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AI Adoption Manager

Job in City of Rochester, Rochester, Monroe County, New York, 14602, USA
Listing for: Butler/Till
Full Time position
Listed on 2025-12-31
Job specializations:
  • IT/Tech
    AI Engineer, Data Analyst
Job Description & How to Apply Below
Location: City of Rochester

Strategic HR Partner with proven leadership in Talent Relations/Strategy, Culture, and Organizational Development

Butler/Till is a results‑driven marketing agency offering deeply collaborative client experience, proprietary technology, and world‑class partnerships. At Butler/Till, we take immense pride in our independent, women‑owned and led status, our unwavering commitment to a purpose‑driven approach, our B‑Corp status, and our unique structure as a 100% employee‑owned company (ESOP).

SUMMARY

The AI Adoption Manager leads the full lifecycle of AI enablement across the agency — from initial rollout of enterprise AI tools to long‑term optimization of advanced capabilities. This role bridges configuration, training, adoption, and governance to ensure Butler/Till extracts maximum value from its AI investments. In addition to driving training and adoption, this role plays a critical part in configuring AI bots and models to meet the unique needs of functional teams, balancing innovation with security, compliance, and risk management.

Acting as both strategist and hands‑on enabler, the AI Adoption Manager ensures that AI solutions evolve in step with business requirements and deliver measurable, ethical, and scalable impact.

Key Outcomes & Responsibilities

Key Outcome: Implement and manage the enterprise rollout and full lifecycle management of AI tools to ensure smooth deployment, adoption, and continuous optimization across the agency.

  • Lead the staged rollout of enterprise AI solutions (e.g., Microsoft Copilot, embedded AI in SaaS platforms).
  • Manage the lifecycle from onboarding to adoption, feature expansion, and ongoing optimization.
  • Partner with IT and Business Transformation to ensure seamless implementation and integration.
  • Establish pilot groups across diverse functions to gather insights and refine rollout plans.
  • Define, communicate, and manage the AI rollout timeline with clear milestones and deliverables.
  • Track and report on pilot outcomes, using data and feedback to inform future rollouts and ongoing optimization.
  • Strategically assign AI licenses to high‑impact teams and priority use cases during initial rollout.
  • Monitor license utilization and continuously optimize allocation to ensure maximize business value and ROI.
  • Define adoption and utilization KPIs, tracking across functions.
  • Quantify impact in terms of productivity gains, error reduction, and quality improvements.
  • Align metrics with business outcomes, focusing on productivity, efficiency, quality, and employee experience.
  • Continuously evolve AI usage to align with business and client needs.

Key Outcome: Configure and train AI bots and models to deliver accurate, role‑specific, and business‑aligned outputs across departments.

  • Serve as the functional “trainer” of AI bots and models to meet specific departmental needs (e.g., Media Ops, Analytics, Creative, Finance).
  • Configure AI settings, prompts, workflows, and integrations to ensure relevant, high‑quality outputs.
  • Maintain AI system accuracy by curating datasets, refining configurations, and managing contextual knowledge.
  • Partner with IT and data governance to ensure configurations meet security and compliance standards.

Key Outcome: Drive agency‑wide AI Adoption through training, enablement, and continuous learning.

  • Design and deliver role‑based training programs, ensuring confidence and compliance in AI use.
  • Establish “always‑on” enablement resources including toolkits, office hours, and user communities.
  • Build and sustain a Copilot user community to encourage peer learning and best practices.
  • Identify and empower AI champions and early adopters to promote engagement and support.
  • Facilitate feedback loops and document use cases to showcase success and innovation across functions.
  • Implement structured feedback mechanisms (surveys, focus groups, direct channels) to inform ongoing improvements.

Key Outcome: Drive organizational readiness and engagement through effective change management and transparent communication.

  • Establish and lead an AI Council with executive sponsors and cross‑functional stakeholders, to guide strategy, adoption, and governance.
  • Develop and execute a comprehensive change management
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