AI Hub

The AI Hub serves Customer Service teams worldwide. My part covered research, design, and implementation, working alongside the product manager, project team, and software engineers.

As an enterprise tool used across the organization, it had to meet accessibility requirements, and I accounted for accessibility throughout the design.

Too many new tools, too little clarity.

New AI tools were being introduced company-wide almost every week. Employees in Customer Service struggled to find the right tool for their job and were unsure what to use.

The starting point was broad: tool overload and confusion. I created the AI Hub platform and owned the user experience end to end, from user feedback and research through design to implementation, for a worldwide audience.

The problem surfaced in two places: in leadership programs, and in feedback users shared with facilitators. Agents, tools, and apps were being created across the company, often duplicating each other, and people weren’t sure what to use whenever a new one appeared in their team or elsewhere.

Start from the job, not the tool.

I gathered user feedback and researched Customer Service job roles to define which tools and content each audience needed. That work shaped the structure of the hub around roles.

I stayed involved through implementation to keep the build aligned with the approved design, and briefly took over front-end updates to implement the design myself.

One hub, familiar patterns.

I designed the complete feature suite for the hub. Employees can find a curated list of tools for their role, open tool-specific pages with use cases and training videos, read reviews, and collaborate in community spaces.

I designed the experience to be relatable to existing hubs while staying distinct and specific to the organization and its needs.

Each tool has its own page: setup steps to get started, key features, supported use cases, success stories, and training resources. Ratings, target roles, and related tools sit alongside, so people can judge quickly whether a tool fits their work.

An About page sets out the hub’s mission and vision, and what it offers: curated AI tools, a community of people sharing what works, practical guidance for each tool, and a quality bar every tool is evaluated against.

Branding. The hub had to stay within the Customer Service branding, so I worked within it rather than giving the hub a look of its own.

The built-in assistant. An assistant built into the hub was explored as an experiment. The team later decided it wasn’t necessary, which kept the hub focused on helping people find and learn the right tools.

Recognize the people who share what works.

An AI Champions leaderboard celebrates contributors. People earn points for reviews and the tools they use, collect badges such as Community Champion, AI Pioneer, and Tool Master, and can view the rankings for all time, by month, or by week, for technical and non-technical roles. A nomination button invites people to recognize a leader who inspires them. These features came out of wider team discussions, and I designed how they work in the hub.

A later version of the home page brings points, a community pulse with the topic of the week, AI events, and learning paths onto the first screen.

Help people use AI well, not just find it.

A Responsible AI page explains why AI ethics matters and sets out clear do’s and don’ts, such as fact-checking outputs, combining AI with human judgment, and never sharing sensitive data. It links to the internal AI policy resources for anyone who wants more detail. The idea came out of wider team discussions, and I designed the page.

A way to add tools with care.

A hub stays useful only if new tools are added thoughtfully. The project manager and project team defined the governance model, including a request-and-review mechanism with approval criteria.

I designed the in-product flow that supports it: a smooth path for admins to review submitted tool requests and approve them against the criteria, including role eligibility approvals.

Shaping this flow alongside the governance model influenced how new tools are introduced and reviewed.

A trusted place to start.

The AI Hub gave the worldwide Customer Service organization one trusted place to discover relevant AI tools and learn how to use them.

Leaders approved the designs before handoff, and the build was developed with engineering to match them.

End to end ownership, research-driven design, leadership buy-in, and hands-on collaboration with engineering to deliver a curated, governed tool hub for a global audience.