This unit examines how autonomous agents mature into enterprise platforms and how they are architected, orchestrated, and scaled within marketing systems. Students will explore data foundation requirements, market intelligence approaches, proof-of-concept considerations, and human transformation needs to prepare for pilot selection and deployment.
Learning Objectives
- Analyze the autonomous agent ecosystem and differentiate stages of platform maturity, including enterprise platform characteristics and implications for marketing operations
- Demonstrate the sense-reason-act architecture by mapping agent workflows and explaining multi-agent orchestration patterns relevant to customer-facing marketing use cases
- Apply principles for building a unified data foundation by proposing data integration, governance, and quality requirements for an agent-based marketing proof of concept
- Evaluate organizational readiness and human transformation requirements to select an appropriate pilot tier (e.g., customer service) using criteria for ROI, scalability, and stakeholder alignment
Curriculum
- 1 Section
- 12 Lessons
- 30 hours
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- Unit 2 — Enterprise Autonomous Agent Foundations12
- 1.1The Autonomous Agent Ecosystem Landscape20 mins
- 1.2Why Enterprise Platforms Represent Agent Maturation20 mins
- 1.3The Sense-Reason-Act Architecture: How Autonomous Agents Work20 mins
- 1.4Multi-Agent Orchestration20 mins
- 1.5The Reltio Results: Proof of Concept at Scale20 mins
- 1.6Notes20 mins
- 1.7The Two Paths to Market Intelligence20 mins
- 1.8The Evolution from Einstein GPT to Agentforce20 mins
- 1.9Building the Unified Data Foundation20 mins
- 1.10Human Transformation Requirements20 mins
- 1.11Notes20 mins
- 1.12Tier Selection: Starting with Customer Service20 mins
Instructor
Free
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