[Case 01]
Accenture Gen-Ai Navigator Platform
Enterprise Internal Application
[ Impact ]
[Project Overview]
Accenture AI Navigator is an internal, executive-facing Generative AI platform built to support subject matter experts (SMEs) and senior leaders during high-stakes client engagements. The platform consolidates fragmented internal knowledge GenAI usecases, solution frameworks, product capabilities, and prior deliverables into single, intelligent interface.
Designed for real-time use, AI Navigator helps consultants quickly surface relevant insights, structure conversations, and respond confidently to client needs without disrupting the flow of discussion. The experience prioritises clarity, speed, and low cognitive load, ensuring the tool fits naturally into existing consulting workflows rather than demanding attention of its own.
[My Role]
Lead Product Designer (UX Lead)
[Platforms]
Internal Enterprise Platform
[Problem Statement]
[Process]
Due
[ Users & Context ]
The primary users were senior ( Subject Matter Experts ) SMEs and executives responsible for leading client conversations, identifying pain points, and proposing tailored solutions. These users typically operate in high-pressure environments such as live meetings and workshops, often while managing multiple tools, documents, and inputs simultaneously.
In this context, the platform was not a primary workspace but a supporting system used alongside presentations, notes, and real-time discussion. Speed, clarity, and trust were critical, while complex interactions or dense visual elements risked becoming distractions.
[ Design Goals ]
The design focused on enabling experts to stay present in conversations while accessing relevant information seamlessly.
Reduce cognitive load during live usage
Surface insights and assets instantly
Support confident, real-time decision-making
Maintain a high level of clarity and trust
Fit naturally into existing consultant workflows
[ Approach ]
Given the executive nature of the users and limited availability for structured research, the design process prioritised contextual understanding and iterative validation. Inputs from stakeholders, usage patterns, and real working environments informed design decisions.
The approach emphasised practicality over novelty focusing on how the platform would be used in real moments rather than how it appeared in isolation.
[ Solution ]
The final solution was a streamlined, lightweight GenAI interface designed to function as a glanceable assistant rather than an immersive application. Key elements included:
A minimal, distraction-free layout
Large, readable typography for at-a-glance consumption
“Battlecard” style summaries with key talking points and assets
Simplified navigation and reduced interaction depth
Voice-first and hands-free interaction where appropriate
The design intentionally removed unnecessary visual complexity to prioritise speed and usability in live settings.
[ Solution ]
Designing for expert users requires a deep understanding of context, not just tasks. In high-stakes environments, the most effective design is often the one that stays out of the way supporting thinking, reducing friction, and enabling confidence without demanding attention.
This project reinforced the importance of clarity, restraint, and workflow-first thinking when building enterprise AI products.
[Persona]
Ryan Fransis
Subject matter Expert
Age: 29
Location: New York City
Tech Proficiency: Moderate
Gender: Male
[Goal]
Quickly complete purchases without interruptions.
Access accurate product details and a seamless payment process.
Trust the platform with his payment and personal information.
[Frustrations]
Quickly complete purchases without interruptions.
Access accurate product details and a seamless payment process.
Trust the platform with his payment and personal information.
[Process]
[Outcome]
25% increase in checkout completion rates.
30% reduction in cart abandonment on mobile devices.
30% reduction in cart abandonment on mobile devices.
[Key Learnings]
[Key Learnings]