

Artificial Intelligence (AI) is now being used widely across Private Banking and Investment Management. In a 2024 global survey of investment managers, 25% of managers stated the use of AI to support investment decision-making, 21% for risk management inputs, and 18% for portfolio construction and rebalancing (Mercer, 2024). While AI is increasingly being adopted by firms, questions surrounding governance, true value creation and scaling of these systems company-wide are being asked.
PryceWilliams’ perspective on the use of Artificial Intelligence in the industry has been curated through our extensive experience working with Private Banks and Investment Management firms. The firms we deal with are at different stages in AI adoption. Some are simply experimenting, while others have embedded AI operating models. The common challenge shared by firms is identifying the areas where AI can create tangible value, how to ensure proper governance, and how best to take accountability.
Artificial Intelligence at this stage in Private Banking and Investment Management can be best understood as a force multiplier for productivity. Using large language models, such as ChatGPT, in workflows can be compared to having a highly effective personal analyst at hand.
Tasks that once required hours can now be delegated to an LLM. For example, reading market updates, analysing company filings, synthesising research and creating Excel spreadsheets. In this sense, AI can be compared to prior technological innovations, such as Excel transforming the productivity of the accountant.
However, using AI differs from technologies like Excel in several ways. AI systems can execute several tasks autonomously without necessarily requiring a user’s validation at each stage. For example, an AI assistant could be prompted to collect, analyse and interpret data, and be incorrect at any one of these stages. If such inaccurate analysis is fed into investment strategy or client recommendations, the outcome may be detrimental due to the substantial capital that is often at stake. Moreover, we must consider accountability in relation to the use of AI.
In our previous examples, who exactly should be held accountable for a poor decision that is made relating to an investment strategy or client recommendation? Some may point to the individual or team that prompted the AI, whereas others may suggest the final decision maker. This question, like many others involving AI in Private Banking & Investment Management, does not have straightforward answers.
To understand and answer these questions, PryceWilliams is partnering with Funds Talent to host a live webinar on the 26th of February 2026. During this event, our expert panel will put forward their ideas to pressing questions such as:
In addition to considering attending the event, firms should:
PryceWilliams provides specialist consulting and project delivery services for organisations undergoing strategic change, regulatory compliance and technology transformation needs. Our focus is on supporting the project sponsor to ensure project implementation is delivered on time and within budget. Should you need support, contact us to make progress happen.
Mercer Investments (2024) AI integration in investment management: 2024 global manager survey. Mercer Investments. Available here. (Accessed: 17/02/2026).