How AI Is Delivering Real Gains To B2B Commerce Today
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B2B commerce is finally seeing real AI value as companies embed intelligence into pricing, catalogs, and approvals instead of chasing hype.gettyEvery year, companies lose staggering amounts of money to breakdowns in the B2B buying journey. Experts estimate that B2B organizations forfeit hundreds of billions of revenue each year — a figure that reflects how often orders collapse because buyers cannot find the information they need, navigate complex approval flows, or complete digital purchases. These losses happen in a market that already dwarfs consumer retail.Analysts say the global B2B ecommerce, the network of companies buying from companies, is already estimated at over $32 trillion in 2025, with some forecasts pushing it to $36 trillion by 2026 — a scale that makes every delay and every mismatch matter.Inside this world, the smallest inefficiencies multiply quickly. Large manufacturers and distributors often manage catalogs that contain thousands of items, each represented by stock-keeping units that track details like size, variant and technical specification. When these records are inconsistent or outdated, buyers run into dead ends. Search results fail to surface the right matches, core information is missing and orders stall because teams cannot confirm prices or product details. These problems may seem small, but at an enterprise scale, they become structural issues that drain time and revenue.The result is the tension many companies face today: They know AI can help with discovery, forecasting and workflow support, but getting AI to perform optimally has been another story entirely. Over the past year, however, companies have been trying to address this problem by embedding AI directly into the platforms that manage pricing, catalogs orders and approvals rather than treating it as a standalone tool. Used in this practical way, AI seems to finally be delivering real gains in the everyday work of B2B commerce.Why Practical AI Matters NowAt the beginning of the AI revolution, buoyed by the emergence of ChatGPT three years ago, many companies bought the shiniest new AI tool on the market without much analysis. But more and more, organizations are moving away from the idea that AI must be revolutionary to be useful. Instead, they now understand that they need a type of intelligence that enhances their existing procurement processes.MORE FOR YOUThis is why practical AI — which focuses on the tasks that consume the most effort — is getting into the spotlight now. Practical AI organizes product data, helps teams navigate catalogs that contain thousands of similar items and improves search accuracy by recognizing patterns across historical orders.According to Yoav Kutner, CEO of OroCommerce, “the companies seeing results are the ones grounding their AI strategy in real problems. They want systems that help buyers and operators move faster without adding new layers of complexity.”That’s a claim backed by Forrester’s 2025 commerce forecast, which noted that firms investing in practical AI saw the earliest and most reliable returns because they focused on tasks tied to revenue and operational efficiency. In other words, practical intelligence could become the next competitive advantage in B2B commerce.Where AI Delivers Real GainsSome of the clearest gains of using AI in B2B commerce appear in product data enrichment. Many enterprise catalogs contain thousands of items with inconsistent descriptions, mismatched naming conventions and gaps that confuse buyers. A 2025 McKinsey analysis found that companies using AI to standardize and enrich catalog information saw meaningful improvements in search accuracy and customer satisfaction. When buyers can trust the information in front of them, they complete orders more quickly.AI is also improving the overall search experience. Intelligent search tools analyze wording patterns, historical purchases and product relationships to guide buyers toward the right items. This makes a difference in sectors where items differ only by technical detail or regulated specification. Instead of relying on guesswork buyers receive clearer pathways to what they need.There are gains on the supplier side as well.
As Jary Carter, CRO and cofounder of OroCommerce, told me, “teams want AI that lightens the workload. When systems reduce repetitive tasks like simplifying order processing the impact becomes visible right away.”Gartner reports that as AI tools mature, many procurement organizations stand to improve productivity and reduce operational costs, especially when intelligence is embedded directly into the systems that support daily purchasing decisions.Behind The ScenesAI cannot deliver these improvements without a strong foundation. Many enterprises rely on older software systems that store customer data, pricing structures, approval rules and order histories. These are often called enterprise resource planning systems, the central platforms that coordinate the flow of information inside a business. When data is spread across several systems, AI struggles to interpret it accurately.This is why platform flexibility has also become essential. Companies like OroCommerce, Commercetools and Elastic Path are investing in architectures that let enterprises tailor AI features to their pricing models, contract terms and approval chains. These systems give AI a reliable structure to work with, making it easier for companies to control how intelligence flows across departments.As Carter further noted, “AI needs a clear path through the business. Clean information and adaptable workflows give it the structure needed to make accurate decisions.”A New Path ForwardB2B commerce is now entering a phase where the most valuable improvements come from strengthening what already works: Better catalogs, faster search, clearer approvals and more accurate decision support. These changes ripple outward into margins and customer experience and create organizations that can move more confidently through volatile markets.As digital procurement continues to expand, those stakes will only grow. Companies that invest in practical intelligence will gain speed and resilience without adding unnecessary complexity. Contrarily, those that continue relying on manual or disconnected systems will likely face rising costs and slower buying cycles. “The future will not be defined by the boldest AI experiments. It will be shaped by organizations that understand where AI can quietly solve the problems that have plagued procurement teams for years. When companies place intelligence in the right environment, it allows difficult processes to become simpler,” Kutner said.