Workforce Transformation Platform (Consulting Firm)

Lead • UX Lead • Ongoing

The client is building their own workforce transformation suite to reduce reliance on external tools. Several services are already live within the organization and continue to evolve through sprint-based improvements, managed by multiple PMs.

I joined four months ago at the start of their GenAI initiatives, when cross-functional teams came together to explore how agents and generative AI could enhance workforce planning and analytics.

The immediate need was to design a GenAI MVP that could adapt across different workforce use cases, integrate with the existing suite, and serve as a foundation for testing model performance. The challenge was to make the concept ambitious enough to demonstrate AI’s potential while simple enough for teams to adopt, test, and iterate on quickly.

As the design lead for this engagement from Dentsu, I was responsible for defining and prototyping this MVP concept.

My Role & Challenge

An interaction model that let users explore data through conversations, organize insights into boards, and generate presentation-ready reports. This created a clear, coherent workflow that resonated with teams.

Concept

Created a demo prototype to helped teams validate the concept and bring it to life for key stakeholders.

Showcased the end-to-end flow and secured alignment to move forward with design and implementation.

Demo

For the MVP, we set up one conversation linked to one board per survey, giving coaches and teams a focused flow to sharpen insights, test ideas, and improve outcomes.

I adapted the existing design system to ensure visual consistency and accelerate development handoff.

Design handoff

With the MVP now in build, along with supporting teams on this project I’m also responsible for driving improvements across the broader suite of services.

I work with multiple PMs to refine workflows, document design standards, and run workshops that explore deeper integration of AI capabilities. My current focus spans data preparation, diagnostics and analytics, and scenario tracking ensuring each stream benefits from consistent design and scalable AI-native patterns.

Status quo

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