AI Enablement Lead

Canal Insurance Company•Greenville, SC

3d•Hybrid

About The Position

Canal Insurance Company, a commercial trucking and specialty transportation insurer founded in 1939 and based in Greenville, South Carolina, is seeking an AI Enablement Lead to move the enterprise from isolated AI experiments to scaled, governed, business-embedded adoption. This hybrid strategic and tactical role owns the AI adoption strategy and outcomes, connecting business stakeholders, IT teams, and governance functions to deliver trusted AI solutions. The role defines enterprise AI priorities, builds support for AI across the organization, identifies and delivers high-value business use cases, and drives AI adoption within IT and engineering. It also leads enterprise adoption of Microsoft Copilot and other licensed AI productivity tools, establishes AI governance policies and approval processes, and works with Legal, Risk, Compliance, and Security to address regulatory and operational risks. Success in the first 12 months includes an approved and operational AI adoption strategy and governance framework; business use cases moved from pilot to scaled production with measured ROI; increased active use of Copilot or other enterprise tools; measurable improvements in engineering delivery metrics attributable to AI; an operating AI governance council; and no material AI-related compliance or risk incidents.

Requirements

At least 8 years of experience in technology strategy, digital transformation, or enterprise IT.
At least 2 years of recent hands-on AI or generative AI implementation experience.
Demonstrated experience translating business problems into deployed AI solutions, beyond advisory or strategy-deck work.
Experience driving AI or tooling adoption within an engineering or IT organization, with understanding of the software development life cycle and developer workflows.
Experience leading enterprise rollouts of Copilot, ChatGPT Enterprise, or comparable AI tools at scale.
Working knowledge of AI governance frameworks and emerging regulation, such as the EU AI Act, NIST AI RMF, ISO/IEC 42001, or equivalent.
Strong stakeholder management skills and credibility with business executives and engineering leadership.
Experience building and running cross-functional programs involving Legal, Compliance, Security, and Data teams.
Ability to work at both strategic and tactical levels, including roadmap development, board reporting, pilot design, adoption metrics, and hands-on rollout.

Nice To Haves

Prior experience in a Head of AI Enablement, AI Transformation, or similar hybrid role.
Consulting background implementing AI programs, or in-house experience scaling AI beyond the pilot stage.
Familiarity with Microsoft's AI stack, including Copilot, Azure AI, and Power Platform, or an equivalent enterprise AI ecosystem.
Experience establishing an AI Center of Excellence or governance council from scratch.

Responsibilities

Define and own an enterprise AI adoption strategy aligned with business priorities and the operating model.
Build executive buy-in, business-unit champions, and organization-wide enthusiasm for AI.
Identify, prioritize, and build business cases for high-value AI use cases across functions.
Translate business problems into AI-enabled solutions and represent AI strategy and progress to executive leadership and the board as needed.
Partner with business-unit leaders to identify workflows where AI can improve speed, quality, or cost.
Own delivery of prioritized use cases from business case and pilot through scaled deployment and value measurement.
Manage a prioritized AI use-case pipeline or roadmap and track return on investment.
Establish repeatable frameworks for evaluating, piloting, and scaling AI solutions.
Drive AI adoption within IT and engineering to improve development speed, code quality, and delivery efficiency.
Own rollout, training, and adoption strategy for developer-facing AI tools.
Partner with engineering leadership to embed AI into the software development life cycle, including code generation, testing, code review, documentation, and incident response.
Define and track adoption and efficiency metrics for AI-assisted engineering.
Own the enterprise adoption strategy for Microsoft Copilot and other licensed AI productivity tools.
Design and run enablement programs, including training, champions networks, use-case libraries, and adoption campaigns.
Track and report actual tool usage, workflow integration, and productivity impact, beyond licenses issued.
Partner with procurement and vendor management on tool rationalization and licensing strategy.
Build and own the enterprise AI governance framework, including policies for responsible use, data handling, model risk, and human oversight.
Establish approval workflows and accountability models for AI deployed in business-critical processes.
Partner with Legal, Risk, Compliance, and Security to align with regulatory requirements.
Own the AI risk register and maintain a documented, auditable decision trail for AI systems in production.
Establish an AI governance council with clear escalation and sign-off processes.