AI Ops Adoption & Enablement Analyst

Micron•Boise, ID

About The Position

As an AI Ops Adoption & Enablement Analyst in Micron's AI Operations Center of Excellence (AI Ops COE), you will accelerate adoption of AI capabilities across Micron IT. You will partner with IT leaders, solution owners, architects, cybersecurity teams, delivery collaborators, implementation teams, and executive sponsors to ensure AI initiatives are deployed, adopted, and coordinated effectively in daily operations. The role combines adoption enablement, organizational change, customer engagement, communications, operational coordination, and value realization. Through training, coaching, communication, coordination, and measurement, you will support solution rollouts, build organizational readiness, and help teams realize sustainable operational improvements from AI investments.

Requirements

Bachelor's degree in Business, Information Systems, Organizational Development, Communications, Project Management, or a related field, or equivalent experience.
Demonstrated ability in organizational transitions, technology adoption, enablement, customer success, project coordination, training, communications, or related work supporting successful technology adoption.
Demonstrated experience coordinating multi-functional initiatives, including planning, roadmap management, achievement tracking, action management, dependency coordination, executive reporting, communications, and execution support.
Ability to communicate effectively with technical and non-technical audiences, facilitate discussions, influence outcomes, and build trusted relationships across organizational boundaries.
Experience gathering feedback, analyzing adoption data, identifying trends, and translating findings into actionable recommendations and continuous improvement opportunities.

Nice To Haves

Experience supporting adoption of artificial intelligence, automation, digital workplace technologies, Copilot platforms, or enterprise transformation initiatives.
Familiarity with organizational change frameworks, partner analysis, readiness assessments, communications planning, and adoption measurement practices.
Experience supporting enterprise initiatives through roadmap management, action-item tracking, dashboard development, leadership reporting, working-session facilitation, and value realization measurement.
Experience facilitating workshops, developing learning materials, leading office hours, creating enablement content, or supporting adult learning initiatives.
Experience working directly with senior leaders and supporting executive adoption of new technologies, operating models, and transformation initiatives.

Responsibilities

Collaborate with key parties to develop and implement adoption strategies that prepare teams for new AI capabilities and support organizational change.
Provide hands-on support, coaching, and guidance to users adopting AI solutions, helping teams apply AI to workflows and improve efficiency, decision-making, service delivery, and employee experience.
Build relationships with technical teams, solution owners, managers, and executive leaders; address concerns, gather feedback, and encourage adoption.
Provide tailored guidance and white-glove support to senior leaders so they can understand, adopt, and champion AI solutions.
Develop and maintain implementation plans, turning point schedules, action-item tracking, dependency tracking, and delivery roadmaps across AI Ops initiatives.
Coordinate working sessions, planning meetings, readiness reviews, and collaborator forums; document decisions, track action items, follow up on commitments, and help remove delivery and adoption blockers.
Prepare executive presentations, leadership briefings, status reports, dashboards, and portfolio updates covering progress, dependencies, risks, achievements, adoption metrics, and upcoming successes.
Coordinate communications, awareness campaigns, workshops, office hours, learning sessions, and enablement activities that reinforce responsible AI adoption and continuous learning.
Collect user feedback, adoption insights, and lessons learned to identify opportunities for solution improvements, training enhancements, and process optimization.
Develop and maintain adoption metrics, readiness indicators, usage trends, benchmark reporting, and operational value measurements; assess realized benefits and identify improvement opportunities.
Contribute to rollout playbooks, communication frameworks, enablement methodologies, reporting standards, and adoption protocols that improve consistency and scalability across AI initiatives.