AI Adoption & Internal Capabilities Senior Lead

Wells Fargo & Company•Charlotte, NC

1d•Hybrid

About The Position

The AI Adoption & Internal Capabilities Senior lead plays a critical execution role in scaling AI adoption across CBL. Reporting to the Director, AI Adoption and Internal Capabilities, this role is responsible for translating AI adoption strategy into action—driving enablement, coordinating tool rollouts, tracking adoption and impact, and supporting change management across teams. The Senior Lead operates as a hands‑on orchestrator, ensuring AI tools are embedded into day‑to‑day work in measurable, repeatable, and responsible ways. Learn more about the career areas and lines of business at wellsfargojobs.com.

Requirements

7+ years of Artificial Intelligence Solutions experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
7+ years of experience in managing large scale adoption programs (or equivalent practical experience)

Nice To Haves

Experience driving enterprise technology or AI adoption, change management, or enablement initiatives at scale, ideally within a large, matrixed organization.
Strong analytical and execution skills, with the ability to translate usage data and qualitative feedback into clear insights and recommendations for leaders.
Demonstrated ability to partner effectively across business, product, technology, analytics, and learning teams to deliver outcomes in a fast‑moving environment.
Previous AI solutions experience in Financial Services is preferred but not required

Responsibilities

Operationalize the Director’s AI adoption strategy by driving day‑to‑day execution of priority initiatives across CBL.
Coordinate rollout of approved AI tools and platforms (e.g., M365 Copilot and role‑based AI tools), partnering with enterprise AI, technology, and business teams to support readiness and adoption.
Execute role‑based AI enablement activities, including training sessions, office hours, playbooks, and communications, ensuring content is practical, actionable, and aligned to real workflows.
Serve as a primary point of contact for CBL teammates adopting AI tools—answering questions, resolving blockers, and reinforcing responsible AI practices.
Track and analyze AI adoption, usage, and engagement metrics across tools, roles, and lines of business, surfacing trends and insights to inform leadership decisions.
Partner with analytics, product, and enterprise AI teams to translate usage data into clear, business‑relevant insights tied to productivity and value realization.
Prepare recurring adoption dashboards, executive summaries, and readouts for the Director and senior stakeholders, highlighting progress, risks, and recommended actions.
Identify gaps in adoption or capability enablement and propose targeted interventions to improve outcomes.
Support the day‑to‑day operations of the CBL AI community of practice, including AI Champions engagement, forums, and knowledge‑sharing routines.
Capture and synthesize frontline feedback, success stories, and lessons learned to continuously improve enablement approaches and normalize AI usage.
Contribute to development and maintenance of AI adoption playbooks, FAQs, and reusable assets that accelerate consistent adoption across teams.
Support AI use case intake, triage, and tracking processes by coordinating inputs, documenting requirements, and maintaining visibility into status and outcomes.
Help connect related use cases and adoption efforts across teams to encourage reuse, reduce duplication, and accelerate learning.
Partner with business, product, and data teams to ensure adoption considerations (training, readiness, measurement) are embedded into AI solutions from the start.
Work closely with product, engineering, data science, learning, and enterprise AI partners to ensure adoption and enablement efforts are tightly coordinated.
Demonstrate strong execution discipline by managing dependencies, timelines, and deliverables across multiple concurrent adoption initiatives.
Proactively identify risks, constraints, or change‑management challenges and escalate with clear recommendations.
Build deep fluency in AI tools, enterprise AI direction, and CBL business priorities to effectively support adoption at scale.
Act as a trusted extension of the Director—representing the adoption agenda in working sessions, forums, and execution‑level discussions.