Director, Enterprise AI Operations
New
F
ForbesMedia
This position is only open to candidates residing in California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Maine, Maryland, Massachusetts, New Jersey, New York, North Carolina, Pennsylvania, South Carolina, Tennessee, Texas, & Washington.Full-TimeDirector
Salary180,000 - 195,000 USD per year
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Job Details
- Experience
- 8–12+ years
- Required Skills
- Artificial IntelligenceData AnalysisStakeholder managementChange Management
Requirements
- 8–12+ years of experience in transformation, operations, product, platform, or program leadership.
- Proven track record in building and scaling AI operations or large-scale enterprise operational programs.
- Strong change management experience, specifically driving adoption in large or complex organizations.
- Experience defining and managing operational standards, workflows, and governance frameworks.
- Demonstrated ability to execute complex cross-functional initiatives with competing priorities.
- Strong operational and execution instincts with the ability to create scalable implementation plans.
- Hands-on experience applying AI/LLMs to operational workflows.
- Data-driven mindset with experience tracking operational impact and adoption metrics.
- Exceptional organizational and stakeholder management skills.
- Comfortable operating in ambiguous, high-visibility executive environments.
Responsibilities
- Execute and operationalize internal AI roadmap in partnership with executive leadership.
- Drive implementation of high-impact AI initiatives that improve workflows and outcomes.
- Translate strategic priorities into scalable operational programs, processes, and execution plans.
- Lead enterprise-wide AI adoption efforts across editorial, audience, revenue, and corporate functions.
- Build and scale enablement systems, training programs, and operational playbooks.
- Own end-to-end change management processes and maintain an internal AI community of practice.
- Establish operational standards for AI usage, governance, sourcing, and disclosure.
- Monitor AI tooling ecosystem, operational risks, and reputational concerns.
- Build reporting frameworks to track AI adoption, workflow efficiency, and business ROI.
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