Retail has long embraced automation to streamline operations. From rule-based replenishment to predictive analytics, technology has helped teams work faster and more efficiently. But today, ambitious leaders are looking beyond automation. They’re asking a new question: What happens when AI becomes a teammate, not just a tool?
Enter Humans + Agents. In this model, intelligent agents don’t just assist, they act. They monitor sales data, propose merchandising changes, initiate fulfillment shifts, and learn from outcomes. Humans don’t step aside, they step into more strategic roles: reviewing, approving, and guiding. And powering this collaboration is a composable infrastructure, built to support distributed, adaptive agent frameworks.
This article explores how platforms like Fluent Order Management (Fluent OMS) are enabling this transformation— turning agentic workflows into production reality, without the need to replatform or bet the farm.
From Automation to Agency
Automation in retail has served its purpose. It’s helped teams offload repetitive tasks and enforce consistency. But it’s always been limited by static rules. It waits for a trigger. It doesn’t reason, adapt, or initiate.
Agentic systems are different. They pursue goals. They connect across systems, learn from patterns, and make decisions. As Orium’s Humans + Agents ebook puts it:
“AI agents don’t just assist; they act… They can work independently, coordinate with other agents, and hand off to humans when needed. They’re not just completing tasks—they’re contributing to outcomes.”
This is a work model shift. Not just faster workflows, but workflows designed around collaboration between humans and AI.
Composable Systems: The Backbone of Agentic Retail
For this collaboration to thrive, composability is critical. Agents require systems that are modular, API-driven, and event-based—not monoliths.
The Fluent Order Management Architecture, for example, offers a headless, cloud-native OMS that exposes real-time data via open APIs. Its modular services allow teams to inject logic, augment workflows, and evolve over time, making it an ideal foundation for AI agent frameworks. Fluent’s Big Inventory service also supports the real-time visibility agents need to take action confidently across channels, from digital storefronts to physical stores.
Without this infrastructure, AI agents are brittle, trapped behind walls of integration debt. With it, they become operational teammates.
Humans + Agents: Working Together by Design
The future of work isn’t fully automated; it’s hybrid. Agents handle the grunt work: data pulls, system monitoring, recommendations. Humans make judgment calls, refine insights, and set direction.
But collaboration only works when roles are clear:
- Agents draft, humans refine
- Agents monitor, humans decide
- Agents route, humans prioritize
When those boundaries are intentionally designed, trust grows. And with trust, delegation scales. This is how agent frameworks move from pilot to production.
Use Case: Merchandising Agents in Action
Let’s make it real. Picture this:
An agent monitors sales velocity on a set of SKUs. It notices strong traffic but low conversion. It correlates the issue to a mismatched discount window and proposes a price adjustment. It models the revenue impact based on historical promo performance and sends a morning brief to the merchandising team.
All of this is possible because the agent has access to real-time inventory and order data, provided by Fluent OMS’s capabilities. The human team doesn’t need to start from scratch. They start from insight.
That’s not automation. That’s orchestration between agents and experts.
Where to Begin: From Sticky Notes to Strategy
You don’t need a massive AI strategy to get started. You need to start where the friction is.
As Jennifer Wright, Sr. Director of Strategic Delivery at Orium, writes in a recent article:
“When every team member sees the same workflow end‑to‑end, the places where agentic experience can have an outsized impact become obvious.”
That’s the power of EventStorming, a workshop method Orium uses to surface real-world pain points by mapping business processes as domain events. Teams naturally identify delays, manual workarounds, and high-friction steps that are perfect candidates for agent-led pilots.
The outcome? A shortlist of agent-ready use cases with clear metrics, aligned stakeholders, and shared context. That’s how agent frameworks go from concept to backlog to production.
The OMS as Agentic Platform
Most retailers still think of the OMS as a system of record. But composable OMS platforms like Fluent are evolving into agentic platforms— decision engines that sit at the center of execution.
And as agent frameworks like CrewAI and LangChain mature, it becomes easier to coordinate memory, actions, and reasoning across composable systems. The OMS becomes the connective tissue between signals and action.
Brands that embrace the humans-agent collaboration model won’t just operate more efficiently. They’ll adapt in real time, with systems that evolve as fast as their strategy.
Take the Next Step (Without the Overhaul)
You don’t need to replatform to work with agents. You don’t need a year-long roadmap. To start, you just need to:
- Identify a high-friction, repeatable task.
- Pilot a lightweight agent with clear KPIs and human-in-the-loop governance.
- Let the system learn. Let your teams lead.
- Scale what works.
In the end, the future of retail won’t be won by brands that plug in the most AI. It’ll be won by the ones that structure how humans and agents work together. Because composable systems unlock AI, but it’s humans + agents that unlock performance.
To lean more about how Fluent Order Management is enabling AI Agent integration, contact us today.
