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Designing the Enterprise AI & Agentic Architecture Roadmap

AI StrategyAgentic ArchitectureEnterprise Integration
SAP, OMS, PIM
Systems Integrated
ML, GenAI, Agents
AI Capabilities
Core Retail
Scope
AI Architect
Role

The Challenge

QVC Group's Core Retail transformation required connecting transactional retail platforms - SAP S/4HANA, IBM OMS, and STIBO PIM - with advanced AI capabilities. The organization needed a cohesive architecture that could support large-scale ML, generative AI, knowledge graphs, and autonomous agent frameworks while ensuring end-to-end interoperability across data, processes, and decision systems.

My Approach

I defined and continue to evolve the enterprise AI and Agentic Architecture roadmap, ensuring that AI capabilities are not bolted on but deeply integrated into the retail technology landscape.

Architecture Integration

The roadmap addresses integration across three core enterprise platforms:

Each integration point is designed for interoperability - AI systems can consume and enrich data across these platforms without creating silos.

Agentic Framework

The architecture incorporates autonomous agent frameworks for retail-specific use cases, enabling AI systems that can reason, plan, and execute multi-step workflows with appropriate human oversight.

Key Decisions & Trade-offs

Interoperability first: Rather than building isolated AI capabilities, I prioritized end-to-end data flow across all enterprise systems. This added architectural complexity but ensures AI capabilities compound rather than fragment.

Agentic + traditional ML: The roadmap balances autonomous agent capabilities with proven ML approaches (forecasting, recommendations, classification), choosing the right paradigm for each use case.

Impact

The architecture provides a unified foundation for AI-driven personalization, operational optimization, and enterprise automation across QVC Group's Core Retail operations.