Director Internal AI Governance

Enterprise AI Governance
Define and maintain NIQ’s enterprise framework for the governance of internally used AI, including generative AI, machine learning, autonomous agents, and third-party AI-enabled products.
Establish clear policies, standards, decision rights, approval thresholds, and accountability for AI use across the enterprise.
Define risk-based governance requirements based on factors such as data sensitivity, business criticality, autonomy, customer or employee impact, regulatory exposure, and financial risk.
Ensure governance remains proportionate to risk and enables responsible experimentation without creating unnecessary barriers to adoption.
Maintain an enterprise inventory of material internal AI solutions, use cases, models, vendors, and associated owners and risks.
AI Investment and Use-Case Governance
Establish governance processes for evaluating proposed AI investments and internal AI opportunities.
Partner with Finance and business leaders to ensure material AI initiatives have clearly defined business cases, measurable outcomes, full lifecycle costs, and accountable benefit owners.
Define criteria for progressing, scaling, pausing, or stopping AI initiatives based on business value, adoption, performance, risk, and total cost of ownership.
Help ensure NIQ prioritizes meaningful business opportunities rather than deploying AI solely because the technology is available.
Establish governance mechanisms to identify overlapping tools, duplicative investments, and opportunities for enterprise reuse.
Responsible AI and Risk Management
Develop and operationalize NIQ’s responsible AI principles and control framework for internal AI.
Partner with Privacy, Legal, Security, Risk, Compliance, and HR to address risks including data privacy, intellectual property, cybersecurity, bias, explainability, human oversight, records retention, regulatory requirements, and inappropriate use.
Define requirements for human review, testing, validation, monitoring, auditability, and escalation based on AI risk classification.
Establish processes for identifying, reporting, investigating, and remediating AI-related incidents.
Monitor emerging AI regulation, standards, and industry practices and translate them into appropriate NIQ governance requirements.
Technology and Architecture Governance
Partner with Technology and Security leaders to establish approved AI technology patterns, platforms, models, and architectural guardrails.
Define requirements for the use of public, private, proprietary, and open-source AI models.
Establish governance for AI data access, model access, identity and permissions, integrations, agents, APIs, logging, monitoring, and production deployment.
Partner with technology teams to define controls for AI development environments, experimentation, productionization, and ongoing operations.
Support enterprise decisions regarding build-versus-buy approaches and strategic AI platforms.
Third-Party and Vendor AI Governance
Partner with Procurement, Technology, Security, Privacy, and Legal to establish standards for evaluating AI capabilities embedded within third-party products and services.
Define due-diligence requirements for AI vendors, including data usage, model training practices, security, intellectual property, contractual protections, service continuity, and regulatory risk.
Help ensure the enterprise understands the full financial and operational impact of AI technology commitments, including licensing, consumption, infrastructure, integration, support, and ongoing operating costs.
Governance Operating Model
Chair or lead appropriate enterprise AI governance forums and provide clear recommendations to senior leadership.
Establish transparent escalation paths and decision-making processes for high-risk or high-impact AI initiatives.
Define governance metrics and reporting that provide leadership with visibility into AI adoption, value realization, risk exposure, policy compliance, and portfolio health.
Create practical guidance, playbooks, templates, and education that enable teams to comply with governance requirements efficiently.
Continuously improve the governance model based on emerging technologies, organizational learning, regulatory developments, and operational experience.
Leadership and Influence
Serve as a trusted advisor to senior Technology, functional, and business leaders on internal AI strategy, governance, and risk.
Build alignment across functions with different objectives, risk tolerances, and levels of AI maturity.
Develop a culture in which teams understand that responsible governance and rapid innovation are complementary rather than competing objectives.
Lead and develop a high-performing governance capability as the organization’s needs evolve.
Qualifications
Significant leadership experience (15+ years) in technology governance, enterprise technology, AI, risk, cybersecurity, data governance, digital transformation, or a related discipline.
Demonstrated experience establishing or operating enterprise governance frameworks in a large, complex, global organization.
Strong understanding of generative AI, machine learning, enterprise AI platforms, AI-enabled applications, and emerging agentic technologies.
Working knowledge of AI-related risks including privacy, cybersecurity, intellectual property, bias, model risk, data leakage, regulatory exposure, and third-party risk.
Experience partnering with Legal, Privacy, Security, Finance, Procurement, Technology, and senior business leadership.
Demonstrated ability to translate complex technical and regulatory topics into practical business policies and decisions.
Strong understanding of enterprise investment governance, business cases, total cost of ownership, and benefit realization.
Ability to establish structure and clear decision-making in rapidly changing and ambiguous environments.
Exceptional executive communication, influencing, and stakeholder-management skills.
Experience leading globally distributed initiatives and operating across organizational boundaries.
Preferred Qualifications
Experience establishing an enterprise Responsible AI or AI Governance program.
Experience governing generative AI platforms, copilots, large language models, or autonomous AI agents.
Familiarity with emerging AI regulatory frameworks and recognized AI risk-management standards.
Experience with large-scale enterprise cloud, data, security, and technology environments.
Experience managing technology or transformation portfolios with measurable financial and operational outcomes.
Measures of Success
Success in this role will be measured by NIQ’s ability to:
Scale internal AI adoption while maintaining appropriate levels of enterprise risk.
Make AI investment and deployment decisions faster through clear standards and decision rights.
Demonstrate measurable productivity, cost, revenue, or operational benefits from material AI investments.
Reduce unmanaged, duplicative, or non-compliant AI usage.
Maintain clear ownership and visibility of material AI solutions across the enterprise.
Identify and mitigate AI risks before they result in material business impact.
Create governance that business and technology teams view as practical, predictable, and enabling

Employment type
Full-time

Work arrangement
Hybrid