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AI Transformation Lead - Global Legal & Compliance
Liberty Mutual Insurance · Boston, MA
Publicada em 03/11/2026
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Description AI Transformation & Strategy exists to make AI a practical, embedded capability across Global Legal & Compliance, not an experiment on the side, but a core part of how we work, deliver, and create value for the enterprise. This pillar drives GL&C's ability to responsibly adopt, scale, and govern AI and emerging technologies in service of our 2030 vision: to serve as both a protector of the enterprise and an accelerator of Liberty Mutual's ability to win in the markets where we compete.This role sits within the newly formed GL&C Data Office, under the Strategy, Intelligence & Integration organization, at a defining moment for GL&C and Liberty Mutual. The Transformation Lead will report to the GL&C Data Officer. They will connect AI strategy directly to data governance, analytics, product management, and knowledge management so that GL&C's AI investments are grounded in trusted data, aligned to GL&C priorities, and built to compound over time.The AI Transformation Lead will design GL&C's holistic AI strategy and roadmap to execution for 2030, focusing on the most critical AI value drivers for GL&C by quarterbacking initiatives that are highly complex, cross-functional, and cross-imperative. They will be responsible for effectively driving solutions to enable us to achieve our GL&C 2030 goals and productivity targets.The Transformation Lead will effectively synthesize diverse perspectives into a cohesive and aligned AI Transformation strategy by bringing the right voices to the table, building mutual trust and strong relationships, and allowing for vigorous debate. They will drive a unified vision across senior leaders and key stakeholders inside and outside of the SBU, while ensuring initiatives are in alignment with strategic business priorities.Ultimately, the Transformation Lead needs to leverage varying resources to build the plan and infrastructure that will turn strategy into reality, ensuring robust e
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