AI Adoption & Enablement Leader Job Charleston area,South Carolina USA,IT/Tech

Job Description Summary

The AI Adoption & Enablement Leader drives the adoption of new AI tools and technologies, skills development, and change management across Wind Engineering. This role ensures that new AI capabilities are not only introduced, but effectively adopted, trusted, and sustained in day-to-day engineering work. The position leads training, communications, and community-building efforts that help teams build confidence and practical capability with emerging AI technologies, while also supporting integration into engineering workflows where they create measurable value.

This role owns the budget for AI enterprise costs and is accountable for ensuring that AI tool investments deliver sustainable, measurable value across Wind Engineering. Reporting to the Director – AI Strategy & Transformation, the ideal candidate is a people-oriented leader with a strong change management and learning design background who understands the engineering context in which AI is being deployed.

Key Responsibilities

Drive AI Tool and Technology Adoption Across Wind Engineering

Lead structured adoption plans for new AI tools and technologies, aligned with engineering priorities, workforce readiness, and user needs.
Partner with engineering teams to introduce, pilot, and scale AI tools and technologies that improve engineering workflows and productivity.
Identify and address adoption barriers, including usability, trust, access, workflow fit, and cultural resistance.
Track adoption rates, utilization patterns, and user satisfaction across deployed AI tools to inform prioritization and investment decisions.
Ensure that tools not achieving sustained adoption are escalated, re-evaluated, or rationalized.

Own and Govern the AI Enterprise Cost Budget

Own and actively manage the AI enterprise cost budget, including tools such as Git Hub Copilot, compute infrastructure, AWS Services and new technologies.
Push for sustainable, value-driven implementation of AI solutions, ensuring costs are justified by measurable adoption, utilization, and business value.
Partner with Finance and Digital/IT to maintain budget visibility, forecast spend, and provide leadership with clear cost-versus-value reporting.
Evaluate new tool and technology investments through a structured lens covering capability fit, cost sustainability, adoption likelihood, and alignment to Wind Engineering priorities.
Drive rationalization of tools that are underutilized, duplicative, or not delivering value relative to cost.

Develop AI Training, Enablement, and Skills Development Programs

Design, build, and maintain AI training and enablement programs that develop practical capability across Wind Engineering, from foundational AI literacy to advanced practitioner skills.
Tailor training to engineering roles and personas, ensuring relevance to how engineers, leads, and managers actually engage with AI in their workflows.
Develop role-based competency matrices that map to AI strategy and career progression expectations.
Continuously update training content to reflect new tools, evolving AI capabilities, governance requirements, and lessons learned from adoption.

Establish and Grow AI Communities of Practice

Create and sustain AI communities of practice across Wind Engineering to accelerate knowledge sharing, peer learning, and reuse of effective approaches.
Design community programming including working sessions, showcases, lunch-and-learns, collaborative problem-solving events, and recognition mechanisms.
Ensure community activity connects to broader AI strategy priorities, reinforcing focus areas, sharing portfolio wins, and surfacing emerging opportunities from practitioners.
Maintain visibility of community health through engagement metrics, contribution quality, and knowledge reuse indicators.

Lead AI Communications and Change Management

Develop and execute a Wind Engineering AI communications strategy that builds awareness, understanding, trust, and enthusiasm for AI across the organization.
Design and manage change management plans for significant AI capability introductions, tool rollouts, and workflow transitions.
Ensure communications are tailored to audience, from engineering practitioners to functional leaders to senior executives.
Proactively surface and address resistance, skepticism, or misalignment through structured engagement and targeted messaging.
Partner with the AI Process Transformation Lead to ensure adoption communications are synchronized with portfolio milestones and initiative timelines.

Measure and Improve Adoption, Usability, and Trust

Define and maintain a dashboard of adoption metrics across Wind Engineering's AI tool and capability portfolio, including utilization rates, active user trends, retention, workflow integration depth, and user-reported value.
Establish mechanisms to regularly capture user feedback on AI tool usability, reliability, trustworthiness, and workflow fit.
Use data to identify high-performing adoption patterns that can be replicated and…