The Data & AI Enablement Lead acts as a value orchestrator for data and AI initiatives across SEAA. The role owns the upstream shaping of initiatives — including opportunity identification, business case development and initiative framing — and the downstream realization of value through adoption, impact measurement and capability building. It drives the successful enablement and adoption of data and AI products across the organization, ensuring they are translated into practical levers for better decision-making, stronger activation and measurable impact. Through communication, change management, upskilling and stakeholder engagement, the role helps business teams understand, trust and effectively use data and AI products.

Impact You Can Create In The Role:

Corporate Strategic KPI Management

Partner with Finance, P&O, President Office to define and align the strategic KPIs that guide business steering, performance management and leadership decision-making.
Establish clear definitions, calculation logic, ownership and interpretation principles for key enterprise metrics, ensuring consistency across the organization
Support alignment & adoption, ensure strategic KPIs are consistently understood, trusted and used in business reviews and decision making.

Opportunity Identification & Business Case Development:

Liaise with divisions, functions and data teams to identify high-value opportunities where data products, analytics or AI-enabled solutions can support growth, improve decision-making and accelerate activation towards LEAP ambition.
Translating business priorities and pain points into clear initiative charters, including objective, expected business value, ROI logic, success KPIs, feasibility considerations and delivery implications.
Liaise with the President Office to challenge and prioritize new ideas based on business impact, strategic alignment, stakeholder readiness, data availability, technology feasibility and resource constraints.

Data & AI Initiative Orchestration:

Orchestrate selected data and AI initiatives across business, data, technology and analytics teams, ensuring business objectives, delivery scope, timelines and dependencies are clearly aligned.
Translate approved use cases into actionable delivery plans, including expected outputs, milestones, resource needs, risks and stakeholder engagement requirements.
Monitor initiative progress, facilitate issue resolution and escalate key risks or decisions to ensure delivery remains focused on business value and adoption readiness.

Business Adoption & Operationalization:

Define and execute adoption plans for dashboards, data products and AI-enabled solutions, ensuring products are embedded into business routines, decision forums and ways of working.
Promote business activation by guiding users on how to interpret, trust and act on insights from data and AI products, rather than treating them as standalone technical tools.
Capture user feedback, adoption barriers and enhancement needs, and translate them into practical product improvements or change actions.
Communicate data and AI initiative updates, product adoption progress and project status to leadership and working-level stakeholders in a clear, business-friendly manner.

Upskilling & Data Literacy:

Collaborate with HR / P&O, Tech partners, data teams and business leads to design and deliver practical data and AI training, upskilling and enablement activities.
Develop user guidance, playbooks, communication materials and learning content that help business users build confidence in using data products and AI-enabled tools.
Identify common capability gaps across workstreams and coordinate targeted data literacy interventions to support adoption and sustainable value realization.

Your Success Measures

Corporate Strategic KPI Management: Strategic KPIs are clearly defined, aligned across stakeholders and embedded into business reviews, performance conversations and leadership decision-making.
Business Value & ROI: Priority data and AI initiatives are linked to clear business value, measurable KPI logic and practical ROI assumptions.
Adoption & Usage: Launched dashboards, data products and AI-enabled solutions are actively used by target business users and embedded into relevant business routines.
Requirement Readiness: Initiatives are clearly scoped, prioritized and ready for BI, data engineering, analytics and AI teams to deliver with minimal rework.
Stakeholder Alignment: Business, Finance, P&O, President Office, Tech and data teams are aligned on objectives, scope, timelines, ownership and expected outcomes.
Delivery Discipline: Initiatives are mobilized and tracked with clear plans, transparent status updates, managed dependencies and timely escalation of risks or open decisions.
Capability Building: Business users demonstrate improved confidence and capability in interpreting, trusting and acting on data and AI products.
Continuous Improvement: User feedback and adoption insights are translated into actionable enhancements that improve product relevance, usability and business impact.

You are Energized by:

Making an Impact: Seeing data and AI initiatives translate into better business decisions, clearer priorities, stronger client experiences and measurable growth outcomes.
Bridging Business and Data: Turning business ambition, stakeholder needs and complex data topics into clear priorities, practical requirements and actionable stories.
Driving Adoption: Helping teams move beyond delivery to actual usage, behavior change and sustained value from data and AI products.
Building Confidence: Enabling business users to understand, trust and act on data and AI outputs with clarity and confidence.
Collaboration: Working cross-functionally with divisions, corporate functions, Finance, P&O, President Office, Tech, BI, engineering, analytics and AI teams to operationalize data-driven value creation.

What You Will Bring - Capability Requirements:

Business Opportunity Framing & ROI Thinking: Strong ability to identify data and AI opportunities with business stakeholders, shape the business case, define value logic and prioritize initiatives based on impact, feasibility and strategic alignment.
KPI & Measurement Design: Solid understanding of KPI definition, performance measurement and value tracking. Able to translate business priorities into practical, measurable indicators.
Data / AI Product Understanding: Good understanding of dashboards, analytics products and AI-enabled solutions, with the ability to bridge business needs and technical delivery without needing to be the technical builder.
Project & Workstream Management: Skilled in managing cross-functional initiatives, coordinating timelines, dependencies, risks, status updates and follow-up actions across business and technical teams.
Stakeholder Management & Communication: Able to engage senior and working-level stakeholders, communicate complex data and AI topics in accessible business language, and manage expectations across functions.
Adoption, Change & Operationalization: Experience driving adoption of new tools, products or ways of working, including user engagement, feedback management, communications and embedding change into business routines.
Upskilling & Data Literacy Enablement: Comfortable collaborating with HR / P&O, Tech and data teams to develop practical training, guidance and enablement materials for business users.
Business Acumen & Entrepreneurial Mindset: Proactive in identifying value creation opportunities, connecting business strategy with data / AI possibilities, and turning ideas into practical actions that support growth and decision-making.

At Chanel, we are focused on creating an inclusive culture that nurtures personal growth, contributing to collective progress. We believe the uniqueness of each individual increases the diversity, complementarity and effectiveness of our teams. We strongly encourage your application, as we value the perspective, experience and potential you could bring to Chanel.

Data & AI Enablement Lead, SEAA