The Next Era of Commerce Platforms

Many organizations approach artificial intelligence as a new layer of technology to add to their existing stack. However, AI doesn't create value simply because it exists. Its impact depends on the strength of the operational foundation beneath it. Businesses see the strongest results when AI helps reduce the time between insight and action. Connected systems, unified data, and integrated workflows allow merchants to move with greater speed and confidence. In retail, that speed becomes a competitive advantage.

Commerce platforms are evolving through three distinct stages. They began as systems of record, capturing transactions and managing operations. Today, they're becoming systems of intelligence, helping merchants understand what's happening across their business. The next evolution is systems of action: platforms that help merchants decide what comes next and increasingly automate routine operational tasks on their behalf.

The next chapter of AI in commerce will be defined by which businesses can turn intelligence into outcomes faster. But before AI can improve decision-making, businesses need something more fundamental: trusted business context. That starts with connected systems, unified data, and a technology foundation built for real-time operations.

Better Decisions Begin With Better Foundations

AI is only as useful as the foundation beneath it. In retail, that foundation is often fragmented, inconsistent, and underused. Retailers may be sitting on enormous volumes of information, from transactions and inventory levels to customer preferences and purchase behavior, but too often that data lives across disconnected systems.

E-commerce platforms, point-of-sale systems, payments providers, and third-party applications each hold part of the picture. Without a unified view of that data, any intelligence built on top of it is incomplete and difficult to trust.

That is where many AI initiatives begin to lose momentum. Businesses layer AI onto already complicated technology stacks without first addressing the underlying fragmentation.

The result is familiar: more dashboards, more reporting, and more surface-level insights, but not more clarity, and certainly not faster decision-making.

Intelligence Belongs in the Workflow

The most meaningful use of AI in commerce happens inside the everyday workflows merchants already rely on. The opportunity is not to create another standalone tool. It's to make core business systems more intuitive, responsive, and useful at the moment decisions need to be made.

That shift is already becoming visible across commerce. In retail, AI is helping operators understand product performance and customer behavior faster. In wholesale, it's helping buyers navigate assortment complexity with greater speed and confidence.

Most businesses don't need more data. They need a faster, clearer way to interpret the data they already have and act on it with confidence. That's why conversational interfaces and embedded intelligence matter. Instead of forcing operators to pull reports, jump between dashboards, or rely on analyst support, they allow businesses to ask straightforward questions and get useful answers within the systems they already use.

Unlike large enterprises, most merchants don't have dedicated analyst teams or specialized AI resources. Their success depends on making effective decisions while managing the day-to-day realities of running a business. For them, the value of AI is not novelty. It's simplification.

Modern commerce platforms create lasting value when intelligence is embedded directly into everyday workflows.

From Intelligence to Action

The next evolution of AI in commerce is not simply about generating better insights. It's about helping merchants execute with greater confidence. For years, retail technology focused on digitizing transactions. More recently, it focused on delivering visibility through dashboards and analytics. The next generation of platforms will be defined by something different: their ability to help businesses make better decisions and take meaningful action in real time.

Every day, merchants make hundreds of operational decisions, including what to reorder, how to price inventory, which products to promote, where to invest marketing dollars, and how to allocate staff. Most of those decisions still require operators to assemble information from multiple systems before deciding what to do next. Rather than asking merchants to interpret reports or search across disconnected applications, intelligent commerce platforms should surface recommendations in context, explain why they matter, and increasingly automate routine operational tasks where appropriate.

As AI becomes more deeply embedded into commerce platforms, technology will spend less time helping businesses understand what happened and more time helping them determine what should happen next.

Bhawna Singh is chief technology officer at Lightspeed Commerce, the unified omnichannel platform.