Purpose of the role Turn AI delivery learning into governed, discoverable and reusable guidance, while ensuring new AI services are understood, adopted and sustained. Own the AI CoE playbook, asset catalogue, communities, onboarding and adoption-readiness approach across Europe and India.
Key responsibilities
Define and own the AI CoE playbook, information architecture, taxonomy, templates, contribution workflow and review/retirement cycle.
Capture approved patterns, engineering assets, controls, architecture decisions, lessons, runbooks and operational guidance from Microsoft and delivery teams.
Maintain the reusable asset catalogue with clear ownership, versioning, searchability, release notes and usage analytics.
Develop role-based onboarding, community-of-practice and learning pathways for Product Owners, reviewers, architects, engineers and operations teams.
Own adoption-readiness standards: stakeholder mapping, impact assessment, communications, learning, user feedback and operational acceptance.
Coordinate with UX/service design and Product Owners to ensure human-AI interaction, support, escalation and feedback are understood before release.
Measure adoption and reuse, identify recurring friction and feed improvement priorities into the AI CoE backlog.
Accept and maintain the Microsoft capability-transfer package, including repositories, playbooks, patterns, architecture decisions and runbooks.
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Experience
10+ years in knowledge management, change/adoption, delivery excellence or technology programme enablement, with meaningful exposure to digital, data or AI transformation.
P1 - must have
Knowledge management and information architecture for technical and business audiences.
Change and adoption methods covering stakeholder impact, communications, learning and adoption measurement.
Proficiency with Microsoft 365, SharePoint, Teams, Loop, Azure DevOps wiki and/or GitHub.
Content lifecycle governance: taxonomy, metadata, versioning, review, approval and retirement.
Community facilitation, onboarding and ability to convert complex technical decisions into actionable guidance.
Ability to work across Europe and India and coordinate partner knowledge transfer.
P2 - preferred
Understanding of AI/cloud delivery concepts, agents, platform services and runbooks.
Experience with service design, UX research or human-AI adoption.
Power BI or equivalent adoption/reuse analytics.
Prosci, CCMP, ITIL 4 or knowledge-management certification.
Core competencies
Stakeholder orientation and executive influence
Results and value orientation
Courage to challenge and sound judgement
Cross-cultural collaboration across Europe and India
Learning agility and capability building
Structured decision-making and transparent governance
Key deliverables
AI CoE playbook; pattern and asset catalogue; contribution/review workflow; onboarding kits; role-based learning paths; adoption-readiness checklist; community calendar; reuse and adoption dashboard; knowledge-transfer acceptance pack.
First 90 days
Baseline existing Microsoft and ArcelorMittal knowledge assets and assign owners.
Launch the AI CoE repository structure, contribution workflow and minimum playbook.
Define adoption-readiness criteria and role-based onboarding for the first use cases.
Establish communities of practice and publish the first reuse/adoption dashboard.
