Industry Primer for Consumer Goods: Technology, Innovation, and AI
1h 30mBeginner2026-07-27
Authors

Starweaver
Course details
Get a working knowledge of the technology stack behind consumer goods, from the core systems that run retail and CPG operations to the AI use cases now shaping pricing, promotion, and shopper engagement.
Start with the core systems, including enterprise resource planning, supply chain planning, and digital experience platforms. See how cloud adoption, workflow automation, and unified data platforms are modernizing them without disrupting commercial continuity. Move on to AI: pricing, promotion, demand sensing, shopper insights, agentic commerce. Look at where it delivers and where it fails, and how governance keeps commercial decisions accountable. The course concludes by mapping the consulting opportunities across AI strategy, technology modernization, data, and automation.
Start with the core systems, including enterprise resource planning, supply chain planning, and digital experience platforms. See how cloud adoption, workflow automation, and unified data platforms are modernizing them without disrupting commercial continuity. Move on to AI: pricing, promotion, demand sensing, shopper insights, agentic commerce. Look at where it delivers and where it fails, and how governance keeps commercial decisions accountable. The course concludes by mapping the consulting opportunities across AI strategy, technology modernization, data, and automation.
Concepts
Introduction
- Getting started
Technology Landscape Overview
- Core systems and the industry tech stack, part 1
- Core systems and the industry tech stack, part 2
- Infrastructure and security considerations
- Emerging technology trends and adoption patterns
Digital Transformation Trends
- Cloud, automation, and the role of data
- Transformation challenges and customer experience
AI and Advanced Analytics in the Industry
- Decision intelligence and AI maturity
- AI use cases and associated risks, part 1
- AI use cases and associated risks, part 2
Innovation and Emerging Technologies
- Emerging technologies and innovation models
- Platform shifts and ecosystem change
Technology Challenges and Risks
- Legacy constraints and data quality
- Security, compliance, and change management
Consulting Opportunities in Tech and AI
- AI strategy and technology modernization
- Data strategy and automation initiatives
Conclusion
- Course wrap-up