It’s bigger than GEO. Bigger than SEO. This is about being the #1 answer when 700 million people ask AI what to buy.
When we built SaaStr’s AI tools on Replit over the past year, I needed to make dozens of vendor decisions. Email delivery? The Replit agent recommended Resend. Authentication? Clerk. Voice and audio? ElevenLabs.
Are there better options out there? Maybe. I genuinely am not sure. What I do know is that I picked the vendors the agent told me to pick. Every single time. I didn’t run a bakeoff. I didn’t read G2 reviews. I didn’t ask for demos. The agent had an opinion, and I trusted it.
That’s the new buyer journey. And it’s already happening.
90% of B2B Purchases May Be Handled By AI Agents
Here’s what’s actually happening:
According to Responsive’s “Inside the Buyer’s Mind” report (October 2025, surveying 350+ B2B buyers worldwide), two-thirds of B2B buyers now rely on AI agents and chatbot as much as or more than Google when evaluating vendors. In tech and software specifically, that number jumps to 80%. One in four B2B buyers use GenAI more often than traditional search for vendor discovery.
And it’s not slowing down. Gartner projects that 90% of all B2B purchases will be handled by AI agents within three years—channeling more than $15 trillion in spending through automated exchanges.
That may be too soon. But it’s already started. And more and more of us will trust our #1 AI Agent when it comes to what products to pick. Think about it. You probably already do.
This Isn’t GEO. This Is Something Bigger.
Many have been talking about GEO—“Generative Engine Optimization”—for a while now. How to show up in AI-generated answers. How to structure content so LLMs cite you.
But that’s thinking about it wrong.
GEO is about showing up. What I’m talking about is about winning. Being the recommended answer by the AI agents your customers use. The default. The favorite.
When a VP of Engineering asks Claude to compare API management platforms, that AI isn’t browsing—it’s synthesizing, recommending, and shortlisting. Either your product is the one it recommends, or you’re invisible.
The Shopping Agents Are Already Here
ChatGPT launched Instant Checkout in late 2025. Over a million Shopify merchants—Glossier, SKIMS, Spanx, Vuori—can now sell products directly inside conversations. No redirect. No cart abandonment. Ask ChatGPT for running shoes under $100, get recommendations, buy in three taps.
Then Walmart joined. Their entire product catalog, inside ChatGPT.
Shopify announced what they’re calling “Agentic Storefronts”—a central hub to manage how products surface across ChatGPT, Microsoft Copilot, Google’s Gemini, and whatever comes next. They’re not betting on one AI. They’re building the infrastructure to be the #1 recommendation across all of them.
Google launched AI Mode in Search and the Gemini app with native shopping and embedded checkout. Microsoft’s Copilot has the same. And they all co-developed something called the Universal Commerce Protocol (UCP)—an open standard for AI agents to complete purchases across any commerce stack.
The infrastructure for agent-mediated commerce is being built right now. And it’s moving faster than anyone expected.
B2B Is Next
Here’s what most B2B companies are missing: this isn’t a consumer play that might someday reach enterprise. The B2B version is arguably more transformative.
When ChatGPT recommends a CRM, that recommendation reaches hundreds of millions of potential buyers. When Claude suggests an API management platform, that synthesis shapes shortlists across thousands of enterprises.
The companies building these agents understand this. Salesforce’s Agentforce, ServiceNow’s AI Agents, SAP’s Joule, Microsoft’s Agent 365—they’re all racing to build the autonomous systems that will handle procurement, vendor selection, and purchasing decisions.
Every major platform will have agents. And those agents will need to recommend software.
The question is: will they recommend yours?
Why Agents Play Favorites
Traditional search was built on links and keywords. You could game it. Buy your way to the top with enough AdWords spend. Stuff keywords until you ranked.
AI doesn’t work that way.
When I asked Claude about coding platforms, it synthesized actual signal: revenue trajectories, production validation, security concerns, platform lock-in risks. It didn’t regurgitate marketing copy. It formed an opinion based on what it learned about each product.
Agents form preferences the way informed humans do—through the weight of evidence across thousands of data points. User reviews. Community sentiment. Technical documentation. Support quality. Integration depth. Pricing transparency.
You can’t keyword-stuff your way into an AI’s good graces. You have to actually be worth recommending.
The Platforms That Will Win
This is where it gets interesting for B2B.
Right now, if you ask ChatGPT about CRMs, it has opinions. Ask Claude about project management tools, same thing. Ask Perplexity about marketing automation platforms, it will give you a ranked list with reasoning.
Those opinions were formed from training data. But the next wave of agents won’t just have static opinions—they’ll have access to real-time data, user feedback, and direct integrations with the platforms they recommend.
Imagine Salesforce’s Agentforce recommending best-of-breed tools that integrate deeply with their ecosystem. Or ServiceNow’s agents favoring platforms with native workflow connections. Or Shopify’s commerce agents preferentially surfacing merchants in their catalog.
The platforms building the agents will have enormous influence over what gets recommended.
What This Means For Your Startup
If you’re building B2B SaaS, this is your new marketing reality:
1. Reference rates matter more than click-through rates
The old metric was getting people to your site. The new metric is getting agents to recommend you. If AI systems can’t identify or understand your offering, you may never make a buyer’s shortlist.
2. Product quality is your marketing
You can’t optimize your way into AI recommendations. You have to earn them by building something actually worth recommending. When AI synthesizes signals from thousands of sources, mediocre products get exposed.
3. Data structure is critical
AI agents prefer content with clear hierarchical organization, extractable answer blocks, and verifiable claims. Your documentation, your pricing page, your feature descriptions—all of it needs to be structured for machine comprehension, not just human readability.
4. Platform integrations become distribution
Deep integrations with Salesforce, ServiceNow, Shopify, and other platforms building agents will increasingly determine discoverability. If their agents recommend tools that work seamlessly in their ecosystems, being a great native integration isn’t just good product strategy—it’s marketing.
5. Community and authentic signals matter
Agents synthesize user reviews, community discussion, and organic mentions. Manufactured testimonials and paid placements won’t fool systems designed to find authentic signal. Real user love becomes measurable competitive advantage.
The Timeline Is Now
G2’s research shows 87% of B2B software buyers say AI chatbots are changing how they research, with ChatGPT leading at 47% preference—nearly 3x any other LLM.
Semrush projects LLM traffic will overtake traditional search by end of 2027. Economic value parity is expected even sooner due to significantly higher conversion rates from AI-referred traffic.
This isn’t a 2030 problem. This is a 2025-2026 problem. The companies that figure out how to become the recommended answer—the favorite—will have an almost insurmountable distribution advantage.
The ones that don’t will wonder why their pipeline dried up while their competitors scaled.
