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 find solutions relevant to their work.
• Build a strong community of AI-forward builders and power users who help expand innovation beyond the capacity of the central team.

Mindset

• Highly AI-forward, curious, and hands-on; learns new capabilities by experimenting with them.
• Product thinker who obsesses over users, quality, adoption, and continuous improvement.
• Natural evangelist who can create energy while remaining grounded in practical business value.
• Comfortable balancing rapid innovation with enterprise risk and control requirements.
• Believes the central team should create more capable builders across the organization rather than become a bottleneck for innovation.

Qualifications

Required:

• Bachelor's degree or equivalent experience in business, technology, product management, information systems, or a related discipline and 8+ years of related experience
• Experience in AI/digital product management, innovation, emerging technology, transformation, or related roles.
• Strong hands-on understanding of generative AI, LLMs, agentic workflows, prompt/instruction design, reusable AI capabilities, and evaluation approaches.
• Demonstrated ability to identify user needs and translate emerging technology into practical products or business capabilities.
• Strong communication and presentation skills, with an ability to engage both technical specialists and broad business audiences.
• Experience working across business, technology, data, and risk stakeholders.
• Builder mindset with demonstrated ability to create new capabilities or programs from the ground up.

Preferred:

• Experience developing or managing platform ecosystems, marketplaces, developer communities, or reusable enterprise capabilities.
• Product-management experience in complex enterprise environments.
• Familiarity with AI governance and responsible AI practices.

FINRA Requirements

FINRA licenses are not required and will not be supported for this role.

Work Flexibility

This role is eligible for hybrid work, with up to one day per week from home.

Base Salary Ranges

Please review the job posting for the location of this specific opportunity.

Placement within the range provided above is based on the individual’s relevant experience and skills for the role.  Base salary is only one component of our total compensation package.  Employees may be eligible for a discretionary bonus, which is determined upon company and individual performance.

Benefits