Head Data & AI Strategy

Recruiting a Head of Data & AI Strategy requires a thorough understanding of the role. The following is a very general summary, which should be adapted to your specific context.

The Head of Data & AI Strategy reports directly to the Chief Data & AI Officer (CDAO) and is responsible for designing, planning, and implementing the Data & AI strategy within the company. This role involves defining a clear and ambitious roadmap, designing an effective operating model, and ensuring that Data & AI products are aligned with the company’s business objectives.
They work closely with the entire CDAO team (Head of AI Factory, Head of Analytics, Head of Data Governance, Head of Data & AI Product, Head of Data Platform, etc.) to ensure consistent and value-creating execution.

Core Responsibilities

a. Definition and Management of the Data & AI Roadmap

Roadmap Design:

Develop a strategic roadmap for Data & AI products, aligned with the company’s business objectives and in collaboration with the CDAO and business teams.
Prioritize initiatives based on their business impact, technical feasibility, and available resources.

Stakeholder Alignment:

Collaborate with management, business, and technical teams to validate and adjust the roadmap.
Present the strategy and progress to stakeholders (executive committees, investors).

b. Design and Optimization of the Operating Model

Operating Model:

Define an effective operating model for the implementation of Data & AI products, in collaboration with other members of the CDAO team (e.g., team organization, delivery processes, governance).
Identify and resolve bottlenecks in existing processes to improve efficiency and speed of product delivery.

Collaboration with the CDAO Team:

Work closely with the Head of Data & AI Product (and/or with the Head of AI Factory and Head of Analytics) to ensure products are delivered according to the roadmap.
Coordinate with the Head of Data Governance and the DPO to ensure products comply with governance and compliance standards.
Align resources (teams, budgets, tools) with strategic priorities, in collaboration with peers within the CDAO team.

c. Strategic Alignment and Value Creation

Business Opportunity Analysis:

Identify high-potential Data & AI use cases for the company (e.g., new products, process optimization, customer experience).
Assess the business impact and ROI of proposed initiatives, in collaboration with business teams and the Head of Data & AI Product.

Strategic Monitoring:

Monitor market trends and innovations in Data & AI to anticipate changes.
Benchmark best practices and competitive solutions.

d. Governance and Compliance

Governance Framework:

Contribute to defining data governance policies and ethical standards for AI, in collaboration with the Head of Data Governance and the DPO.
Ensure that Data & AI products comply with regulations (GDPR, AI Act) and internal standards.

Risk Management:

Identify risks related to Data & AI products (e.g., algorithmic bias, data security) and propose mitigation measures, in collaboration with relevant teams.

e. Communication and Strategy Adoption

Internal Communication:

Raise awareness and train business teams and management on the Data & AI strategy and its benefits.
Promote a data & AI-driven culture within the company.

Reporting and Monitoring:

Establish performance indicators to measure the progress and impact of Data & AI products.
Regularly report progress and results to stakeholders.

f. Collaboration with Other Functions

Alignment with the CDAO:

Work closely with the Chief Data & AI Officer to ensure the strategy aligns with the company’s overall vision.

Coordination with Technical Teams:

Collaborate with Data Engineering, AI Factory, and Analytics teams to ensure smooth execution of Data & AI products.

Concrete Achievements Examples

Data & AI Roadmap: Designed and implemented a 3-year roadmap aligned with the company’s overall strategy, including flagship Data & AI products such as business process automation and the creation of new data-driven products.
Optimized Operating Model: Redefined the operating model to reduce delivery times for Data & AI products by 30%, aligning teams with business needs.
Business Value Creation: Identified and prioritized Data & AI use cases generating a 20% ROI on operational costs.
Regulatory Alignment: Established a data governance framework compliant with GDPR, reducing non-compliance risks.