Head of AI Adoption & Capability

Role Description

The Head of AI Adoption & Capability is a senior leadership role within GRS responsible for translating enterprise AI investments into competitive advantage. The role partners directly with the GRS Leadership Team to define and execute a rolling AI adoption strategy, builds a self-sustaining culture of AI capability across all of GRS, and ensures that every AI tool deployed delivers tangible business impact.

This role owns GRS's strategy for embedding AI into how the business works — driving measurable value from AI tools across 2,300+ employees, building lasting organizational capability, and serving as GRS's senior voice on AI adoption in partnership with the GRS Leadership Team. This is not a technology role. It is a business leadership role that sits at the intersection of strategy, change management, learning, and operations.

Key Responsibilities

• Strategy & Roadmap Ownership
  • Own and evolve the GRS AI adoption strategy on a rolling 12–18-month horizon, in close partnership with GRS Leadership.
  • Maintain a prioritized roadmap of AI tools, use cases, and capability investments across all of GRS.
  • Evaluate emerging AI tools and capabilities, advising GRS Leadership on what should be adopted, piloted, or monitored.
  • Serve as GRS's primary voice into enterprise AI governance bodies, product feedback loops, and vendor relationships.
• Claude & Everyday AI Tools — Deployment & Adoption
  • Lead license deployment and onboarding across multiple waves, designing training sessions, intake mechanisms, and onboarding materials.
  • Track engagement and surface momentum: partner with the Licensing Lead to monitor usage, flag low adoption, and identify early wins.
  • Build toward a self-sustaining model by equipping AI Champions to own ongoing peer support.
  • Develop and manage a communications cadence that keeps leaders informed and connected to AI progress.
• Business Impact Measurement
  • Define and maintain a GRS-specific AI value framework, translating usage metrics into business outcomes.
  • Produce regular impact reporting for GRS Leadership and enterprise stakeholders.
  • Build the business case for future AI investments based on demonstrated, evidence-based value.
  • Identify, curate, and circulate GRS use cases and success stories that demonstrate tangible impact.
• Capability Building & Learning Culture
  • Design and own a tiered AI learning curriculum across GRS.
  • Partner with HR and L&D to embed AI skills into role profiles, performance expectations, and career development frameworks.
  • Lead a mature, structured AI Champions program.
• Workflow & Process Integration
  • Identify high-value GRS workflows where AI can be systematically embedded.
  • Partner with business unit leaders and process owners to redesign workflows around AI capabilities.
  • Collaborate with IT and engineering where deeper integrations could multiply impact at scale.

Key Indicators

• Adoption: Active usage rates across license holders; reduction in low-adoption cohorts over time.
• Capability: Completion of tiered learning curriculum; growth of AI Champions program; qualitative skill uplift.
• Business Value: Documented time savings, quality improvements, and business outcomes tied to AI use cases.
• Strategy: GRS LT satisfaction with AI roadmap clarity; GRS influence on enterprise AI direction.
• Compliance: Zero material incidents related to AI misuse; governance framework kept current with regulatory change.

Risk, Compliance & Responsible Use

• Own GRS's responsible AI use framework — maintaining guardrails, acceptable use standards, and data handling guidelines.
• Stay current on regulatory developments relevant to AI in risk and insurance.
• Partner with Legal, Compliance, and Risk functions to ensure AI adoption stays ahead of governance requirements.

Stakeholder & Vendor Management

• Manage the relationship with Anthropic and other AI vendors on behalf of GRS.
• Represent GRS in enterprise AI forums and working groups.
• Build and maintain a network of AI leads across peer business units.

What Makes this Role Distinctive

This role is rare: it requires someone who is equally comfortable presenting an AI strategy to a C-suite audience and running a hands-on prompting workshop with underwriters. The ideal candidate brings strong organizational instincts, genuine curiosity about AI, and the humility to build on what already exists rather than create from scratch.

Preferred Qualifications

• Prior experience in financial services, insurance, or a risk-adjacent function.
• Hands-on experience with AI tools and a genuine curiosity about their evolving capabilities.
• Experience managing third-party vendor relationships in a technology or SaaS context.
• Familiarity with responsible AI frameworks, data governance, or enterprise compliance requirements.

Qualifications

• 8+ years of progressive experience in strategy, change management, organizational capability, or a related field.
• Demonstrated experience leading enterprise-scale adoption or transformation programs.
• Strong executive presence and ability to influence senior leaders without direct authority.
• Exceptional communication skills — able to translate complex AI concepts into clear business language.
• Experience designing and delivering learning and capability programs at scale.
• Commercial acumen and comfort working with data to demonstrate business impact.

Travel

• 50%