceived as a tool for survival and massive scaling, which can cause executives to force teams into use cases before they are ready. To avoid allowing the shiny new AI object gathering a patina of disappointment, buy-side firms should have a plan and POV on their AI implementation, an AI leadership group or steering committee to unfurl the roadmap, and helpful technology vendors with capital markets domain expertise. Ultimately, the goal of AI adoption should be to change the economics and trajectory of the business through thoughtful, use-case-driven strategies rather than technical hype.