Accenture AI

Data visualisation & AI hub

The AI Community Explorer title, set in pink and white across a deep violet field.

AI Community Explorer is an enterprise knowledge platform designed to map, connect, and scale Accenture's artificial intelligence initiatives globally. The work covers wireframing through to final high-fidelity UI, built in close collaboration with UX and product stakeholders. The ecosystem delivers a dynamic internal hub connecting global AI specialists, alongside a structured repository for enterprise case studies.

Client
Accenture
Role
Product Design
UI Design
Interaction Design

AI Explorer: Interactive Prototype

The Explorer uses dynamic data visualisation to reveal complex relationships between AI initiatives — designed at the intersection of logic and fluid interaction. As a personal extension of this case study, I designed and built a fully interactive version of the Explorer — from interface to functional prototype — using Claude Code.

Launch Prototype

Enterprise Scope: Tailored strictly for desktop environments and professional workflows. Minimum width: 1024px.

The Explorer Layer

To manage extreme data density, the UI employs a dual-experience framework: a macro-level visual map revealing the entire Accenture AI ecosystem at scale, paired with a micro-level utility interface for frictionless, deep-dive navigation into granular topic content.

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UI foundations

Early user interface mapping the platform's data structure.

The first map: every AI capability set out in rings around four organisational groups.

Visualising how initiatives, specialists, and resources connect to each other

The finished map with one initiative selected, its connections drawn out to the capabilities it touches and the panel open beside it.

Contextual panel

To maintain orientation within a dense data map, each node opens a contextual side panel — surfacing key insights and related resources without breaking the user's flow.

The contextual panel in full: the capability and what it covers, the assets counted and linked, then its credentials, the experts behind it, and the clients it has been delivered for.

Designing for Power Users

Built for technical experts already fluent in the domain, the interface skips traditional onboarding — prioritising fast access to the platform's navigation mechanics over guided introduction.

The welcome card: an introduction to the AI Community, with Get started and Skip tour.

Assets layer

The Assets Layer shifts focus to pure utility, turning a large database into an easy-to-navigate repository. Early wireframes introduced 'narrative filtering' — letting users surface assets through natural, contextual search rather than rigid dropdown menus.

The wireframe of the assets browser: a directory on the left and a filter written as a sentence across the top.

Assets Layer: UI Components

The Assets Directory: A centralised, high-density index designed for discovering AI tools and resources across the global ecosystem.

The assets directory: rows of cards under each capability, filtered by strategy, objective and purpose.

The Experts Directory: A streamlined index mapping internal AI specialists by domain expertise and business unit.

The experts directory: a lead specialist at the top, then the domain and location leads beneath, filtered by domain and region.

The Events Directory: A utility-first interface for tracking, filtering, and enrolling in upcoming global AI initiatives.

The events directory: a month of talks and webinars listed by date, each with a place and a way to add it to a calendar.

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This work is covered by a confidentiality agreement. The full case study is shared by an access key.

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