Morgan Stanley

Morgan Stanley's 15,000+ financial advisors faced time-intensive manual research to uncover the right investment recommendations, requiring them to comb through large volumes of research, market data, and client information. Scalability limits meant advisors struggled to serve growing books of business, and recommendations were inconsistent depending on individual advisor capacity. There was also growing client demand for more tailored, data-backed advice in an increasingly competitive wealth management landscape.

Morgan Stanley deployed 'Next Best Action' (NBA), an internal AI engine that analyses client preferences, portfolio history and behaviours, real-time market conditions, proprietary research, and product suitability and compliance filters. The system generates personalised recommended actions and messages advisors can send to clients, including rebalancing suggestions, timely product recommendations tied to life events or market trends, and follow-up prompts after portfolio underperformance. By mid-2022, over 90% of Morgan Stanley advisors were actively using NBA.

The system delivered a 30% increase in client engagement with investment proposals. Advisor productivity improved, enabling more clients to be served without increasing headcount. Response times for client needs shortened with proactive, timely insights, and consistency and compliance in recommendations were enhanced. Junior advisors were empowered with the same insight quality as seasoned professionals.

• AI augmentation rather than replacement creates a force multiplier effect: 90%+ advisor adoption shows the tool enhanced rather than disrupted existing workflows.
• Combining real-time market data with client behavioural data enables hyper-personalised outreach at scale, addressing both consistency and relevance challenges.
• Embedding compliance filters directly into the AI recommendation layer reduces regulatory risk while accelerating advisor outreach.