One AI experience — across every MSCI product.
How I led the design team in building MSCI's AI Design System from the ground up — turning a dozen competing AI experiments into a single, ownable AI language, the way Copilot is unmistakably Microsoft.
A shared language for AI at MSCI.
The MSCI AI Design System is the single source of truth for how every AI experience — chatbots, copilots, agents, AI-assisted flows — looks, behaves, and feels across the company. One system, unique to MSCI, adopted by product, engineering, and design.
Everyone was building their own AI.
Product teams across MSCI had an urgent, escalated need: ship AI capabilities fast to win a competitive edge. So each one started building — and each built a different AI.
The race to market created a quiet liability. Divergent AI journeys, visual styles, and interaction patterns were multiplying across product lines — every team reinventing the same chatbot, none of them recognizably MSCI.
The fragmentation
Scattered. Inconsistent. Off-brand.
Unified. Consistent. Ownable.
Stepping in with a point of view.
When the need escalated to leadership, I didn't wait for a mandate. I brought a vision: MSCI shouldn't have many AIs — it should have one, and it should be unmistakably ours.
The brief wasn't "design a chatbot." It was bigger than that. If AI was going to show up in Private-i, Total Plan, Data Platform and beyond, it needed to feel like the same intelligence — a single personality, a single set of rules, a single visual signature. The way Copilot is to Microsoft, this would be to MSCI.
I framed the problem for leadership and product partners, secured buy-in, and set the design team in motion. The goal: not a one-off UI, but an owned, reusable AI design language — opinionated enough to be recognizable, flexible enough to live inside very different products.
We studied the best, then explored hard.
An industry benchmarking study anchored the work in evidence. It became a decision engine — every finding turned into a design hypothesis we could test, keep, or kill.
The question underneath every exploration was deceptively simple: where should AI live, and how should it behave? We ran the benchmarking findings through several rounds of design, pressure-testing four distinct directions with the team before the system took shape. Here's the trail — what we tried, and why each survived or got parked.
The directions we explored
One question, one principle. The directions converged on a single answer — one behavior, many surfaces — which became a core rule of the system: panel by default, inline when light, full-screen when deep.
The full field
Founded on real use cases. The explorations were never a styling exercise — every direction was tested against real asks from business units and product teams across the enterprise. That grounding is what took us beyond a single AI icon to a scalable component library: one system any team can build on, from an in-app AI insight to a full conversational chatbot.
The MSCI AI Design System.
The explorations converged into a real, documented system — principles, foundations, and a component library purpose-built for AI experiences and ready for teams to build on.
A system, not a screen. Documented foundations and a reusable component library — the difference between a one-off design and an asset the whole company can build on.
One template for every chatbot at MSCI.
The system's centerpiece: a Conversational AI master template that any product can adopt — the canonical blueprint for chatbot experiences company-wide.
Natural-language entry.
A consistent prompt surface with suggested starting points, so users always know how to begin — and the experience feels the same in every product.
Grounded, cited responses.
Streaming answers with sources and confidence built in — the trust patterns from the system applied consistently, every time.
Panel to full report.
The same surface stretches from a quick side-panel reply to a full, structured report — one template, many intensities of work.
The blueprint. Adopt the template, plug in your product's data, and ship a chatbot that's instantly consistent with every other AI experience at MSCI.
From system to shipped.
A design system only matters if teams build on it. Working cross-functionally with engineering, we proved it twice — AskDocument and AskTPM — and set the pattern for rollout across every vertical.
"When AskDocument and AskTPM feel like the same product, that's the system working. The win isn't a single chatbot — it's that the next ten teams won't have to start from zero."
What changed.
Not just a chatbot shipped — a way for the whole company to build AI.
The deeper shift is cultural. Teams that were each solving AI alone now start from a shared foundation — faster to market, and recognizably MSCI when they get there. The design system turned AI from a per-team scramble into a company-level capability.
That's the role of design systems leadership: not to design every screen, but to make the right design the easy default — at scale, across products, for teams I'll never sit next to.