AI Enablement Lead

People Ai Enablement Lead

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish. The people here at Apple don't just craft products - they build the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts.

The People Technology team is looking for an AI Enablement Lead to partner with our business owners and engineering teams on re-engineering processes using new emerging technology. This role sits squarely at the intersection of business strategy, technology, process design, and applied AI. The ideal candidate combines operational judgment with technical fluency — understanding both the realities of People processes and the practical considerations required to deploy AI-enabled workflows responsibly at enterprise scale.

This is a high-ownership, high-visibility role that will help influence how the People organization evolves its operational model over time.

• Conduct structured assessments across People functions to identify workflows where AI-enabled automation can deliver meaningful improvements in user experience, effectiveness, scalability and accuracy
• Evaluate opportunities based on operational leverage, business value, process complexity, risk profile, governance considerations, and measurable impact
• Identify repetitive manual work, operational bottlenecks, fragmented workflows, and high-volume process areas suitable for intelligent automation
• Build and maintain a prioritized backlog and roadmap of AI deployment opportunities tied to clearly defined operational KPIs and business outcomes
• Map structured and unstructured data flows across enterprise platforms including Workday, Service Now, People EDW, collaboration platforms, project management tooling, and knowledge repositories
• Define human-in-the-loop review checkpoints, escalation paths, auditability requirements, and governance controls within deployed workflows
• Configure and operationalize AI-enabled workflows using APIs, MCP servers, orchestration tooling, integration layers, and enterprise operational platforms
• Translate operational requirements into scalable production-ready solutions with appropriate safeguards, monitoring, documentation, and support models
• Ensure deployed solutions remain maintainable, supportable, and operationally sustainable over time
• Operate and monitor deployed agents and AI-enabled workflows against defined operational KPIs including cycle time, exception rates, accuracy, reliability, adoption, and workflow quality
• Manage evaluations, regression testing, and workflow validation following significant model updates, schema changes, process modifications, or operational dependency changes
• Maintain operational documentation including workflow maps, data lineage, escalation models, governance considerations, and change logs
• Partner cross-functionally with People team leadership, operations teams, engineering, governance, security, and platform teams to ensure deployed workflows align with enterprise standards and operational controls
• Surface emerging automation opportunities as operational needs and organizational priorities evolve
• Drive iterative improvement of deployed workflows through operational feedback loops, usage patterns, testing, and ongoing refinement
• Support adoption of AI-enabled workflows through rollout planning, stakeholder engagement, operational enablement, documentation, and training support
• Establish and maintain People-specific knowledge repositories including process documentation, operational narratives, runbooks, LOB context, and workflow guidance
• Ensure knowledge assets remain current, governed, and accessible in ways that improve both workflow reliability and team self-service capabilities
• Contribute to operational best practices for deploying AI-enabled systems responsibly within enterprise People environments