VP, Global Head of Agentic AI Solutions

About the Role

The Global Head of Agentic AI Transformation will lead the enterprise-wide strategy, development, and implementation of agentic AI solutions and associated end‑to‑end process re-engineering across AIG’s businesses and functions globally. This executive will be accountable for partnering in transforming underwriting, claims, operations, finance, and corporate functions by combining advanced autonomous AI agents, modern workflow design, and rigorous process‑improvement disciplines such as Lean and Six Sigma.

This role will report to the Global Chief Data Officer and will partner with executive leadership to define the company’s agentic AI vision, drive platform and architecture decisions, design and scale enterprise-wide AI‑powered operating models, and ensure that all deployments deliver measurable improvements in productivity, accuracy, service levels, and cost efficiency.

Responsibilities

Enterprise Strategy & AI Vision

• Define the multi‑year strategy for agentic AI adoption, including architecture, platforms, operating models, and global rollout

• Drive the company’s evolution, in partnership with People Leaders, toward an agent‑augmented workforce, combining AI autonomy with human oversight

• Establish enterprise‑level standards for agent behavior, safety guardrails, performance telemetry, and lifecycle management

Process Re‑Engineering & Operational Excellence

• Partner with Operations, Technology, and Business Unit leaders to redesign processes to be automation‑ready, agent‑compatible, and data‑driven

• Enable end‑to‑end process redesign to unlock automation potential and remove structural inefficiencies across underwriting, claims, operations, and all other applicable functions

• Establish measurable operational KPIs and drive continuous improvement programs.

Product, Technology & Delivery Leadership

• Build and lead cross‑functional AI Companion/Agent development pods, including product owners, SWE, data scientists, process engineers, and SMEs

• Deliver and scale flagship agentic AI solutions including Companion Agents for high complexity work, Automation Agents for operations and back-office functions, and other agents as determined based on learnings and value opportunities

• Ensure seamless integration with enterprise systems and alignment with target‑state business processes

Architecture, Platform Decisioning & Governance

• Co‑lead AI platform evaluations and selections across vendors such as Anthropic, AWS, Palantir, and internal AI environments

• Direct the development of the services layer that enables agents to read/write into core systems safely and efficiently

• Partner with AI Governance to develop/enhance enterprise governance standards including AI lifecycle management, post‑deployment model monitoring, risk and compliance controls, transparent auditing and evaluation frameworks

Change Leadership & Enterprise Adoption

• Lead organizational change through education, upskilling, and partnership with HR on the future‑of‑work transition

• Develop and maintain an Agentic AI Inventory / System of Record to track use cases, maturity, adoption, performance, and ROI

Business Impact & Financial Accountability

• Drive quantifiable improvements in process throughput, underwriting and claims accuracy, customer servicing speed, cost reduction and efficiency, and workforce productivity

• Oversee benefit realization modeling, investment governance, and AI program financial performance.

Requirements

Experience

• 15+ years of progressive leadership in AI, analytics, digital transformation, intelligent automation, or enterprise technology

• 10+ years leading process‑improvement, Lean/Six Sigma, operational excellence, or large‑scale transformation in a complex global organization

• Insurance industry expertise is strongly preferred; deep familiarity with underwriting, claims, or policy administration is a plus

• Proven track record delivering AI or automation solutions at production scale

• Experience managing cross‑functional global teams and working with C‑level executives

Technical & Process Skills

• Deep knowledge of:

  • Agentic AI frameworks (tool‑use, planning, orchestration, RAG‑enhanced agents)

  • Enterprise AI architecture and services layers

  • LLM and multimodal model ecosystems

  • Document intelligence, ingestion pipelines, AutoExtract‑style classification/extraction, and automation patterns

• Mast