The agentic AI revolution in retail
From vision to process reality
Andreas Späne, Harald Dutzler, Dr. Matthias Schlemmer, and Dr. Maik Hesse
Key findings
- Agentic commerce is moving from vision to impact: Agents will drive up to 15% of European e-commerce spending by 2030, with adoption at a pace of up to four times faster than traditional e-commerce
- Agentic AI delivers dual impact: Driving a 30% reduction in operational costs for customer service by 2029 while 89% of U.S. retailers report that AI initiatives positively impact revenue
- Value chains evolve from linear to autonomous: Agentic AI transforms the retail value chain from sequential workflows into continuously orchestrated, real-time ecosystems
- Agentic AI will redefine retail, the winners move early and build agent-ready foundations now
Agentic AI drives retail reinvention
The retail industry stands at a transformation point. Agentic AI marks a shift from experimental use cases to operational scale. The priority now is execution - embedding AI into core processes to drive efficiency, relevance, and growth.
What is agentic commerce?
Agentic commerce describes a shift from AI-assisted human decision-making to autonomous agents that negotiate, decide, and execute end-to-end economic transactions - across consumer shopping and enterprise procurement.
Agentic AI tackles rising retail complexity and operational pressure that current models can’t absorb:
- Geopolitical volatility demands continuous risk sensing and adaptive market compliance: 25% of German CEOs view geopolitical conflicts as their biggest threat. AI agents drive flexible real-time sourcing, pricing, and operations
- Supply chain upheaval requires real-time orchestration across fragmented networks: By 2030, the competition from fully-integrated ecosystems powered by AI is expected to grow by 40%. Tech players (Google, OpenAI, Anthropic) establish strong retail partnership networks
- Disruptive competitors leverage data-powered ecosystems and agentic platforms to shape supply and demand: Industry frontrunners already leverage agentic use cases from procurement to commerce. 17% of those adopting agentic AI do so in almost all workflows and functions
- Tech-savvy customers expect a coherent and personalized experience across channels: By 2030, 33% of consumers expect to make purchases with AI. Visibility is revenue-critical as LLMs become top-of-the-funnel
In this report, we explore how agentic AI revolutionizes the retail industry and outline enablers for building the agent-ready enterprise.
AI autonomy levels reshape retail and consumer markets
As retail moves from analytics to autonomous action, agentic AI evolves through distinct maturity stages to execute decisions at scale:
Agentic commerce is moving from vision to impact
- Agentic AI is driving a massive paradigm shift in retail, with adoption at a pace of up to than traditional e-commerce
- Agents will drive up to 15% of European e-commerce spending by 2030
- In Europe, agentic shoppers could drive 100+ EUR bn e-commerce revenues - up to 17 EUR bn in Germany
- One in two retailers are already assessing agentic AI - 20% have already deployed agents along the value chain
From linear value chains to autonomous agentic networks
Agentic AI transforms the retail value chain from sequential workflows into continuously orchestrated, real-time ecosystems.
Today's value delivery shifts from human-driven, tech-enabled, data-powered process execution to fluid and autonomous agent-driven orchestration and decision-making with humans-in-the-loop (HITL).
Principles of change
- 1 Agent-centric process redesign
- 2 Human–agent teams as default workforce model
- 3 Interoperable, agent-ready enterprise architecture
- 4 Adaptive, risk-based agent governance
- 5 Responsible, transparent agent design and deployment
Your roadmap to building an agent-ready enterprise
Moving from pilots to ROI requires focus, integration, and measurable performance discipline.
I. Detect high-value processes
- Stop experiments with defined "kill" criteria to reduce noise and increase focus
- Identify 2-3 end-to-end processes where agents can deliver tangible value (e.g., procurement, commerce replenishment, service)
II. Start small, scale fast
- Establish target-oriented, lean organization to facilitate agent use case ideation and validation
- Run focused lighthouse pilots, validate agent behavior with HITL oversight and boundaries
III. Ensure last-mile integration
- Ensure end-to-end operability of agents in live environments to unlock full value
- Integrate agents via stable, standardized interfaces to core retail systems (OMS¹, ERP, store-ops)
IV. Scale, measure, adapt
- Scale proven agents across the organization
- Industrialize delivery via reusable components and standard integration
- Establish performance loops using KPIs and telemetry
Dr. Florian Schneider, Dr. Tobias Kalsbach, Stefan Feyertag, Talib Qureshi, and Franziska Henn have contributed to this report.
