The companies expected to dominate the AI era are often portrayed as technology pioneers armed with sophisticated algorithms, autonomous agents and vast AI budgets, Justin Thomas VP Sales EMEA North at Akeneo challenges this assumption.

The organisations most likely to thrive in AI-driven commerce are unlikely to be the most exciting. Instead, they will be the companies with disciplined product governance, consistent processes, reliable data standards and a relentless focus on operational execution. In other words, they may well be the most boring companies in the room.

That might sound like an odd conclusion at a time when every retailer and manufacturer is racing to deploy generative AI. Yet as commerce moves beyond search engines towards AI assistants and autonomous buying agents, competitive advantage is shifting away from the algorithms themselves and towards the quality of the information those algorithms consume.

AI is rapidly becoming commoditised, but trusted commercial data is not. Traditional ecommerce was built around customers searching websites, filtering products and comparing options, while brands controlled much of that journey through merchandising, search optimisation and carefully designed digital experiences.

Increasingly, consumers ask AI systems for recommendations instead of browsing category pages. Tomorrow, AI agents will go further, comparing products, negotiating prices and completing purchases on a customer's behalf. The website is therefore no longer the primary decision point because the decision is increasingly happening inside the AI itself.

That fundamentally changes what organisations need to optimise. Visibility is no longer determined by search rankings or advertising spend but by whether AI can confidently understand, compare and recommend products. In AI commerce, product data becomes the product.

The next challenge is to build a single, integrated decision layer because AI does not think in silos. When an AI agent recommends a product, it evaluates description, price, availability, profitability and context simultaneously as part of a single commercial decision.

Product information is therefore no longer simply supporting commerce but becoming the decision layer that connects pricing, merchandising, marketing, sales, inventory and profitability.

This is why the relationship between product information and pricing is becoming increasingly important. Pricing has traditionally been treated as a downstream activity, yet prices only make sense alongside product attributes, competitive positioning, customer demand, assortment strategy and commercial objectives. By bringing structured product information and pricing together, organisations can respond more quickly to changing market conditions while making decisions based on complete commercial context rather than isolated datasets.

The question is therefore no longer simply, "What should this product cost?" Increasingly, organisations need to ask, "How should this product compete?" Better data should produce better commercial outcomes, but much of the conversation surrounding AI focuses on automation when the greater opportunity lies in better commercial decision-making.

Well-governed product data delivers far more than catalogue completeness. It enables organisations to understand which products generate the strongest margins, which attributes influence conversion, which products achieve the greatest AI visibility, where promotional investment will deliver the highest return, which ranges should be expanded or retired and which pricing strategies maximise profitability.

As AI analyses performance across entire product portfolios, organisations will create continuous feedback loops in which customer behaviour, market conditions and commercial performance continually improve the catalogue itself. Instead of maintaining static product records, businesses will manage responsive catalogues that evolve through richer content, stronger product attributes, more accurate categorisation, competitive pricing and sharper market positioning.

The economics of visibility

AI commerce introduces a very different economic model. Products increasingly compete for inclusion within AI-generated recommendations rather than website rankings, fundamentally changing the economics of visibility.

Incomplete attributes, inconsistent product information or conflicting pricing no longer simply reduce conversion after customers arrive on a website. They reduce the likelihood that customers will ever see the product because AI cannot recommend it with confidence.

Visibility therefore becomes a commercial asset. Generative Engine Optimisation (GEO) helps organisations understand how frequently their products appear in AI-generated responses, but measurement alone creates little value. Knowing that products are invisible matters only if organisations can continuously improve the product information that determines visibility.

This is where governance becomes commercially important. The organisations that consistently appear in AI recommendations will not necessarily have the most sophisticated optimisation dashboards. They will be those with the strongest operational discipline for enriching, governing and distributing trusted product information across every channel from which AI gathers signals.

Agentic commerce will reward operational sophistication. As AI agents begin negotiating and purchasing products autonomously, they will compare structured specifications, verify trust signals, evaluate pricing, assess compatibility, understand policies and calculate overall value before making recommendations.

That level of automation rewards consistency rather than creativity. It favours organisations with governed product data, standardised taxonomies, validated pricing models and clearly defined commercial rules because those businesses make it easier for AI to reach confident decisions. Boring perhaps, but the companies that have invested in governance, product quality, process standardisation and cross-functional collaboration over the past decade may discover they have unintentionally built the ideal platform for AI commerce.

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