Internal Visionary Concept • AI

AI-assisted employee learning

A strategic exploration of how to leverage unified internal data to direct ServiceNow Sales team members to impactful first- or third-party ai-powered learning experiences.

This project explored how AI-assisted learning could better support employees navigating complex systems and unfamiliar workflows. Rather than designing a single feature, the focus was on understanding how learning, guidance, and intent could be more naturally integrated into everyday work.

The problem

Executive pressure to deliver a next-generation, AI-assisted learning tool came without clear direction. At the same time, many partners were unaware of the foundational changes already underway in our back-end systems that would ultimately enable this new effort.

Instead of starting with a predefined solution, my work focused on clarifying those underlying data and platform changes, while applying emerging pattern thinking to align partners, reduce knowledge gaps, and define an iterative, system-based approach. This resulted in a shared vision presented to executive leadership and the global Sales organization in Fall 2025, outlining a clear and achievable path forward for employee learning integrated with a single internal data source.

Timeline

1 month

Role

Project lead

Type of work

Vision

Audience

Executives & Internal Sales teams

Strategic Planning

The following artifacts were created to clarify how a highly personalized AI experience could be powered by data flowing across disparate back-end services.

This work informed a series of low-fidelity animations that blended familiar ServiceNow interaction patterns with a strategic lens, making complex architectural concepts more approachable and illustrating an iterative path toward realizing the vision outlined in the next section.

Architecture mapping

Prior to this work, product teams had limited visibility into how underlying systems and data needed to be leveraged, creating a risk that strategic decisions would be made on incomplete assumptions and lead to downstream churn.

Current state

Transitional state

Emerging state

These graphics and animations marked SNU’s first attempt to connect executive vision with emerging patterns across the organization and the realities of back-end systems. Together, they reframed the work into a more cohesive and attainable direction.

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