A buyer looking for a new supplier can already begin the selection process without manually reviewing dozens of websites, catalogs, and technical data sheets. Part of that work can be delegated to an Artificial Intelligence agent that identifies companies matching specific requirements, compares their offerings, checks available information, and produces a shortlist. In more standardized workflows, the same agent can also support purchasing and reordering.
This is no longer just a theoretical scenario. In research published on August 25, 2026, Gartner reports that a growing number of B2B procurement teams are adopting AI buying agents at key stages of purchasing and replenishment. At the same time, enterprise platforms such as Oracle and SAP are introducing AI capabilities to identify suppliers, check qualifications and compliance, support purchasing decisions, and recommend options that meet company policies and contract requirements.
For food manufacturers, this raises a very practical question: how easy is it for an automated system to understand exactly what the company produces, including product characteristics, certifications, and supply terms?
What an AI agent can do in the purchasing process
AI agents used in procurement go beyond a simple chatbot search. They can be given an objective, access information available in corporate systems, and carry out a sequence of tasks according to predefined criteria and rules.
Oracle, for example, has introduced capabilities that allow procurement professionals to search for suppliers using natural-language requests. The system can draw on supplier profiles, product and service categories, previous transactions, business classifications, and other data available on the platform to identify relevant candidates.
Another Oracle application uses AI agents to support supplier qualification by identifying missing certifications or requirements, flagging qualification issues, and helping determine where action is needed. SAP is moving in a similar direction, integrating agents into procurement systems to support decisions, enforce company policies, and recommend options aligned with existing contracts.
Human buyers remain central to strategic decisions, complex negotiations, new product development, and relationship management. But the initial screening process can increasingly take place before a supplier ever speaks to a person.
Suppliers increasingly need to be machine-readable
An experienced buyer can interpret incomplete information. They may recognize that two different descriptions refer to essentially the same ingredient, call to ask about minimum order quantities, or contact a sales representative to confirm whether a certification is still valid.
Automated processes work best when this information is explicit, structured, and up to date. If an essential data point exists only in a PDF, in a sales representative's inbox, or in the personal knowledge of an account manager, it may be much harder for an automated system to use it during supplier selection.
Being "machine-readable" does not mean making all company information publicly available. It means organizing data so that authorized systems can access and use it through digital catalogs, company websites, supplier portals, procurement platforms, PIM, ERP, EDI, APIs, or other data exchange tools.
For a food manufacturer, this information may include:
- company and facility identification, production categories, and markets served;
- product data, including GTIN, product name, format, weight, ingredients, allergens, and product characteristics;
- certifications and qualifications, including their current validity;
- shelf life, storage conditions, and temperature requirements;
- logistics configurations, including units per case, cases per pallet, dimensions, and weights;
- MOQ, or minimum order quantity, lead time, and availability;
- where relevant, origin, traceability, and information required for compliance in different markets.
Data completeness and consistency are becoming commercial factors
The issue is not only how much information is available, but whether it is consistent. If a company's website lists one certification, its catalog shows another, and its profile on a customer's platform has not been updated, an automated process may trigger requests for clarification or fail to recognize the supplier as meeting the required criteria.
Applications already on the market show how practical this issue can become. Oracle's latest capabilities can search for suppliers using the product and service categories included in their profiles and use qualification data to support supplier selection. Other applications can identify missing or non-compliant qualifications.
Keeping supplier profiles current on the portals and platforms used by key customers should therefore no longer be viewed as purely administrative work. It can become part of a company's commercial visibility.
Certifications and claims need to be verifiable
This is particularly important in the food industry because many supplier selection criteria involve requirements that can be objectively verified. An importer may be looking for a manufacturer certified to a particular standard, an organic product, a specific origin, defined nutritional characteristics, or a product that meets particular market requirements.
In these cases, a promotional statement on a website is not necessarily equivalent to information that can be used in a qualification process. What matters is the exact name of the certification, the issuing body, the facility covered, its scope, validity date, and supporting documentation.
The same applies to product claims. As procurement becomes more automated, it becomes increasingly useful to separate marketing language from technical information that can be compared and verified.
Existing standards are becoming more valuable
There is no need to create a new language specifically for AI agents. The food industry already uses infrastructures and standards designed to identify products, companies, and logistics units and to exchange information between trading partners.
GS1, for example, enables products and supply chain participants to be uniquely identified through standards such as GTIN and GLN. Verified by GS1 can be used to verify information associated with product identifiers, companies, and locations, while GS1 Digital Link connects GS1 identifiers with information and services available online.
In August 2026, GS1 also updated specifications related to Digital Link and its resolution system. These technologies were not developed specifically for AI purchasing agents, but they illustrate the growing importance of unique identifiers, structured data, and digitally accessible information sources, exactly the type of infrastructure that can also support automated procurement processes.
From static catalogs to up-to-date commercial data
Good product descriptions alone are not enough. Many purchasing decisions depend on information that changes over time.
An agent supporting a reorder may need to know availability, lead times, minimum order quantities, logistics conditions, or the current status of required qualifications. If this information is updated only occasionally in a PDF catalog, much of the benefit of automation is lost.
Especially in relationships with large distributors, retailers, and industrial customers, this may drive a gradual shift from exchanging documents toward more frequent and integrated data flows. EDI, APIs, supplier portals, and system-to-system connections can therefore also serve a commercial purpose by allowing customers to quickly determine whether a supplier can meet a specific requirement.
The sales team's role is changing too
When AI handles part of the initial research and comparison process, the sales function does not become less important. What changes is when sales professionals enter the process and the type of value they are expected to provide.
Standard information such as available formats, certifications, logistics capabilities, and technical specifications should ideally be accessible without requiring direct human involvement. Sales teams can then focus more on negotiation, custom product development, private label, commercial planning, exception management, and building customer relationships.
At the same time, marketing, sales, quality, IT, and supply chain become increasingly interdependent. If information that could help win a new customer is poorly managed within company systems, what appears to be a data issue can directly affect market access.
A data audit can be the first step
Assessing how ready a company is for this new model does not necessarily require a major technology investment. A practical first step is to select a few important SKUs and check whether an external party could reconstruct all the essential information about them without ambiguity.
The questions are straightforward: Is the product uniquely identified? Are specifications up to date? Can certifications be easily verified? Are MOQ, lead time, and logistics configurations available? Is the information consistent across the website, catalog, ERP, and customer portals? Is responsibility for updating each data point clearly assigned within the company?
The same exercise can be extended to company and facility information, separating data that can be public from information that should be shared only with qualified partners and data that must remain confidential.
Being easy to evaluate can become a competitive advantage
Agentic procurement can provide meaningful support in supplier selection without removing the human element. In the food industry, quality, safety, production capacity, innovation, reliability, and commercial relationships will continue to require human judgment, particularly for strategic supplies.
The biggest change may happen earlier in the process: when creating the list of suppliers to evaluate, checking minimum requirements, comparing alternatives, and managing more standardized reorders.
For food manufacturers, it will therefore become increasingly important to ensure that products, capabilities, and company credentials are accessible, comparable, and verifiable by the AI systems supporting the buyer. As procurement becomes more automated, reducing information friction can become a meaningful source of commercial competitiveness.
