Gartner released its top data and analytics trends for 2026 this week. The headline number is the kind that ends up in every boardroom deck: more than one in ten enterprises will be “AI-first” by 2030.
It’s an easy figure to nod along to. But the more useful part is buried in the trends themselves. So let’s look past the headline.
Six trends, one common thread
Gartner’s list reads like a tour of this year’s buzzwords. Agentic data streaming. Agentic data management. Decision governance. GraphRAG. Strip away the labels, however, and they all converge on a single, unglamorous truth:
An AI agent is only as good as the data underneath it.
The agents getting all the attention sound impressive. Real-time quoting. Automated reordering. AI-driven product discovery. Dynamic personalization. Yet none of them run on magic. Instead, they run on clean product data, accurate inventory and pricing, and a catalog structured well enough that a machine can actually read it.
That foundation is where the real work lives. And it’s the part most merchants skip.
Gartner is clear on the sequencing
The numbers back up this order of operations. For example, Gartner forecasts that adoption of data streaming for agentic AI will climb from under 15% of organizations in 2025 to over 60% by 2028. In other words, teams are laying the plumbing before the agents arrive.
Furthermore, a separate study this year found that organizations with successful AI initiatives invest up to four times more in their data foundations than everyone else. The pattern stays consistent. First the foundation, then the agent.
This matches what we see at Atwix every day. We’ve worked inside Adobe Commerce, Shopware, BigCommerce, and Shopify catalogs for over a decade. And the agencies and merchants who win with automation almost always fix their data first. Our Sirius ERP connector exists for exactly this reason. It syncs price, stock, and product data between systems like Prophet 21, Infor, Kodaris, and Expertek and the storefront, so the catalog a machine reads actually reflects reality.
Three things to audit before any agentic project
Before you commit budget to an AI agent, pressure-test the groundwork first. We run this same check with B2B clients before any automation conversation starts.
- Source-of-truth alignment. Your ERP, your PIM, and your storefront need to agree on price and availability. If they don’t, automation won’t resolve the conflict. Rather, it will just ship the wrong answer faster.
- Catalog structure. Machine retrieval depends on clean attributes, consistent taxonomy, and complete product data. Without that structure, “AI search” returns noise instead of signal. This is also where most legacy Magento catalogs need the most work.
- Decision ownership. Someone has to govern how automated decisions actually get made. Otherwise, AI adds risk rather than efficiency. So assign that ownership before you ship, not after.
None of this is glamorous. Honestly, it’s data plumbing. Still, it’s the difference between an AI strategy and an AI slide.
The takeaway
The merchants positioned to benefit from agentic commerce in 2027 are the ones investing in their data foundation in 2026. Meanwhile, the trend reports will keep getting flashier. The work that makes them real won’t change.
At Atwix, we’ve spent years on the unglamorous layer. We clean catalogs, connect ERPs, and structure product data so it holds up under automation. Therefore, if your team is mapping where AI fits in your commerce stack, that conversation is worth having now. And it should start with the data, not the agent.