Job Summary and QualificationsThe AI Enablement Lead drives practical, responsible, and measurable adoption of approved AI tools across the Human Resources Group. This role leads the HR AI enablement strategy, champion networks, use case intake, adoption measurement, and ongoing optimization of AI-enabled ways of working, including tools such as ChatGPT, MCP Servers and future AI capabilities embedded in enterprise and third-party applications.
This role is responsible for identifying, documenting, and prioritizing high-value AI use cases across HR, with a focus on measurable time savings, efficiency gains, accuracy improvements, adoption rates, user satisfaction, and business value. Based on this evidence, the AI Enablement Lead recommends which use cases should become Custom GPTs, automated workflows, reusable playbooks, training materials, or internal AI-enabled applications.
The AI Enablement Lead centrally maintains HR-owned Custom GPTs and AI enablement assets, manages access and license allocation to ensure the highest-value users retain access, and partners with HR, technology, product, privacy, security, data governance, legal, and responsible AI stakeholders to ensure AI is used ethically, safely, and effectively. This role also prepares the organization for AI features enabled in third-party applications and helps determine when an internal AI-enabled solution is needed to address a business gap.
Success requires strong HR business acumen, advanced analytic capabilities, AI literacy, stakeholder influence, change leadership, analytical measurement discipline, ability to educate others, responsible AI judgment, and the ability to translate emerging AI capabilities into practical, governed, and scalable HR solutions.
What you will do:AI Enablement Strategy & Adoption Leadership
- Lead AI enablement efforts across the Human Resources Group, including rollout planning, adoption strategy, communications, training, champion engagement, and value measurement.
- Translate HR business needs, user pain points, and emerging AI capabilities into a prioritized AI enablement roadmap.
- Partner with HR leaders, HR operations, analytics, technology, product, transformation, governance, and vendor partners to identify responsible AI opportunities that improve productivity, quality, consistency, and employee experience.
- Establish repeatable methods for AI use case intake, evaluation, prioritization, documentation, pilot execution, measurement, and scale.
- Identify adoption barriers, change management needs, workflow dependencies, tool limitations, and stakeholder alignment risks; recommend practical mitigation actions.
AI Champion Network Leadership
- Build, lead, and sustain HR AI champion networks to support tool adoption, peer learning, use case discovery, feedback collection, and responsible AI practices.
- Equip champions with reusable materials, examples, prompts, demonstrations, office hours, FAQs, and guidance aligned to approved AI tools and enterprise policies.
- Create feedback loops with champions and business users to understand where AI is creating value, where additional enablement is needed, and where risks or confusion may exist.
- Recognize and elevate high-impact use cases, successful adoption patterns, and reusable practices across HR functions.
- Support leaders and teams in developing AI confidence while reinforcing appropriate human oversight, validation, and escalation practices.
Use Case Discovery, Documentation & Value Measurement
- Identify and document high-value AI use cases across HR functions, including expected benefits, target users, process impacts, risks, assumptions, dependencies, and success measures.
- Measure and report AI value, including time savings, efficiency gains, quality improvements, accuracy, adoption rates, user engagement, avoided manual effort, and stakeholder satisfaction.
- Develop reporting methods to track AI adoption, business value, active use cases, license utilization, and enablement outcomes.
- Analyze use case performance data to determine which opportunities should be scaled, retired, redesigned, automated, or converted into Custom GPTs or repeatable workflows.
- Partner with HR subject matter experts to validate that AI-enabled outputs are accurate, useful, compliant, explainable, and appropriate for the intended HR process.
Custom GPT & AI Workflow Portfolio Management
- Centrally maintain HR-owned Custom GPTs, prompt libraries, reusable AI workflows, enablement materials, and related documentation.
- Prioritize Custom GPT and automation candidates based on business value, frequency of use, complexity, user demand, risk level, scalability, and measurable outcomes.
- Define intake criteria, naming standards, documentation expectations, testing requirements, ownership models, maintenance routines, and retirement criteria for Custom GPTs and AI assets.
- Coordinate development, testing, validation, rollout, monitoring, and continuous improvement of MCP Server Workflows, Custom GPTs and AI-enabled workflows in partnership with technology, governance, and business owners.
- Ensure Custom GPTs and AI workflows remain current, accurate, governed, and aligned to approved data, security, privacy, and responsible AI requirements.
AI Tool Access, License & Utilization Management
- Manage HR access to approved AI tools and licenses, including intake, prioritization, approval recommendations, renewal reviews, utilization monitoring, and reallocation processes.
- Determine or recommend which users and teams should receive access based on expected value, business need, readiness, responsible use, and demonstrated adoption.
- Monitor license utilization to ensure licenses are retained by users and teams with the highest-value use cases and meaningful ongoing engagement.
- Partner with leaders to reassign underutilized licenses, identify additional high-value users, and align licensing decisions to business priorities.
- Maintain clear documentation of access criteria, license decisions, utilization trends, and related governance expectations.
Third-Party AI Readiness & Internal AI Application Opportunity Assessment
- Lead HR readiness for AI capabilities embedded in third-party applications, including business impact assessment, user enablement, governance review, process redesign, and adoption planning.
- Partner with product owners, vendors, technology teams, privacy, security, legal, and governance partners to assess AI-enabled vendor features before rollout.
- Identify when third-party AI capabilities are sufficient, when additional configuration or controls are needed, and when gaps may require an internally built AI-enabled application.
- Evaluate internal AI application opportunities based on business need, user experience, data availability, risk, feasibility, expected value, governance requirements, and long-term support needs.
