JOB SUMMARY:
The Manager, AI Enablement & Engineering is responsible for driving enterprise adoption, operationalization, support, and value realization of AI tools and solutions across the organization. This role leads the enablement and operational engineering strategy for AI technologies including copilots, internal AI agents, workflow automations, enterprise AI productivity platforms, and emerging AI-enabled business solutions. This is a player-coach leadership role responsible for leading AI enablement engineers, analysts, automation specialists, and technical resources to deliver scalable AI adoption, automation, training, support, governance, and operational capabilities across the enterprise. The role partners closely with business stakeholders, IT leadership, Security, Infrastructure, Enterprise Applications, and AI engineering teams to ensure AI solutions are effectively deployed, governed, supported, adopted, and optimized for measurable business impact. The Manager, AI Enablement & Engineering combines technical leadership, operational management, user enablement, change leadership, and AI governance responsibilities to accelerate responsible AI adoption while improving employee productivity, operational efficiency, and business outcomes.
SUMMARY OF ESSENTIAL JOB FUNCTIONS:
AI Adoption, Enablement & Strategy
- Define and execute the enterprise AI enablement and operationalization strategy.
- Develop programs to drive AI awareness, adoption, productivity, and measurable business value.
- Partner with executive leadership to align AI initiatives with organizational priorities and transformation goals.
- Establish success metrics, KPIs, and operational standards for AI adoption and value realization.
- Drive enterprise AI best practices, governance alignment, and standardized usage guidance.
AI Engineering & Solution Delivery
- Lead AI enablement engineers and technical specialists responsible for deployment, configuration, integration, and operational support of enterprise AI solutions.
- Oversee implementation and operationalization of AI copilots, internal AI agents, workflow automations, and AI-enabled productivity tools.
- Partner with AI engineering, infrastructure, and enterprise application teams to prioritize integrations, enhancements, and AI platform capabilities.
- Establish scalable operational processes, support models, technical standards, and documentation practices for AI-enabled services.
- Support evaluation, pilot programs, and rollout of emerging AI technologies and platforms.
- Ensure AI solutions align with enterprise architecture, security, governance, and compliance standards.
- Drive operational maturity, scalability, and continuous optimization of enterprise AI services.
Feedback, Analytics & Continuous Improvement
- Collect and analyze user feedback, adoption trends, support metrics, and operational analytics.
- Measure and report on AI adoption, productivity improvements, operational efficiencies, and business value realization.
- Develop executive reporting and dashboards demonstrating ROI and impact of enterprise AI initiatives.
- Identify gaps in usability, operational support, training effectiveness, or technical solution performance.
- Partner with engineering and business stakeholders to improve AI capabilities using data-driven insights.
- Drive continuous improvement initiatives focused on user experience, operational excellence, and AI effectiveness.
Training & Organizational Change Management
- Oversee development and delivery of enterprise AI training programs, onboarding, and enablement resources.
- Ensure effective education and support for tools including Microsoft Copilot, ChatGPT Enterprise, internal AI agents, automation platforms, and enterprise AI solutions.
- Lead organizational change management initiatives to accelerate adoption and responsible AI usage.
- Standardize enterprise AI usage guidance, playbooks, and best practices.
- Promote AI literacy and responsible AI behaviors across business and IT organizations.
AI Support Operations & User Experience
- Own the enterprise AI support model and end-user experience strategy.
- Manage AI support operations, ticketing processes, escalation workflows, and issue resolution coordination.
- Identify recurring user issues and drive proactive operational or technical improvements.
- Partner with engineering teams to troubleshoot and resolve complex AI platform issues.
- Ensure a high-quality, scalable, and secure user experience for enterprise AI capabilities.
AI Governance & Responsible AI
- Partner with Security, Legal, Compliance, and IT leadership teams to enforce responsible AI governance standards.
- Support governance processes for evaluating, approving, and operationalizing enterprise AI tools.
- Ensure AI usage aligns with data protection, privacy, compliance, and acceptable use policies.
- Promote secure and compliant usage of enterprise-approved AI technologies.
- Assist in development and communication of enterprise AI policies, standards, and operational procedures.
Team Leadership
- Lead and develop a multidisciplinary AI Enablement & Engineering team including enablement engineers, automation specialists, business analysts, and support resources.
- Establish team priorities, operational KPIs, delivery roadmaps, and service expectations.
- Manage workload prioritization, resource planning, and execution of AI initiatives.
- Provide technical and professional mentorship to team members supporting enterprise AI platforms and services.
- Foster a culture of innovation, experimentation, accountability, and continuous learning.
Vendor & Platform Management