A New Kind of Buyer Has Arrived
The summer of 2025 marked a turning point in AI: organizations are racing not just to experiment with AI, but to deploy autonomous AI agents at scale. Deloitte predicts that 25% of enterprises using generative AI will launch AI agents in 2025, climbing to 50% by 2027.
Just a few years ago, while teaching a design course at the University of Houston, I told my students to prepare for a future where artificial intelligence would be their workplace peer or their client. That future is arriving faster than any of us expected. For those students, the upside is that they still have room to experiment, make mistakes, and grow into that reality. In B2B organizations, however, there is far less slack in the system: AI agents are already showing up as buyers, not just tools, and business will not pause to let teams catch up.
The brands that will actually win in this new economy aren’t just “AI‑ready.” They must transform into agent‑preferred brands: organizations that make it easy for AI agents to discover them, understand their value, and justify choosing them on behalf of human buyers. Ultimately, if your brand is not in order, you’re not open for business for AI agents. For B2B marketers, UX leaders, and product teams, the window to adapt is closing quickly.
What Is an AI Buyer Agent?
An AI buyer agent is an intelligent software agent that acts like a virtual purchasing assistant for a person or organization. It can research options, compare suppliers, negotiate within defined rules, and even place orders autonomously. Traditional AI chatbots (like Claude, Gemini, Perplexity, or ChatGPT) take an input, process it through a large language model, and return a single response. Agentic AI, by contrast, follows a ReAct (“reasoning and acting”) framework: humans set a goal, and the agent plans, acts, observes results, and iterates on its own.
Capable of acting autonomously to achieve defined goals in milliseconds, these digital proxies are no longer just tools; they are a critical new “user” in your buying process. They require a machine-first experience that supports and accelerates their buyer’s journey, from discovery to decision. Traditional marketing tactics are largely irrelevant to this audience, but business leaders would be remiss not to provide agents with the structured, factual information they need to make informed decisions. And first impressions and service quality still matter; AI agents can recall past interactions and behaviors to inform future actions, which means your brand has to “show up” for the robots too.
AI Buyer Agents in the Wild
The AI agent economy isn’t theoretical; it’s here, and they are already shifting procurement and B2B purchasing patterns. Current examples include:
- Intelligent supplier discovery and qualification
- Converting plain-language needs into detailed sourcing profiles.
- Shortlisting suppliers based on capabilities, compliance, performance, and risk.
- Autonomous sourcing and purchasing
- Automatically issuing RFQs, evaluating bids, and awarding business for standard services or commodities.
- Handling routine negotiations within configured parameters.
- Supplier risk and compliance monitoring
- Continuously scanning supplier data for risk signals.
- Proactively recommending alternative suppliers or corrective actions.
- Dynamic spend analysis and optimization
- Continuously analyzing spend to detect maverick purchasing, consolidation opportunities, and cost savings.
- Surfacing real-time, actionable recommendations to procurement and finance teams.
Compressed evaluation cycles mean agents no longer “browse” brands the way humans do; they shortlist and decide in seconds based on whatever structured data they can reliably parse. In that environment, even small inconsistencies across product specs, pricing, compliance claims, or performance metrics become disqualifying signals instead of minor imperfections. Brands that want to remain in the consideration set must assume near‑zero tolerance for gaps or contradictions in their data.
Retailers, banks, and manufacturers are already piloting AI agents that orchestrate analysis, purchasing, consolidate supplier data, and compress purchase-order and payment cycles. A few current examples include:
- Amazon Rufus: Handles complex supplier research, spec comparisons, and bulk reorders autonomously across Amazon Business.
- JPMorgan COiN: Scans supplier risk, compliance, and contracts to approve deals in seconds, saving hundreds of thousands of manual hours.
- Salesforce Einstein SDRs: Qualify vendors, issue RFQs, and optimize spend by analyzing CRM signals and procurement patterns.
In our next article, we’ll touch on the key difference between human and AI agents and what business leaders need to take into consideration as they prepare their organizations to become an agent-preferred brand.
Further reading:
Are You Agent Ready?
In our whitepaper, you'll find a practical checklist and clear framework to help your brand stay visible and selectable as AI buyer agents become a bigger part of B2B purchasing.
