Morgan Stanley: Connecting AI Assistance to the Work Around Client Advice
Morgan Stanley’s published AI initiatives illustrate two connected design questions: how professionals find knowledge, and how meeting information becomes follow-up work.
Ask Dalí: Designing an AI Encounter Around a Cultural Experience
The Dalí Museum’s conversational installation offers a useful lens on how interface, cultural material, and visitor context can work together.
Who Owns the System After Launch?
A live system needs clear ownership for service quality, incidents, and change. Define how those responsibilities work across the business, developers, and vendors.
Before Development: The Architecture Decisions That Shape Cost and Change
System boundaries, vendor choices, and data ownership shape both development cost and future flexibility. Make the consequential trade-offs explicit before implementation gathers momentum.
Designing AI into the Customer Journey
AI can help customers discover, choose, and use a service. Its value depends on how well those moments connect across the customer journey.
Is Your System Ready for AI?
AI readiness depends on the application: whether data, integrations, permissions, and operating capabilities can support what the system is expected to do.
Where Should AI Assist—and Where Must People Decide?
Define what AI may recommend, what it may execute, and which decisions require human authority—before those boundaries are tested by a difficult case.
What Should a Pilot Prove Before You Scale?
A useful pilot tests whether a system can create value under real operating conditions—and provides evidence for the next investment decision.
From Knowledge to Action: What Makes a System Useful?
Useful systems connect reliable knowledge to the situations, decisions, and actions it should support.
Start with the Opportunity, Not the Tool
Before choosing a tool, clarify the need, the value worth creating, and the conditions required to make it work.