Key Considerations for Implementing AI Agents in Retail

Agentic artificial intelligence (AI) is revolutionizing the retail sector, offering unprecedented capabilities in automation and decision-making. Unlike traditional AI tools, AI agents are highly autonomous, capable of handling complex tasks that require reasoning and adaptability. This shift was a major theme at the NRF Big Show 2025, where retailers and vendors showcased innovative applications.

What Are AI Agents?

AI agents function like virtual team members, managing tasks such as order fulfillment, customer service, and personalized shopping experiences. They excel in dynamic scenarios where predefined workflows fail, such as:

• Order fulfillment exceptions: Deciding how to handle delayed shipments or split orders.
• Customer support escalations: Adapting resolutions based on real-time feedback.

Best Practices for Deployment

1. Start with employee-facing use cases: Internal applications, like assisting call center staff, allow brands to refine AI strategies before customer-facing rollouts.
2. Treat AI agents like new hires: Train, monitor, and iterate to improve performance over time.
3. Balance autonomy and control: Ensure AI agents can operate independently while maintaining oversight mechanisms.

Deterministic Workflows vs. AI Agents

• Deterministic workflows are cost-effective for repetitive tasks (e.g., order confirmations).
• AI agents shine in complex, ambiguous scenarios where adaptability is critical.

Evaluation Questions

When assessing AI agent solutions, retailers should ask:

1. How trustworthy are the outputs?
2. Is the system adaptive and proactive?
3. Can it achieve complex goals autonomously?

Nicola Kinsella, Chief Strategy Officer at Fluent Commerce, emphasizes the importance of preparation: "Your next hire might not be human. Are you ready?"

Agentic AI represents a transformative opportunity for retail, but success hinges on strategic implementation and continuous refinement.