AI Adoption Manager
Franklin Fitch, Atlanta, GA, United States
The AI Adoption Manager is responsible for leading the enterprise-wide adoption, implementation, and evolution of artificial intelligence capabilities across the organization. Acting as both a strategist and hands-on builder, this role translates AI potential into practical solutions that improve operational efficiency, unlock the value of organizational data, and embed AI into the daily workflows of teams across the business.
This role owns the full lifecycle of AI enablement - from identifying high-impact opportunities and designing AI strategies to configuring tools, training teams, managing governance, and measuring business outcomes.
Key Outcomes & Responsibilities
Identify and prioritize high-impact AI use cases across the enterprise.
Assess AI readiness, current initiatives, and data maturity.
Develop and communicate an enterprise AI strategy aligned to business goals.
Deliver quick-win pilots to demonstrate early value and build momentum.
Lead staged rollout and configuration of enterprise AI tools.
Build and deploy AI solutions (e.g., knowledge assistants, automation workflows).
Partner with IT for secure integration and system optimization.
Manage pilot programs, refine use cases, and scale successful initiatives.
Design and deliver role-based AI training programs.
Build internal AI champion networks and user communities.
Execute change management strategies to ensure adoption and reduce resistance.
Communicate AI value, purpose, and responsible usage across teams.
Assess and improve enterprise data quality, accessibility, and integration.
Collaborate with data teams to strengthen governance and hygiene.
Ensure AI initiatives are based on trusted and compliant data sources.
Implement AI governance, privacy, and ethical standards.
Conduct audits of AI outputs, usage, and data to mitigate risk.
Balance innovation with security, compliance, and brand safety.
Track AI adoption, utilization, and business impact.
Optimize AI tool allocation and ROI.
Capture success stories and continuously improve AI capabilities.
Qualifications
Bachelor’s degree in Business, IT, Data Science, or related field.
Experience in enterprise software implementation, digital transformation, AI enablement, or product ownership.
Hands-on experience configuring or implementing AI tools, chatbots, automation platforms, or SaaS solutions.
Strong understanding of change management and technology adoption practices.
Knowledge of data governance, privacy, and security considerations related to AI.
Experience working with platforms such as Microsoft Copilot, Azure AI, OpenAI, or similar technologies.
Familiarity with data integration, analytics platforms, or master data management practices.
Certifications in AI governance, change management, or enterprise architecture.
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This role owns the full lifecycle of AI enablement - from identifying high-impact opportunities and designing AI strategies to configuring tools, training teams, managing governance, and measuring business outcomes.
Key Outcomes & Responsibilities
Identify and prioritize high-impact AI use cases across the enterprise.
Assess AI readiness, current initiatives, and data maturity.
Develop and communicate an enterprise AI strategy aligned to business goals.
Deliver quick-win pilots to demonstrate early value and build momentum.
Lead staged rollout and configuration of enterprise AI tools.
Build and deploy AI solutions (e.g., knowledge assistants, automation workflows).
Partner with IT for secure integration and system optimization.
Manage pilot programs, refine use cases, and scale successful initiatives.
Design and deliver role-based AI training programs.
Build internal AI champion networks and user communities.
Execute change management strategies to ensure adoption and reduce resistance.
Communicate AI value, purpose, and responsible usage across teams.
Assess and improve enterprise data quality, accessibility, and integration.
Collaborate with data teams to strengthen governance and hygiene.
Ensure AI initiatives are based on trusted and compliant data sources.
Implement AI governance, privacy, and ethical standards.
Conduct audits of AI outputs, usage, and data to mitigate risk.
Balance innovation with security, compliance, and brand safety.
Track AI adoption, utilization, and business impact.
Optimize AI tool allocation and ROI.
Capture success stories and continuously improve AI capabilities.
Qualifications
Bachelor’s degree in Business, IT, Data Science, or related field.
Experience in enterprise software implementation, digital transformation, AI enablement, or product ownership.
Hands-on experience configuring or implementing AI tools, chatbots, automation platforms, or SaaS solutions.
Strong understanding of change management and technology adoption practices.
Knowledge of data governance, privacy, and security considerations related to AI.
Experience working with platforms such as Microsoft Copilot, Azure AI, OpenAI, or similar technologies.
Familiarity with data integration, analytics platforms, or master data management practices.
Certifications in AI governance, change management, or enterprise architecture.
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