CLIENT

Accenture

ROLE

Design & Delivery Lead

TEAM

• Design Director
• 3x UX Designers
• Technical Lead
• 15+ Engineers

DURATION

32 Weeks

BUDGET

2M

PROJECT OVERVIEW

Accenture’s Global Strategy team and Energy Resources practice required a suite of generative AI-powered applications to streamline workflows, improve knowledge retention, and generate high-value data outputs. The goal was to build multiple interconnected tools that could provide dynamic outputs tailored to the needs of different user groups ranging from analysts to executives, while centralizing knowledge and insights across the whole organization.

The project aimed to showcase innovation in strategic planning through AI, by reducing inefficiencies in data research, output creation, and project scoping. These tools would serve as internal accelerators for client-facing teams, enabling faster, smarter, and more consistent value delivery across global engagements.

CHALLENGE

Accenture needed a solution that could unify and extract value from a broad range of structured and unstructured data sources. The applications had to surface insights that could inform capital allocation, strategic forecasting, and project planning while still accommodating diverse user roles and data access levels.

Additional goals included:

• Reducing manual data collection and synthesis across teams
• Accelerating research, proposal generation, and executive decision support
• Improving internal consistency in strategic modeling and communications
• Supporting global collaboration while enforcing security and governance.

APPROACH

With minimal initial requirements, the team leaned into a discovery-led approach, prioritizing pain points and use cases identified through extensive stakeholder interviews. Each product was aligned to a distinct user goal and anchored by high-value outputs rather than just replicating existing workflows.

Key efforts included:

• Conducted in-depth discovery and stakeholder interviews to define product goals
• Defined six product tracks, each addressing a specific task area (e.g., asset planning, knowledge management, research synthesis)
• Designed a single, cohesive visual system and component library to be used across all tools
• Established pods for engineering and design with shared ceremonies to ensure consistency and velocity
• Integrated GenAI agents into each tool as a primary interaction model (supporting intelligent inputs, summaries, recommendations, and deliverable generation)
• Implemented dynamic outputs based on user permissions, including PPT decks, PDFs, Excel files, charts, and self-service content.