5 Practical Steps to Move Beyond AI Hype in Commerce

Everywhere you turn in the commerce world, everyone is talking about AI. But moving from endless strategy discussions to actually using autonomous, agentic AI in everyday production can feel overwhelming. How do you bridge the gap between grand theory and practical reality?

To help break down the operational roadmap into manageable steps, we have outlined five key strategies to help your organization prepare for the future of commerce.

Five Key Strategies for the Future of Commerce

1. Clean Up Your Data (It’s Still King)

The classic rule of tech, "garbage in, garbage out," is just as true for advanced AI. AI agents don't browse websites like human buyers; they parse raw data. If your catalog, inventory, or pricing data is messy, outdated, or incomplete, the AI will deliver wrong answers to your customers. Ensuring your data is structured, machine-readable and updated in near real-time (ideally every 15 minutes) is your foundational step.

2. Adopt an API-First Approach

For AI agents to seamlessly interact with your commerce environment, they need smooth paths to fetch real-time information, especially in B2B where negotiated pricing and contract terms sit behind firewalls. Embracing an API-First Commerce approach with open API standards (like Swagger/OpenAPI) or GraphQL makes your endpoints easily discoverable and understandable for AI. Additionally, prioritizing fast API response times ensures users or agents aren't left staring at spinning waiting indicators.

3. Define Strong Guardrails and Governance

Before letting AI agents interact across your ecosystem, set firm rules for agentic ai governance. Guardrails protect your business from common risks like prompt injection attacks, accidental leaking of private customer data (PII), or inaccurate pricing responses. Establishing compliance oversight, prompt observability, and rate limits keeps AI interactions safe, secure and under control.

4. Start Small with Focused Pilots

Instead of attempting a massive, multi-year solution overhaul, pick one simple, high-impact use case. Focus on everyday pain points that absorb huge amounts of internal team time, such as automated B2B reordering, subscription management, or basic help desk queries. Testing and proving success in a targeted environment builds a solid foundation to scale into full production later.

5. Assemble a Cross-Functional Team Day One

Implementing AI isn't purely an IT or engineering project. Because agentic AI touches everything from front-end customer experience to back-end compliance, you need alignment across departments from the start. Bring together leaders from CX, legal, risk management, data engineering and business operations early on to ensure everyone’s requirements are met.

Ready to explore further? This article offers just a glimpse of the topics covered throughout our AI in Commerce webinar series. Check out the complete episodes to gain deeper insights on agentic AI, modern composable architecture, and the evolving landscape of B2B digital buying. Watch the full series here.