27/11/2025

Recruiting a Proactive Head of Data & AI Policy

Recruiting a Head of Data & AI Policy: A Strategic Lever for Proactive and Profitable AI Governance

Introduction: Why will this role become critical for businesses undergoing transformation, from large corporations to scale-ups?

The Data & AI teams of our clients—whether structured as a centralised Data & AI office or a Centre of Excellence overseeing decentralised data offices—often need to establish a role that embodies the function of Data & AI Compliance from a business perspective. While a Data Protection Officer (DPO) typically operates within the group’s legal department, their approach is frequently defensive (as lamented by Data & AI offices), focusing on ensuring compliance with legal obligations and ethical standards in data usage and AI design (both analytical and generative).

The most common operational model results in excessive, unproductive back-and-forth between the DPO and the product and technical teams within the the Data & AI office, who develop data and AI products in close collaboration with business units. This inefficiency often stems from the Data & AI office’s lack of preparedness in designing products that meet legal constraints (including data security) and the ethical rules demanded by both enterprises and legislation. Naturally, this slows down the go-to-market process for Data & AI products.

The overarching mission of a proactive Head of Data & AI Policy would be to support product and technical teams in designing compliant-by-design Data and AI products, while continuing to meet business needs and accelerating their development and scalable deployment. This role would involve preparing teams to successfully navigate compliance filters, establishing repeatable and rigorous processes, and creating the necessary governance frameworks.

This position, desired by many of our clients but rarely implemented, serves as the proactive counterpart to the DPO on matters of compliance and ethics.

At Uman Partners, we specialise in AI and Data recruitment and executive search for top-tier Data & AI management profiles. We observe growing potential demand for this pivotal role, particularly in sectors where AI is a key differentiator (such as banking, healthcare, retail, and Industry 4.0). But how should this role be defined, positioned, and—most importantly—successfully recruited?

Our Partner for DACH: Patrick Schmitz

The mission of a proactive Head of Data & AI Policy is to empower product and technical teams to design compliant-by-design Data and AI products.

1. The Head of Data & AI Policy: A Bridge Between Compliance, Innovation, and ROI

1.1. A Role Born of Necessity: The Limits of the Traditional DPO

Data & AI Offices in both large corporations and scale-ups often struggle to align product agility with regulatory compliance. According to a 2024 McKinsey study, 62% of AI products experience delays due to compliance or ethical concerns, directly impacting AI ROI. While DPOs are highly skilled, they are rarely involved early in projects, leading to costly exchanges between legal and technical teams.

1.2. Core Missions: Beyond Compliance, a Strategic Vision

The Head of Data & AI Policy does more than validate processes. They co-design Data & AI products with technical and business teams, embedding key considerations from the outset:

Algorithmic explainability(to mitigate bias and build trust).
Data flow security (encryption, hybrid cloud architectures).
Ethics by default(alignment with corporate values and societal expectations).

Key Figures:

78% of executives believe generative AI will require a governance overhaul by 2026(Gartner, 2025).
Companies with strong cross-functional collaboration between Data, Legal, and Business teams see a35% increase in AI adoption rates(Harvard Business Review).

This role is not just a safeguard—it is a growth accelerator.

2. The Five Pillars of the Role : From Regulatory Monitoring to Continuous Audit

In detail, the core responsibilities typically include:

2.1 – Embedding Compliance in Products

Integrate acompliance and ethics-by-design approachinto the development of Data & AI products within Data & AI Offices, structurally reducing the risk of delays or blockages and accelerating scalable deployment and product adoption.
Collaborate closely with product (Data & AI) and technical teams—as well as the DPO—from the design phase to embed compliance and ethical requirements.

2.2 – Technological, Regulatory, and Normative Monitoring, Innovation, and Continuous Improvement

Participate in working groups and forums on data and AI compliance to share and adopt best practices.
Maintain ongoing monitoring of technological advancements and evolving regulations related to data protection (GDPR, security, etc.) and the ethical, compliant use of AI (with DPO support). Bridge these constraints with technological solutions that address them (e.g., secure data flows, encryption,hybrid cloud solutions, data indexing/enrichment for ethical, unbiased learning, and R&D onalgorithmic explainability).
Bring these technological solutions and innovations to technical teams, while informing and training them on regulatory changes and their implications for current and future products.

2.3 – Risk Assessment

ConductData Protection Impact Assessments (DPIAs)for new products.
Identify and evaluate risks associated with data and AI use, and propose risk mitigation measures.

2.4 – Training and Awareness

Organise training sessions for teams on compliance best practices, data protection, and the adoption of relevant technologies.
Raise stakeholder awareness of the ethical and legal challenges of AI use.

→ A visionary leadership challenge: 89% of employees expect AI training (Forbes, 2025).

2.5 – Collaboration with the DPO

Act as abridge between legal, technical, and business teamsto facilitate communication and mutual understanding.
Participate inagile ceremonies to provide compliance and ethics expertise and help resolve potential issues.

2.6 – Audit and Oversight

Establishgovernance mechanisms to ensure products meet compliance requirementsthroughout their lifecycle.
Conductinternal audits to assess the effectiveness of compliance measuresand identify areas for improvement.

A Note on the DPO’s Role Some may argue that the DPO should already fulfil this role proactively. We agree—but the reality is that this rarely happens, often due to organisational immaturity regarding data and AI, or historical reasons (e.g., the role was assigned to a volunteer from the legal department, far removed from tech culture).

Conclusion: A Role to Turn Compliance into a Competitive Advantage The Head of Data & AI Policy is not a cost, but a growth lever. By integrating this role into your organisation, you will: ✅ Accelerate time-to-market. ✅ Secure your AI investments. ✅ Strengthen your data & AI leadership in your market.

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