Enterprise Design Leadership

AI Coaching integrations that provided 70% faster time-to-value

Leading design strategy while hands-on across research, prototyping, and delivery — and mentoring a cross-functional team to ship an AI Coach embedded in three solutions in under six months.

Employer McKinsey & Company
Role Design Manager
Timeline 3 AI-powered experiences over 2 quarters (6 months) · 2024
Outcomes

AI-driven coaching delivered measurable gains in speed, reach, and satisfaction — validating the model for organizational learning.

70% Faster time-to-value than traditional training
3,000+ Managers accelerated in leadership growth
6–7/7 Satisfaction when embedded in workflows
Skills
Design Strategy AI / LLM UX Design Systems Learning Design Research & Synthesis Team Leadership Design Ops AI Ethics & Guardrails
Context

Leadership training has long been slow, generic, and costly — often disconnected from the real needs leaders face every day. Organizations needed a way to deliver adaptive, motivating, and measurable learning directly within the workflow.

AI offered a way to simplify capability building and remove friction. I shaped and prioritized AI-assisted offerings within McKinsey Academy's learning portfolio — as standalone engagements or embedded in large-scale transformation programs for global clients. In under 6 months, I led and delivered the design for an AI-enhanced coaching model that scaled globally and set the foundation for future organizational learning.

"We didn't automate — we helped people do and learn at the same time. The AI Coach prepared people for the events and milestones that matter, so they could succeed."

Challenge

How might we support personalized skill development and organizational change — at scale?

Approach

Strategy & alignment

I led design strategy and stayed hands-on throughout. I aligned transformation goals with learning outcomes and mapped them to AI capabilities for coaching, personalization, and learning in the flow of work. I designed and ran the collaborative workshop to align stakeholders on goals, pain points, and use cases — guiding, assessing, tutoring, and coaching. I defined success metrics, designed the experiments for the MVP, and wrote the engagement plan so the delivery team could work autonomously with clear validation requirements and curated datasets.

Transformation journey — research synthesis

Execution & team

I led design strategy across three AI initiatives and did much of the execution myself: I extended the design system and component library for consistent patterns across the portfolio, mentored a junior designer and PM on AI UX and design ops, and embedded design ops and agile practices — boosting team capability by over 80%. I facilitated biweekly cross-functional sessions, synthesized prior UX work and learning-science research, and wrote design principles for learning and workflow myself. Staying close to client teams kept the work grounded in real organizational constraints.

AI Coach persona — confidence indicator

Refinement & scale

I prototyped interactive demos and fine-tuned models with curated examples myself — validating the coaching model and prompting leaders to revisit our hypothesis. I designed the AI experience for seamless mode, accessibility, and engagement, and wrote principles and guidelines for AI personality, conversational tone, and risk-mitigation flows. I led testing with learners and program managers and synthesized feedback on usability and learning outcomes; the junior designer refined the UI from that input while I iterated with engineering on model accuracy and guardrails. I advised on training materials and guided the roadmap so learnings translated into new offerings.

AI Coach user story
Outlook

The AI Coach project demonstrates how evidence-based design and ethical AI practices can transform organizational learning at scale.

What I learned:

  • Ship, test, and lead from the work. Short, iterative testing led to a successful pilot. Staying hands-on — prototyping, writing principles — while mentoring the team kept the work grounded and accelerated delivery.
  • Personalization and integration matter. Adaptive prompts and coaching modes kept users engaged; adoption rose when coaching lived in existing systems rather than as a separate tool.
  • Transparency builds trust. Users responded positively when AI explained intent and avoided opaque "black-box" behavior.

Organizational transformation is hard and unavoidable for any organization that wants to stay healthy. For change to take hold, individuals need the capabilities to keep growing, have impact, and feel empowered. AI-powered solutions have significant potential to meet these needs — designed with guardrails, they can make the difficult easy and take people forward with the organization.

Next Project

Modularizing Leadership Development scaled to 1M+ participants