AI Ecosystem & Distributed Innovation Lead

troweprice; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

T. Rowe Price is seeking an AI Ecosystem & Distributed Innovation Lead to build and scale an environment that enables Global Distribution Associates to create reusable value with AI. Reporting to the Director, AI Enablement & Ecosystem, this role owns the strategy and operating model for Associate-built AI solutions.

The position applies a product-management mindset to identify high-value use cases, promote responsible sharing, and drive adoption of scalable AI capabilities across GD.

Responsibilities

• Distributed Innovation Strategy: Own the vision and roadmap for Associate-built reusable AI solutions across Global Distribution.
• Develop mechanisms that encourage broad experimentation and creation while focusing attention on recurring business needs and high-value use cases.
• Understand how Associates use available AI capabilities, identify patterns, and determine where central-team support improves quality or scale.
• Establish measures of ecosystem health, including creation, reuse, adoption, engagement, quality, and demonstrated business value.
• Reusable Solution Lifecycle: Build a scalable lifecycle to discover, assess, improve, validate, publish, promote, measure, maintain, and retire AI solutions.
• Identify high-potential Associate-created solutions and partner with creators to improve reliability and scalability.
• Develop clear standards for when a solution can be broadly shared or endorsed within GD.
• Define criteria and pathways for graduating solutions into AI products when usage, complexity, risk, data requirements, or business importance warrant greater investment.
• AI Ecosystem & Capability Roadmap: Understand enterprise AI platforms, tools, connectors, and emerging functionality.
• Identify gaps between available capabilities and the needs of Associates and reusable-solution creators.
• Translate gaps into clear requirements and roadmap priorities for Technology, Data, and platform providers.
• Evaluate new capabilities through practical experimentation and determine where they unlock meaningful new use cases or improve existing solutions.
• Responsible Scaling & Risk Management: Partner with Technology, Data, Risk, Legal, Compliance, and other control functions to establish guardrails for Associate-built AI solutions.
• Balance innovation and speed with management of operational, data, privacy, compliance, and AI-related risks.
• Identify systemic barriers to distributed innovation and work with enterprise partners to resolve them.
• Activation, Adoption & Community Engagement: Make AI capabilities understandable and exciting to Associates through examples, demos, showcases, experimentation, and practical storytelling.
• Partner with the AI Learning & Community Enablement Lead and AI Champions to identify creators, spread best practices, and drive adoption of high-value reusable solutions.
• Develop an internal discovery experience/catalog so Associates can find reusable AI solutions.

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 Ecosystem & Distributed Innovation Lead will build and scale the environment that enables Global Distribution Associates to create reusable value with AI.

Reporting to the Director, AI Enablement & Ecosystem, this role will own the strategy and operating model for Associate-built reusable AI solutions, including Skills, assistants, agents, templates, playbooks, and emerging capabilities made possible by enterprise AI platforms.

The role will apply a product-management mindset to the broader GD AI ecosystem: understanding what Associates are building and using, identifying the highest-value solutions, helping creators improve promising capabilities, developing approaches to validation and responsible sharing, expanding the enterprise toolkit, and making successful solutions easy for others to discover and adopt.

The role will also serve as a visible AI evangelist across GD, translating fast-moving technology developments into practical opportunities and creating excitement and momentum around what Associates can now accomplish.

Responsibilities

• Distributed Innovation Strategy: Own the vision and roadmap for Associate-built reusable AI solutions across Global Distribution. Develop mechanisms that encourage broad experimentation and creation while focusing attention on recurring business needs and high-value use cases. Understand how Associates are using available AI capabilities, identify common patterns, and determine where central-team support can significantly improve quality or scale. Establish measures of ecosystem health, including creation, reuse, adoption, engagement, quality, and demonstrated business value.
• Reusable Solution Lifecycle: Build a scalable lifecycle to discover, assess, improve, validate, publish, promote, measure, maintain, and retire reusable AI solutions. Identify high-potential Associate-created solutions and partner with their creators to improve reliability, usability, instructions, evaluations, documentation, and scalability. Develop clear standards for when a solution can be broadly shared or endorsed within GD. Define criteria and pathways for graduating successful solutions into targeted workflow interventions or formal AI products when usage, complexity, risk, data requirements, or business importance warrant greater investment.
• AI Ecosystem & Capability Roadmap: Maintain a deep understanding of enterprise-approved AI platforms, tools, connectors, agent capabilities, and emerging functionality. Identify gaps between available capabilities and the needs of GD Associates and reusable-solution creators. Translate those gaps into clear business requirements and roadmap priorities for Technology, Data, enterprise AI teams, Labs, and platform providers. Evaluate new capabilities through practical experimentation and determine where they can unlock meaningful new use cases or improve existing solutions.
• Responsible Scaling & Risk Management: Partner with Technology, Data, Risk, Legal, Compliance, and other control functions to establish practical guardrails for Associate-built reusable AI solutions. Help creators understand appropriate use of enterprise data, approved tools, validation expectations, and other relevant controls. Balance broad innovation and speed with appropriate management of operational, data, privacy, compliance, and AI-related risks. Identify systemic barriers to distributed innovation and work with enterprise partners to resolve them.
• Activation, Adoption & Community Engagement: Make emerging AI capabilities understandable and exciting to Associates through examples, demos, showcases, experimentation, and practical storytelling. Partner with the AI Learning & Community Enablement Lead and AI Champions to identify creators, spread best practices, and drive adoption of high-value reusable solutions. Develop an effective internal discovery experience or catalog so Associates can fin