AI Adoption Manager - name

Job Description:

The AI Adoption Manager drives the successful rollout, scaling, and sustained use of AI capabilities across the organization. This role focuses on enabling teams, reducing friction, building advocacy networks, and measuring adoption so that AI solutions translate into real business value through effective training, usability improvements, and continuous improvement.

Responsibilities: Lead AI Enablement, Training & Advocacy Develop and execute programs that help departments understand, adopt, and effectively use AI capabilities.

Drive training and enablement programs that improve understanding and use of AI tools and workflows

Build, manage, and grow a champions network that accelerates adoption and shares best practices

Promote awareness of AI capabilities in ways that connect technical functionality to business value

Drive Adoption Measurement & Friction Reduction Measure usage and identify barriers so adoption can scale effectively and sustainably.

Track adoption metrics and success indicators across the organization

Identify friction points preventing teams from leveraging AI solutions effectively

Partner with stakeholders to improve usability, accessibility, and overall experience of AI-driven tools

Scale Commercialization & Continuous Improvement: Create repeatable approaches for scaling AI usage, strengthening user value realization, and informing future improvements.

Develop strategies and frameworks that support broad adoption and commercialization of AI capabilities

Gather user and champions feedback to inform enhancements and improve outcomes over time

Partner across product, operations, and business functions to ensure AI initiatives are not only launched, but actively adopted and delivering measurable value

Requirements:

Bachelor's degree in Business, Marketing, Communications, Operations, Product, Organizational Development, or a related field, or equivalent work experience.

3–5 years of experience leading adoption, enablement, training, commercialization, or change management initiatives at scale.

Hands-on proficiency with modern AI tools and generative AI assistants (such as Claude, ChatGPT, or Copilot), including practical experience with effective prompting and a working understanding of what these tools can and cannot reliably do. A solid conceptual grasp of how AI capabilities apply to real business workflows is essential—deep technical or machine-learning expertise is not required, but candidates must be credible, enthusiastic practitioners who can teach others and lead by example.

Strong stakeholder engagement and community-building skills, experience defining and tracking adoption metrics, and the ability to identify user friction and improve workflows or experience.