AI Adoption & Community Enablement Lead

troweprice; United States; On-site; USD 180,000 - 260,000; Full time

Job summary

At T. Rowe Price, the AI Adoption & Community Enablement Lead will build the human capabilities required for Global Distribution Associates to use artificial intelligence effectively, responsibly, and increasingly sophisticatedly in their work.

Reporting to the Director, AI Enablement & Ecosystem, this role will own the scaled AI adoption and community strategy across GD, including learning pathways, platform adoption, the AI Champions Network, manager enablement, and communities of practice for

Qualifications

• Experience defining AI learning strategies for enterprise audiences.
• Ability to translate AI capability into scalable learning programs.
• Strong collaboration with product, HR, and leadership teams.

Responsibilities

• Own the global distribution AI learning roadmap and capability-building plan.
• Define role-based AI learning pathways and practical enablement content.
• Lead adoption efforts for major AI platforms and capabilities.
• Develop manager enablement and communities of practice for AI.
• Coordinate with enterprise L&D and platform owners for content reuse.

Skills

AI strategy

Learning & development

Cross-functional leadership

Change management

Job description

At T. Rowe Price, we identify and actively invest in opportunities to help people thrive in an evolving world. As a premier global asset management organization with more than 85 years of experience, we provide investment solutions and a broad range of equity, fixed income, and multi-asset capabilities to individuals, advisors, institutions, and retirement plan sponsors. We take an active, independent approach to investing, offering our dynamic perspective and meaningful partnership so our clients can feel more confident.

We believe doing the right thing for our clients and our associates is good business . With a career at the firm, y ou can expect opportunities to create real impact at work and in your community. Y ou'll enjoy resources to support your career path, a s well as compensation , benefits , and flexibility to enrich your life. Here, you'll find a collaborative culture that respect s and valu e s differences and colleagues who share a spirit of generosity .

Join us for the opportunity to g row and make a difference in ways that matter to you .

Role Summary

The AI Adoption & Community Enablement Lead will build the human capabilities required for Global Distribution Associates to use artificial intelligence effectively, responsibly, and increasingly sophisticatedly in their work.

Reporting to the Director, AI Enablement & Ecosystem, this role will own the scaled AI adoption and community strategy across GD, including role-based learning pathways, major platform and capability adoption, the AI Champions Network, manager enablement, communities of practice, and ongoing learning and reinforcement.

The role will partner with AI Product Managers, the Applied AI & Implementation team, the AI Ecosystem & Distributed Innovation Lead, business leaders, Human Resources, Learning & Development, and enterprise AI teams to ensure learning keeps pace with rapidly evolving capabilities and translates into sustained changes in how work gets done.

Success will be measured not simply by training participation, but by increased proficiency, adoption, effective use of AI, and the development of a distributed network of Associates capable of helping others identify and implement AI-enabled improvements.

Responsibilities

AI Learning & Capability Strategy

Own the GD AI learning and capability-building roadmap, aligned to the GD AI strategy and evolving enterprise AI ecosystem.

Define the AI capabilities expected across different roles and proficiency levels, from foundational literacy through increasingly advanced use of reusable workflows and AI solutions.

Develop practical role-based learning pathways using a mix of self-directed learning, live sessions, hands-on labs, office hours, examples, and peer learning.

Coordinate with enterprise Learning & Development teams and AI platform owners to leverage firmwide content while addressing GD-specific needs.

Platform & Capability Adoption

Lead the business-side enablement and adoption plan for major AI platform launches, migrations, and new capabilities.

Partner with product and technology teams to sequence learning, communications, and readiness activities with capability releases.

Develop manager enablement and reinforcement approaches that help new ways of working persist beyond initial training.

Identify populations or functions where adoption is lagging and develop targeted interventions to address barriers.

AI Champions & Community

Own and continuously evolve the Global Distribution AI Champions Network.

Establish clear expectations, playbooks, operating cadences, learning opportunities, and support for Champions.

Coach Champions and provide mechanisms for them to exchange best practices, surface opportunities and barriers, and support adoption within their functions.

Partner with the AI Ecosystem & Distributed Innovation Lead to help Champions identify promising Associate-built solutions, spread reusable capabilities, and expand the community of AI creators.

Coordinate broader communities of practice and peer-learning mechanisms that accelerate shared learning across GD.

Learning Experiences, Showcases & Storytelling

Curate a recurring calendar of AI learning and engagement experiences, including demos, showcases, workshops, office hours, and targeted learning events.

Partner with Product Managers, Implementation Pods, AI Champions, and Associate builders to turn successful use cases into practical examples others can understand and replicate.

Develop communications and learning content that make AI approachable, relevant, and grounded in real GD workflows.

Capture and spread lessons learned, emerging best practices, and examples of measurable impact.

Measurement & Continuous Improvement

Establish measures of participation, adoption, proficiency, community engagement, and learning effectiveness.

Use qualitative and quantitative feedback to identify gaps in Associate capability and improve learning programs over time.

Partner with the AI Portfolio,