Sabato Leo

• Proof-of-concept using a multi-agent architecture to replicate the internal decision

dynamics of a marketing department

• Agents work together using signals from traditional ML models (e.g. churn prediction,

personalization) to coordinate budgets, campaign strategies, and actions

• A hybrid system where humans remain in the loop to validate and approve outcomes,

reducing planning cycles from days to hours

• Personal AI generally refers to AI systems that are designed specifically for an individual, learning from their unique data and behaviors

• How enterprises are combining traditional ML-based personalization signals with GenAI agents to orchestrate dynamic, goal-driven marketing and customer engagement workflows

• Practical challenges in deploying agentic systems—from data integration and model oversight to aligning agent actions with brand, compliance, and campaign strategy

• The evolving role of AI teams, marketing leaders, and human reviewers in co-piloting agentic workflows that accelerate planning, content creation, and decision cycles

Personalization promises high-impact engagement, but most initiatives collapse under fragmented data, weak governance, and models that don’t scale. This masterclass explores how to design the data foundations and AI strategies that make hyperpersonalization sustainable — moving beyond pilots to enterprise-wide execution.

• Why most personalization initiatives stall without solid data foundations, and how to avoid common pitfalls

• Architecting scalable personalization with clean, connected, and governed data for AI-driven workflows

• Practical strategies to align data quality, orchestration, and AI models to deliver real-time, personalized experiences at scale

• Data Foundations for an agentic workflow orchestration