AI Enablement

Summary The AI Enablement Adoption Analyst drives hands-on AI adoption across Entravision's US workforce. Working alongside our AI enablement lead, this role turns AI capability into everyday, practical use - designing and delivering training, building enablement materials, running adoption programs, and prototyping lightweight solutions that show teams what is possible.

This is a people-first role at its core. The ideal candidate is energized by teaching and winning people over - meeting employees wherever they are, from those just getting comfortable with AI to advanced power users - and brings the communication skills, organization, and curiosity to move an entire organization up the AI curve.

Note: AI tool approval and governance are owned by Entravision's AI Review Committee. This role focuses on enablement, adoption, and applied AI.

Key Responsibilities

AI Enablement Training

• Design and deliver training programs, workshops, and hands-on labs on enterprise AI tools including Google Gemini, Anthropic Claude, NotebookLM, Gamma, and other deployed platforms.
• Create accessible, high-quality enablement materials - guides, short-form videos, and use case libraries - that help employees at all technical levels adopt AI effectively.
• Meet users across the full proficiency spectrum, from first-time users who feel overwhelmed by AI to advanced power users pushing the latest capabilities.
• Serve as a trusted internal resource and go-to expert for AI questions, translating capability into practical, role-specific workflows. AI Adoption Change Management
• Champion AI adoption across the organization by identifying departmental use cases, facilitating structured pilots, and iterating on enablement strategies.
• Define, track, and report on adoption metrics, using the data to refine programs and demonstrate impact.
• Partner with department leads to embed AI into real workflows and processes, turning training into sustained behavior change.
• Stay current with a fast-moving AI landscape and proactively surface relevant tools, features, and use cases to the business. Prototyping Applied AI
• Prototype lightweight AI-powered tools, automations, and applications that demonstrate feasibility and accelerate adoption across business functions.
• Leverage no-code, low-code, and light-code platforms (e.g., Claude Code, Replit, Apps Script, or similar) to build proof-of-concept solutions in close collaboration with stakeholders.
• Document prototypes, implementation notes, and handoff materials to support transition to engineering or platform teams when needed. Communication Stakeholder Engagement
• Prepare and present clear, business-oriented summaries of adoption trends and program results for leadership audiences.
• Develop internal newsletters, usage reports, and knowledge base content that keep stakeholders informed of AI developments and organizational wins.
• Coordinate with cross-functional partners across IT, HR, Sales, Finance, and Operations to ensure AI initiatives are well-aligned and sustainably supported.