• Support AI Adoption and Enablement Across Teams • Partner with agency and functional leaders to identify opportunities to integrate AI into workflows • Support development and execution of AI training and enablement programs • Help create role-specific playbooks and best practices • Coordinate AI workshops, office hours, and internal enablement sessions • Support development of an internal network of AI champions • Manage Bottoms-Up AI Use Case Pipeline • Collect and organize AI use cases from teams across agencies and functions • Maintain a structured intake and tracking system for use cases • Categorize opportunities based on impact, feasibility, and alignment with priorities • Partner with the AI Generalist and technical teams to support early-stage validation • Support Prioritization and Leadership Reviews • Prepare use cases for review by leadership and decision-makers • Summarize expected benefits, required effort, and dependencies • Support prioritization discussions and documentation of decisions • Ensure alignment with broader AI initiatives and priorities • Assist with Workflow Integration and Pilot Execution • Work with teams to integrate AI into existing workflows • Support pilot execution and capture feedback • Document successful use cases and contribute to scaling efforts • Help standardize repeatable approaches across teams • Capture and Organize Client AI Signals • Gather AI-related requests, needs, and trends from client-facing teams • Organize and synthesize inputs across agencies • Share insights with AI leadership to inform priorities and capability development • Track Productivity Impact and Support Reporting • Help track time savings and efficiency improvements from AI use cases • Support development of reporting on productivity and adoption • Maintain visibility into use case pipeline progress and outcomes • Coordinate Across AI, IT, and Business Teams • Work closely with the AI transformation team and Senior Director • Partner with IT and architecture teams to align on feasibility and scaling • Help ensure use cases follow the defined AI lifecycle

• Build analytical and financial models that quantify the business impact of AI capabilities across Autodesk’s platform and industry groups • Develop forecasts for AI adoption, usage, revenue influence, and long-term planning • Construct business cases and decision-ready analysis to guide investment, prioritization, and leadership reviews • Model and optimize inference cost economics (COGS), including GPU utilization, cloud strategy, and scaling drivers • Translate product telemetry into insights supporting monetization, pricing, and cross-industry growth opportunities • Create executive- and Board-ready presentations, narratives, and slide materials that communicate strategic recommendations, investment plans, and business priorities with clarity and impact • Contribute to building repeatable dashboards, reporting frameworks, and tools to enable data-driven execution across Product, Finance, and Engineering teams

• Owns the curriculum that makes the shift to AI successful • Facilitates executive coaching sessions • Builds connections with customers to surface use case candidates • Contributes to the Provectus enablement playbook

• Represent Pacvue’s AI Vision with Customers • Serve as a senior customer-facing voice for Pacvue on AI, machine learning, Pacvue Agent, agentic workflows, automation, measurement intelligence, and the future of commerce media. • Engage directly with enterprise brands, agencies, retailers, and strategic partners to understand their AI priorities, concerns, workflow gaps, and adoption barriers. • Support executive briefings, customer advisory boards, strategic sales conversations, industry events, and thought leadership. • Translate customer feedback into AI strategy, experimentation themes, product priorities, and roadmap decisions. • Lead Pacvue’s AI, ML, and Data Science organization across experimentation, applied models, recommendations, optimization, measurement intelligence, forecasting, workflow automation, and agentic AI. • Partner closely with existing AI and Data Science leaders to scale the organization, strengthen execution, and increase the impact of AI across customer-facing products. • Create operating clarity across AI Labs, production ML/AI, Data Science, Pacvue Agent, and agentic workflows, ensuring clear ownership, priorities, evaluation criteria, and product impact. • Ensure our AI, ML and Data Science teams are aligned, focused and executing seamlessly. Building a world-class AI team is paramount for our success and this leader must be as passionate about talent as they are the product and innovation they lead. • Accelerate Pacvue Agent as a core AI experience across the platform, directing the team, helping customers move from insight to action through trusted, explainable, workflow-embedded AI. • Lead Pacvue’s agentic AI strategy across customer workflows, internal productivity, decision support, and governed automation. • Define where AI should recommend, explain, act, escalate, and learn within customer and internal workflows. • Partner with Product Growth and Customer Success to ensure AI capabilities are adopted, trusted, and connected to measurable customer outcomes. • Lead AI Labs, focused on rapid experimentation, prototyping, and validation of emerging AI capabilities. • Identify high-potential AI use cases, test them quickly, and determine which should graduate into production roadmaps. • Create a disciplined experimentation model that balances speed, customer value, feasibility, responsible AI practices, and business impact. • Own the product and technical direction for ML, AI, and Data Science capabilities across recommendations, optimization, forecasting, measurement intelligence, workflow automation, and performance insights. • Partner with Product, Engineering, and AI/DS leaders to turn models and AI capabilities into reliable, scalable, explainable product experiences. • Drive decisions around model quality, explainability, trust, governance, evaluation, and adoption.