Flag

We stand with Ukraine and our team members from Ukraine. Here are ways you can help

Get exclusive access to thought-provoking articles, bonus podcast content, and cutting-edge whitepapers. Become a member of the UX Magazine community today!

Home ›› Knowledge Management Challenges and Building Advanced Digital Assistants at Morgan Stanley

Knowledge Management Challenges and Building Advanced Digital Assistants at Morgan Stanley

by Josh Tyson
1 min read
Share this post on
Tweet
Share
Post
Share
Email
Print

Save

Jeff McMillan and David Wu of Morgan Stanley join Robb and Josh for a deep dive into the technical work and strategic initiatives that allowed the global investment bank to create a knowledge base that’s allowing them to take a massive leap forward with conversational AI. As the Head of AI and the Head of Knowledge Management & Generative AI respectively, Jeff and David led the creation of an intelligent digital assistant that is making their advisors smarter and saving them time.

Partnering with OpenAI in the months before ChatGPT was released, Morgan Stanley was able to rebuild their existing content using generative AI and relational databases. This is a deep dive into the technical work and strategic planning required to leverage conversational AI in ways that become a force multiplier within an organization. Don’t miss this high-value episode of Invisible Machines.

Check out the episode here.

post authorJosh Tyson

Josh Tyson
Josh Tyson is the co-author of the first bestselling book about conversational AI, Age of Invisible Machines. He is also the Director of Creative Content at OneReach.ai and co-host of both the Invisible Machines and N9K podcasts. His writing has appeared in numerous publications over the years, including Chicago Reader, Fast Company, FLAUNT, The New York Times, Observer, SLAP, Stop Smiling, Thrasher, and Westword. 

Tweet
Share
Post
Share
Email
Print

Related Articles

Real engagement is about designing experiences that people want to have. Here are some things that games do well that most apps don’t.

Article by Montgomery Singman
Gamification 2.0. Beyond Points and Badges: Designing for Players, Not Metrics. Conclusion
  • Most apps use gamification as a manipulation layer to drive metrics, but people engage with things that are truly worthy of their time, not points or streak guilt.
  • Apps that people stick with do this by designing for intrinsic motivation, making the experience itself rewarding.
  • The true measure of success is whether users feel more capable, accomplished, and enriched for having used your app.
Share:Gamification 2.0. Beyond Points and Badges: Designing for Players, Not Metrics. Conclusion
8 min read

Hiring is automated. The tools built to help you keep up are making it worse. There’s another way — one that puts your data, your drafts, and your decisions back in your hands.

Article by Pavel Bukengolts
Job Search Terminal: A Local-First Tool for an AI-Shaped Job Market
  • The piece argues that most AI job search utilities deal with the wrong problem: they only lower barriers for candidates and perpetuate existing power imbalances.
  • It contends that the choice of local-first, people-centered tools is a political position on professional data ownership, not simply a technical decision.
Share:Job Search Terminal: A Local-First Tool for an AI-Shaped Job Market
5 min read

Join the UX Magazine community!

Stay informed with exclusive content on the intersection of UX, AI agents, and agentic automation—essential reading for future-focused professionals.

Hello!

You're officially a member of the UX Magazine Community.
We're excited to have you with us!

Thank you!

To begin viewing member content, please verify your email.

Get Paid to Test AI Products

Earn an average of $100 per test by reviewing AI-first product experiences and sharing your feedback.

    Tell us about you. Enroll in the course.

      This website uses cookies to ensure you get the best experience on our website. Check our privacy policy and