Since Human Help was a legacy capability, I began by establishing a baseline understanding of how customers experienced escalations and transitions to human support.

Through foundational research with 16 participants, I uncovered four insights that ultimately reframed the opportunity and redefined the role of human help.

One finding changed the direction.

I expected AI to step aside once a human joined.

Instead, 14 of 16 participants preferred the assistant to remain visible, showing that continuity, not replacement, builds trust.

The experience needed to work across products, expert types, service tiers, and channels.

Rather than designing for a single use case, I created a configurable framework that products could adopt while preserving a consistent customer experience.

The strongest direction became a shared connection space where customers stayed inside the experience while AI coordinated access to the right expert.

Because no single team owned the end-to-end experience, I used demos, coded playgrounds, and workshops to align product, platform, AI, and service teams around a shared vision.

The shared vision accelerated adoption across multiple Intuit products.

Because no single team owned the end-to-end experience, I used demos, coded playgrounds, and workshops to align product, platform, AI, and service teams around a shared vision.

The shared vision accelerated adoption across multiple Intuit products.

As AI became more capable, some larger question emerged.

Should human expertise appear only when AI fails?

When Ai becomes the interface, where should human expertise exist?

The work evolved from improving handoffs to defining a new model where AI and human expertise collaborate throughout the customer journey.