B2B buying is moving toward AI-mediated purchasing, which means AI agents can directly participate in the buying process. According to Gartner, by 2028, 90% of B2B buying will be AI-agent intermediated, pushing over $15 trillion of B2B spend through AI agent exchanges.
This changes how B2B companies need to sell. AI agents could discover suppliers, evaluate products, compare prices, check availability, and initiate purchases on behalf of buyers.
For sales teams, the question is how to make your products, pricing, availability, and policies visible and usable by the AI agents making buying decisions. This could make AI agents a new B2B sales channel, and businesses need to prepare for it.
Why are AI agents becoming a sales channel?
- AI agents can bypass the traditional B2B sales funnel. They can research suppliers, compare products, and shortlist vendors before a buyer visits a website or contacts a salesperson. Businesses therefore need to make their product, pricing, and supplier information accessible to AI agents.
- Machine-readable data is becoming critical. AI agents need structured and reliable information about product specifications, pricing, availability, certifications, compatibility, and policies to evaluate suppliers. Product data, APIs, and system connectivity are therefore becoming part of the sales infrastructure.
- AI agents can also move from discovery to purchase. With the right permissions and integrations, they can compare options, check availability, verify requirements, and initiate purchases or reorders. This creates a new path from discovery to evaluation to transaction that B2B businesses need to support.
How can AI agents support Sales?
AI agents can support B2B sales at different levels of autonomy, helping sellers make better decisions to handle defined sales activities more independently.
- Augmented selling: AI helps sales teams make better decisions. It can analyze account and customer data, recommend next-best actions, generate talking points, and personalize sales content. It can also automate follow-up sequences across email and chat. For example, AI identifies that an existing customer may need additional products and recommends the right products and next steps to the salesperson.
- Assisted selling: AI works alongside the salesperson during active sales interactions. It can analyze calls, surface relevant information, suggest responses, draft follow-ups, and update CRM or ERP records. For example, during a customer call, an AI agent retrieves previous orders and product information, suggests relevant products, and prepares a follow-up email while the salesperson focuses on conversation.
- Autonomous selling: AI handles defined sales activities with limited human intervention. It qualifies inbound leads, prioritizes opportunities, answers product questions, nurtures prospects, recommends products, and initiates sales workflows across digital channels. For example, An AI agent receives a product inquiry, qualifies the buyer, checks product availability and pricing, recommends suitable products.
How to Prepare Your Business?
- Make product and pricing data machine-readable. Structure product specifications, pricing, availability, compatibility, policies, and other key information so AI agents can retrieve and understand it through APIs and other machine-accessible interfaces.
- Optimize your digital presence for AI discovery. Make product and company information clear, consistent, structured, and easy for AI systems to interpret. This extends beyond traditional SEO to ensuring AI can accurately understand what you sell, who it serves, and how your products compare.
- Enable secure agent-led transactions. Give controlled access to AI agents for actions such as checking inventory, generating quotes, placing orders, or initiating reorders. Define permissions, approval requirements, payment controls, and audit trails before allowing autonomous transactions.
Conclusion
AI agents can change B2B sales by becoming an active part of the buying process. Instead of waiting for buyers to find a website, fill out a form, and speak with a salesperson, businesses will need to ensure their products are visible, relevant, and easy for AI agents to evaluate. This will make product data, pricing, availability, integrations, and transaction capabilities part of the sales strategy. At Ignitiv, we help B2B businesses prepare for this shift by making their commerce ecosystem ready for machine-led buying, from product and pricing data to connected commerce and transaction workflows.
FAQs
AI agents can search for supplier and product data, compare specifications, pricing, availability, delivery terms, and policies. They use this information to shortlist suppliers that meet the buyer’s requirements.
Agents need structured data such as product specifications, attributes, pricing, inventory, lead times, and minimum order quantities. The data must be accurate, current, and accessible through machine-readable formats or APIs.
Businesses should structure product and company information clearly and make it accessible through APIs and other machine-readable interfaces. Consistent product data, clear specifications, pricing, availability, and policies help agents understand and evaluate their offerings.
With the right integrations and permissions, agents can check availability, compare options, generate quotes, place orders, and initiate repeat purchases. Businesses should define approval rules, transaction limits, and audit controls for agent-led transactions.
Start by making product, pricing, inventory, and supplier data machine-readable. Connect commerce, CRM, ERP, PIM, and OMS systems through reliable APIs. Then enable agents to perform low-risk purchasing tasks with defined permissions and human approval for higher-risk actions.
