Senior Director, AI Enablement & Adoption

Mosai•Nashville, TN

2d•Hybrid

About The Position

This role exists to get AI into productive, safe, everyday use across the company. Success is measured in real usage doing real work, not in pilots launched.

Requirements

6+ years in technology, data, product, or operations, including 2+ years leading a program that changed how a large group of people work.
Hands-on fluency with current AI tooling: assistants, agents, retrieval, prompt and context engineering, and the limits of each. This person builds the workflow, not just the deck about it.
A track record of adoption measured in usage and outcomes, driven across teams that do not report to you.
Working knowledge of AI risk and data handling in a regulated environment, including HIPAA and SOC 2 in practice.
Can teach. Can make a skeptical, non-technical audience competent with tools they did not ask for.

Nice To Haves

AI or automation adoption inside healthcare or another regulated environment.
Familiarity with clinical or revenue-cycle workflows.
Experience building training programs or a community of practice at scale.

Responsibilities

Own the enterprise AI adoption plan: which functions adopt what, in what order, with a named sponsor in each and outcomes stated in cycle time, cost, or quality.
Run enablement end to end; role-based training, workflow playbooks, office hours, and a champions network, so capability spreads without routing through you.
Find and land high-leverage internal automation across support, revenue cycle, clinical operations, finance, and go-to-market. Prove it with the function that owns the work, then hand off a supported workflow.
Curate the approved AI toolset for employees. Recommend additions and retirements, and make the case with usage evidence and ROI analysis.
Measure adoption and report it monthly to function leaders, quarterly to the executive team.
Provide direct leadership and supervision to a team.
Own the employee AI acceptable-use policy: what data goes in which tools, what needs review, what is prohibited. Short enough that people follow it.
Create and maintain approval path and register for employee-facing AI tools, run with Security, Legal, and Compliance.
Manage data-handling rules for internal AI use, including PHI, retention, and whether our data trains a vendor model developed in collaboration with Security and Legal.
Lead training, attestation, and misuse escalations. Internal AI risk feeds the enterprise risk process owned by Security and Compliance.
Maintain partnerships with functional-area leaders on use case selection and the time their teams need to adopt.
Partner with IT and Security on identity, access, licensing, and monitoring.
Closely partner with Legal and Procurement on vendor terms, BAAs, and data-use commitments.
Work closely with Product and Engineering teams building customer-facing AI, who get enablement assets and expertise from this role. They own that governance; this role does not.