VP, Human–AI Experience & Adoption

Chubb•Philadelphia, PA

18d

About The Position

This role sits at the intersection of human centered design, enterprise AI strategy, and organizational change, with a clear mandate: prove how AI should work for people at Chubb, then scale it across the enterprise. Chubb is building AI infrastructure that will fundamentally change how work gets done. We are moving toward a future where employees can query decades of institutional knowledge, generate documents grounded in organizational context, and surface insights from emails, meetings, and internal systems through natural, conversational interaction with AI. The VP, Human–AI Experience & Adoption exists to make that future real. You will serve as the connector among users, technologists, and senior leaders across Global Data & Analytics, advancing the vision, building early examples, and driving adoption of AI native productivity tools. This is not a theoretical or advisory role. You will design, build, deploy, and iterate, demonstrating what’s possible before scaling solutions across the enterprise. Our credibility and product insight depend on being exemplary AI users ourselves. This role exists to break through institutional inertia, challenge “the way we have always done it” and make our AI-team the most AI-augmented team at Chubb. Insurance runs on knowledge (judgment, experience, interpretation, and history). Today, much of that knowledge is fragmented across people, emails, and documents. AI can unlock it, but only if it is designed for humans. This role is the tip of the spear: proving that AI‑native knowledge infrastructure works by deploying it first with the teams building AI at Chubb. If we can’t make it valuable, trusted, and intuitive for ourselves in Data & Analytics, we should not expect the enterprise to adopt it. You will help define the tools and experiences that drive how work evolves at Chubb, an exciting “pace car of the possible”.

Requirements

Skills & Attributes Critical for Success Deeply conversant in AI and large language model capabilities and limitations; able to separate hype from value
A builder and change leader who modernizes how organizations work, not just by shipping tools, but by reshaping operating models
Comfortable leading in ambiguity, influencing without authority, and operating in large, complex enterprises
A compelling communicator who can earn executive sponsorship and bring skeptical stakeholders along
Biased toward action: you ship early, learn fast, and iterate continuously
Experienced in consulting, product strategy, platform, or process/people change leadership roles where adoption mattered as much as delivery
Qualifications 10+ years in technology, data, AI, product, or change leadership roles
Proven track record leading cross‑functional initiatives in large enterprises; regulated industry experience preferred
Experience building or deploying AI products, knowledge platforms, or enterprise productivity tools
Strong grounding in user research, prototyping, and iterative delivery
Demonstrated ability to lead diverse technical teams and drive human adoption of complex systems
Deep practitioner-level fluency with LLMs and AI tools – you should be a power user yourself
Working knowledge of AI/ML concepts, design thinking, and change management; familiarity with AI ethics
Intellectual curiosity and business judgment prioritized over specific degrees

Nice To Haves

Bachelor’s or advanced degree in Human Computer Interaction, Cognitive Science, UX, AI, or related field preferred
Portfolio, writing, or examples that show how you think about human–AI collaboration
Important: You do not need to have held a role titled “Human–AI” before. If you have led technology‑driven change, built products or platforms, redesigned workflows, or driven enterprise adoption, you are strongly in scope.

Responsibilities

Enterprise AI Strategy & Adoption Leadership Identify where AI can materially improve how people work, prioritizing impact over experimentation
Partner with Data & Analytics leadership to define AI adoption roadmaps grounded in real user needs
Lead working sessions, labs, and workshops to educate, energize, and mobilize teams
Articulate how connected AI systems transform productivity, decision‑making, and institutional memory
Translate emerging AI capabilities into practical, human‑centered solutions that deliver measurable outcomes
Human Centered AI Experience Design Define intuitive, trustworthy interaction models for AI‑powered tools across Data & Analytics
Identify high‑impact use cases; prioritize ruthlessly and prototype quickly to prove value
Balance automation with transparency, explainability, and user control to build trust
Conduct deep user discovery and usability testing to surface real friction points
Design and refine end‑to‑end human–AI journeys, including feedback and learning loops
Establish and evangelize clear design principles for responsible, human‑first AI
Build and lead a small, high‑impact team of engineers and data specialists delivering internal AI knowledge infrastructure
Address cultural barriers preventing adoption e.g., “I am faster doing it myself” mindset or simply workflow inertia
Cross Functional Partnership & Scaling Impact Partner across product, engineering, legal, compliance, and business teams to ensure responsible rollout
Implement feedback loops and metrics to track adoption, trust, and productivity impact
Navigate data governance, privacy, and security requirements in a regulated environment without stalling progress
Act as an internal thought leader, expanding what leaders believe is possible while grounding expectations in reality
Codify patterns, playbooks, and standards that can extend beyond Data & Analytics to the broader enterprise