- Help HR leaders understand tradeoffs between using approved enterprise tools, vendor-embedded AI, Custom GPTs, automated workflows, and internally developed AI solutions.
Responsible AI, Governance & Ethical Use
- Understand, apply, and be prepared to defend responsible AI practices to governance committees and cross-functional review groups.
- Guide HR teams on ethical AI use, including fairness, bias, privacy, explainability, transparency, appropriate human oversight, data sensitivity, and acceptable use.
- Partner with governance teams to ensure AI use cases meet enterprise standards and HR-specific risk expectations.
- Review AI use cases, Custom GPTs, prompts, workflows, and third-party capabilities for potential risk, including inappropriate data use, unsupported decisions, bias, automation overreach, or lack of human review.
- Escalate AI risks, policy gaps, data concerns, or ethical issues through appropriate governance channels.
- Reinforce that AI should support, not replace, accountable human judgment in workforce-related decisions.
Change Management, Training & Communications
- Develop and deliver AI enablement content, including training sessions, guides, playbooks, demonstrations, FAQs, office hours, prompt examples, success stories, and leader-ready materials.
- Translate AI concepts, governance expectations, and tool capabilities into practical language for HR audiences with varying levels of technical experience.
- Support communication plans for AI launches, new capabilities, policy updates, champion activities, and adoption campaigns.
- Help teams redesign workflows to incorporate AI responsibly, including defining when human review is required and how outputs should be validated.
- Promote a culture of experimentation, learning, documentation, and responsible innovation across HR.
What qualifications you will need:- Bachelor's degree in Artificial Intelligence, Business, Human Resources, Information Systems, Data Analytics, Computer Science, Organizational Development, Industrial/Organizational Psychology, Education, or a related field
- Typically 5+ years of experience in HR transformation, HR operations, analytics, technology enablement, change management, product ownership, process improvement, digital adoption, AI enablement, or a related environment.
- Experience leading cross-functional initiatives, workstreams, platform rollouts, enablement programs, process improvements, or technology adoption efforts.
- Experience translating ambiguous business needs into clear use cases, requirements, success measures, stakeholder plans, and implementation approaches.
- Experience documenting business value, adoption metrics, process impacts, time savings, efficiency gains, or operational outcomes.
- Experience creating training materials, playbooks, communications, office hours, user guides, or enablement content for business users.
- Experience working with HR stakeholders, technology partners, governance teams, privacy, security, legal, compliance, analytics, or product teams.
- Experience using or enabling approved AI tools, automation tools, collaboration platforms, analytics tools, or workflow technologies.
- Experience managing stakeholder expectations, communicating risks, influencing decisions, and driving adoption without direct authority.
- Experience in Advanced Analytics Solutions
Must Have Skills
- Strong AI literacy, including practical understanding of generative AI, prompt design, Custom GPTs, Agentic AI-assisted workflows, responsible use, and human review expectations.
- Ability to lead AI enablement initiatives from intake through rollout, adoption, measurement, optimization, and governance alignment.
- Strong stakeholder management skills, including the ability to clarify expectations, manage dependencies, communicate risks, and influence decisions across HR and technology partners.
- Ability to identify, document, prioritize, and measure high-value AI use cases across HR functions.
- Strong analytical mindset for measuring time savings, efficiency gains, accuracy, adoption rates, utilization, and business value.
- Ability to manage AI tool access and license allocation based on business value, adoption, readiness, and governance expectations.
- Ability to centrally maintain Custom GPTs, prompt libraries, AI workflow documentation, and reusable enablement assets.
- Understanding of responsible AI considerations such as fairness, explainability, privacy, bias, data sensitivity, transparency, and appropriate human oversight.
- Strong communication and change management skills, including the ability to create practical training, guidance, and leader-ready materials.
- Ability to work with ambiguous business problems and structure practical, governed, and scalable AI enablement approaches.
- Ability to partner effectively across HR, analytics, technology, product, governance, privacy, security, legal, and vendor teams.
- Sound judgment when working with confidential HR and workforce information.
Nice to Have Skills
- Experience leading an AI champion network, digital adoption network, community of practice, product champion group, or similar enablement model.
- Experience with ChatGPT Enterprise, Microsoft Copilot, or other enterprise AI-enabled third-party applications.
- Experience designing, testing, launching, or maintaining Custom GPTs, AI assistants, prompt libraries, RAG-enabled tools, or automated workflows.
- Experience with workflow automation tools, low-code platforms, analytics dashboards, intake tools, knowledge management systems, or enterprise collaboration platforms.
- Experience developing use case scorecards, value realization frameworks, adoption dashboards, or license utilization reporting.
- Experience supporting AI governance reviews, responsible AI documentation, risk assessments, model cards, vendor reviews, or data privacy reviews.
- Experience in HR operations, talent acquisition, talent management, learning, compensation, benefits, employee relations, workforce planning, shared services, or HR analytics.
- Prior experience in healthcare, regulated environments, enterprise HR, or large matrixed organizations.
- Experience recognizing when a business gap requires an internally developed AI-enabled application instead of a third-party feature, manual process, or simple automation.
- Experience facilitating workshops, design sessions, training sessions, demos, office hours, or leadership briefings.
Licenses, Certifications & Training:
- Preferred: role-relevant certification, analytics platform training, data governance training, or Agile delivery training, as applicable.
- Preferred: Responsible AI, data privacy, data security, or HR data handling training.
Knowledge, Skills, Abilities, Behaviors:
- Demonstrates curiosity, ownership, sound judgment, and practical optimism when introducing AI into HR processes, systems, and ways of working.
- Communicates AI capabilities, limitations, risks
