Director, Marketing AI Transformation

A day in the life (Responsibilities)

Develop and Execute AI Transformation Strategy:

• Define and implement a comprehensive AI transformation roadmap aligned with marketing leadership's strategic direction and overall business objectives.
• Translate strategic bets into sequenced adoption plans that account for team readiness, tool maturity, and infrastructure dependencies.
• Identify and prioritize the workflows where AI creates the most leverage and build the playbook for redesigning them.

Drive Change Management and Adoption:

• Build and run programs that drive sustained AI adoption, including practical enablement resources, scalable training programs, and change management approaches that meet teams where they are.
• Own the metrics that distinguish real adoption from performative adoption, tracking workflow changes and behavior shifts rather than training completion rates alone.
• Champion a culture where marketers see AI as a tool for creativity and efficiency rather than a disruption to manage.

Build AI Governance Frameworks:

• Design and implement the standards, review processes, and decision frameworks that let teams move fast while maintaining brand consistency, quality, and compliance.
• Establish how AI generated content gets reviewed before it ships, how parallel agent builds get evaluated and consolidated, and how we define quality when AI is generating at volume.
• Navigate the tension between speed and standardization, building systems that enable both.

Design Workflow Transformation:

• Partner with marketing leaders to break roles down into workflows and identify which should be automated, redesigned, or augmented with AI.
• Build transition plans that move teams from current state to AI augmented operations.
• Serve as the bridge between what gets built by the GTM engineering team and what gets adopted by marketing teams.

Operationalize the AI Champions Network:

• Recruit, onboard, and support 1 to 2 Champions per marketing team who serve as local AI resources and early adopters.
• Give Champions a platform (dedicated Slack channels, demo slots, direct line to the GTM engineering team) and use them as a feedback loop for what is working and what is not.
• Scale peer to peer knowledge sharing as the primary mechanism for broad adoption.

Measure and Report on Transformation Progress:

• Build the measurement framework for AI transformation: adoption rates, workflow efficiency gains, time savings, and output quality.
• Design executive facing dashboards that give leadership honest, clear visibility into where AI is delivering value and where it is not.
• Partner with HR to factor AI proficiency into performance expectations.

Cross-Functional Collaboration:

• Partner with GTM Engineering to prioritize tooling and workflow needs based on real adoption data.
• Work with marketing leaders to embed AI into team goals and quarterly planning.
• Collaborate with HR/Learning & Development to build AI capability building into the organization's learning infrastructure.