To sell to AI agents, make your product data, pricing, and proof machine-readable, and earn accurate mentions in the sources large language models trust. In agentic commerce, autonomous agents research vendors, build shortlists, and increasingly transact on a buyer's behalf, so visibility to the agent now decides whether you ever reach the human behind it.
The shift is moving faster than most pipeline plans assume. Gartner projects that by 2028, 90 percent of B2B buying will be AI-agent intermediated, routing more than 15 trillion dollars in spend through agent-driven exchanges (Gartner). Preparing for that buyer is a growth priority now.
Agentic commerce is moving from demos into real B2B buying
Agentic commerce has crossed from novelty into procurement reality. Forrester's 2026 predictions report that 61 percent of purchase influencers say their organization has adopted or will adopt a private generative AI engine to support purchasing decisions (Forrester). Buyers are wiring AI into vendor evaluation itself.
That changes where a deal is won or lost. A buyer's AI engine reads your public material, compares you to alternatives, and forms a position before a human joins the conversation. Getting represented accurately at that stage is the same discipline behind answer engine optimization, and it sits at the front of any modern account-based experience program.
AI agents choose vendors from machine-readable proof
Agents choose from what they can parse and trust, so structured, accessible information wins. Salesforce's State of Sales research found that 87 percent of sales organizations now use some form of AI, and 54 percent of sellers have already used agents, with nearly nine in ten planning to by 2027 (Salesforce). The same automation is arriving on the buying side of the table.
For sellers, the practical work is unglamorous and specific. Publish clear specifications, transparent pricing signals, and comparison-ready facts an agent can lift without guessing, then keep them consistent everywhere they appear. This is where technical readiness meets go-to-market, and it connects directly to building a website AI agents can actually read.
Selling to AI agents means answering with agents of your own
The buy side and the sell side are both automating, and the gap is closing quickly. Forrester predicts that in 2026 at least one in five B2B sellers will be compelled to respond to AI-powered buyer agents with dynamically delivered counteroffers through their own seller-controlled agents (Forrester). Negotiation is starting to happen machine to machine.
Preparing for that does not mean handing strategy to software. It means giving your systems the clean inputs and clear rules to represent your offer when an agent comes knocking, and orchestrating the human follow-up at the right moment, which is the core idea behind our Next Best Action work.
The automation wave is reshaping how go-to-market spend flows
AI is not only mediating buying; it is reshaping the channels you use to reach buyers. Gartner predicts that by 2028, more than 70 percent of global ad spend and 80 percent of United States ad spend will flow through self-serve advertising platforms where AI materially influences media buying, cost, and outcomes (Gartner). The systems deciding what buyers see are increasingly algorithmic.
The takeaway for growth leaders is to treat AI visibility as a first-class channel with its own budget and owner. Winning it looks a lot like winning the AI-assisted human committee we covered in how AI is rewiring the B2B buying committee, extended to the agents now acting on that committee's behalf.
Humans still close the deal, even when an AI agent opens it
Agents accelerate discovery, and people still carry the decision. Gartner predicts that by 2030, 75 percent of B2B buyers will prefer sales experiences that prioritize human interaction over AI for the choices that carry real risk (Gartner). The agent narrows the field; a person validates the finalist and signs.
So the seller's job splits into two tracks that have to work together. Be discoverable and correct for the agents that build the shortlist, and be genuinely helpful for the humans who confirm it. Aligning those tracks is a coordination problem we help teams solve inside AI-powered ABM programs.
Winning the AI agent shortlist is an account-based discipline
Selling to AI agents rewards teams that prepare the whole buying environment. With Gartner projecting 90 percent of B2B buying to be agent-intermediated and more than 15 trillion dollars flowing through agent exchanges by 2028 (Gartner), the cost of being invisible to agents compounds every quarter you wait.
Two moves matter most right now. Make your data and proof machine-readable so an agent can represent you accurately, and make sure the sources those agents trust describe you correctly. If you want a second set of eyes on how your pipeline handles AI-agent buyers, our team can map it with you.
