- Morgan Stanley has deployed its second generative AI tool, AI @ Morgan Stanley Debrief, for financial advisers.
- The new tool summarizes video meetings and drafts follow-up emails, building on an earlier AI knowledge assistant.
- The trend towards custom AI solutions over off-the-shelf tools is growing in the financial sector.
- Notable industry examples include BNP Paribas partnering with Mistral AI and TD Bank working with Cohere.
- Morgan Stanley’s approach involves integrating AI into existing systems like Microsoft Outlook, Zoom, and Salesforce.
- OpenAI’s partnership with Morgan Stanley emphasizes the benefits of tailored AI solutions.
- Despite advancements, off-the-shelf AI tools often require extensive customization and integration.
- Goldman Sachs and other firms are also focusing on custom AI applications and partnerships.
Main AI News:
Morgan Stanley has recently completed the deployment of its second generative artificial intelligence application for financial advisers, prioritizing internally developed solutions over pre-packaged tools from external vendors. The newly introduced tool, AI @ Morgan Stanley Debrief, is designed to summarize video meetings and draft follow-up emails. This addition builds on the previous launch of an AI knowledge assistant, which helps advisers access Morgan Stanley research efficiently.
Alexandra Mousavizadeh, co-founder and CEO of Evident, noted that the trend of directly collaborating with AI model developers, rather than relying on off-the-shelf technology, is gaining momentum in the financial services sector. Mousavizadeh highlighted the advantages of such a bespoke approach, stating that it allows for tools that integrate seamlessly into existing workflows, thereby enhancing efficiency. She also pointed out that similar solutions could benefit other industries like insurance and retail.
Morgan Stanley’s strategy aligns with a broader industry movement, as seen with BNP Paribas partnering with Mistral AI and TD Bank collaborating with Cohere. Mousavizadeh observed that many banks are now engaging with various model developers, including Meta Platforms’ Llama, Anthropic’s Claude, Google’s Gemini, and OpenAI’s GPT.
Despite the push towards custom-built solutions, the use of off-the-shelf AI tools remains prevalent. For instance, Goldman Sachs has adopted Microsoft’s GitHub Copilot and is building custom applications on models like Llama, GPT, and Gemini. Morgan Stanley’s tools, developed in partnership with OpenAI, exemplify the benefits of tailored AI solutions over generic products, according to OpenAI Chief Operating Officer Brad Lightcap.
While technology providers offer advanced AI tools, these often require significant adjustments to integrate into enterprise systems, raising questions about their cost-effectiveness. Tools from vendors such as Workday and Salesforce are also facing market challenges, with enterprises increasingly favoring custom-built solutions.
Morgan Stanley’s approach to integrating AI within existing systems—such as Microsoft Outlook, Zoom, and Salesforce—demonstrates a commitment to enhancing user experience and productivity. David Wu, the firmwide AI head of product and architecture strategy, emphasized the advantages of bespoke solutions that address specific user needs, rather than adopting generic products that may require extensive retraining.
Currently, Morgan Stanley is evaluating the performance of its new tools, with the meeting summarization tool’s results yet to be disclosed. However, the company has reported that 98% of teams are actively using the AI knowledge assistant, though it has refrained from providing detailed financial impact information.
Conclusion:
Morgan Stanley’s preference for custom-built AI solutions highlights a significant shift in the financial services sector toward tailored technology that integrates seamlessly into existing workflows. This trend reflects a broader industry movement away from generic, off-the-shelf products towards bespoke solutions that can offer better alignment with specific operational needs. As enterprises face challenges with the integration and cost-effectiveness of standard AI tools, the demand for customized solutions is likely to grow. This shift may influence other sectors to explore similar approaches, potentially reshaping the market for enterprise AI solutions.
