AI Adoption Manager

SUMMARY

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).

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 maximum 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 information.
• 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 plan that includes proactive communication, role‑based training, and clear expectation setting.
• Foster a culture of trust, transparency, and continuous learning around AI adoption.
• Build trust and transparency by addressing resistance, clarifying AI’s role, and fostering a culture of continuous learning.

Key Outcome
:
Strengthen data privacy, governance and hygiene to ensure secure, compliant, and ethical AI usage.

• Co‑own the enterprise data hygiene strategy, collaborating with IT and data teams to ensure quality, accessibility, and compliance.
• Review, enforce, and continuously improve data governance policies, focusing on security, privacy, regulatory compliance, and ethical use.
• Conduct regular audits of data sources, permissions, and AI outputs for accuracy and mitigate risk.
• Balance configuration flexibility with robust data security, and…