VP, Data & AI Implementation & Enablement

Job Classification

Technology - Data Analytics & Management

Are you energized by building enterprise capabilities that accelerate innovation with speed, scalability, and strong governance? Our Data & AI organization is shaping how Prudential modernizes responsibly—embedding trust, usability, and measurable value into the way teams adopt data and AI. When you join our organization, you will help the enterprise operationalize modern data governance and Responsible AI capabilities that enable safer, faster, and more consistent business outcomes at scale.

As the Vice President, Data & AI Implementation & Enablement, you will play a pivotal role in translating Prudential’s Data & AI governance strategy into scalable operating processes, tooling, and enterprise adoption. Sitting within the Data Enablement organization, you will lead the implementation and rollout of core governance and Responsible AI capabilities, including enterprise data catalog and metadata management, data quality enablement, governance playbooks, and Responsible AI operationalization.

This role is designed for an executive leader who is both a strategist and an operator—someone who can convert governance intent into practical execution through clear operating models, repeatable playbooks, and measurable outcomes. You will drive onboarding and readiness, develop training and communications, monitor adoption and effectiveness, and partner across product, engineering, legal, risk, compliance, and business teams to reduce friction and embed governance and AI controls into day-to-day workflows.

In this role, you will establish and scale enterprise-wide enablement mechanisms, including communities of practice, reusable assets, training, and adoption support, to accelerate capability building and drive consistency across domains and lines of business. You will ensure governance tooling and processes are implemented in a way that is practical, sustainable, and aligned with regulatory expectations and enterprise risk posture—enabling trusted data, stronger analytics, and responsible use of AI across the enterprise.

Newark, NJ hybrid (minimum 3 days/week in office)

• Translate Data & AI governance strategy into an enterprise enablement roadmap spanning processes, tooling, playbooks, training, communications, and adoption metrics.
• Build and lead a scalable enablement operating model that supports consistent rollout, onboarding, adoption, and continuous improvement across the enterprise.
• Lead the implementation and adoption of governance capabilities, including data catalog, metadata, lineage, stewardship, and data quality tooling.
• Serve as, or partner closely with, product leadership for governance platforms by defining requirements, prioritizing user needs, supporting releases, demonstrating value, and driving ongoing optimization.
• Develop and standardize governance playbooks, including stewardship workflows, critical data element definitions, data quality rule patterns, issue management, and approval processes.
• Partner with Legal, Risk, Compliance, Model Risk, and AI teams to operationalize Responsible AI requirements into clear controls, templates, workflows, and supporting documentation.
• Enable Responsible AI use case intake, risk tiering, documentation standards, review workflows, and lifecycle management in coordination with governance forums and control partners.
• Design and deliver enterprise-wide training, communications, and readiness programs to support adoption of Data & AI governance tools, standards, and ways of working.
• Establish adoption mechanisms such as office hours, onboarding materials, champion networks, communities of practice, and structured feedback loops.
• Track, measure, and report adoption, engagement, and effectiveness metrics, including tool usage, data quality improvement, control maturity, and cycle-time reduction.
• Create and scale a Data & AI Governance Community of Practice to share reusable assets, implementation patterns, lessons learned, and success measures across the organization.
• Act as a senior connector and influencer across data owners, stewards, architects, engineers, and business…