By Anothony Lancaster: The quality of AI ROI measurement depends on pre-deployment decisions around business outcomes, leadership alignment, and establishing trusted information, among other factors.

Artificial intelligence (AI) has become a significant strategic investment across wealth management. As its deployment evolves from experimentation into day-to-day operations, firms are increasingly expected to demonstrate the business value of those investments.

Many firms, however, are still laying the groundwork to measure AI’s return on investment (ROI). According to recent research from F2 Strategy, 67% of wealth management firms now have a dedicated AI budget, yet 65% still lack a formal methodology for measuring AI success.

Measuring AI’s outcomes starts with decisions made before deployment. Firms need to define the business outcome an investment is expected to improve, determine how success will be measured and identify the information and capabilities needed to demonstrate that impact. Establishing those parameters upfront gives firms a stronger foundation for evaluating whether an initiative delivers business value.

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