I watched something unsettling in our analytics last month. A prospect visited our website, engaged with our chatbot, requested a demo, watched automated product walkthroughs, compared pricing, signed up for a trial, activated core features, and converted to paid—all without a single conversation with a sales rep.
This wasn't a small deal. It was a $47K annual contract from a 200-person company. The entire buyer journey from first visit to closed-won took nine days and involved zero human sales interaction.
When I asked our head of sales about it, she shrugged. "Happens more and more. Especially with companies under 500 people. They don't want to talk to sales. They want to research independently, try the product, and make their own decision."
That moment crystallized something I'd been avoiding: AI agents aren't going to replace sales reps in some distant future. They're already handling buying journeys for a significant portion of prospects. The question isn't whether this will happen—it's what product marketers do when our primary customer isn't sales reps anymore, it's AI agents and self-directed buyers.
The Silent Majority Who Never Talk to Sales
I started tracking buyer journeys more carefully after that $47K self-serve deal. I wanted to know how common it was. The data was startling.
In deals under $25K annually, 67% of buyers never spoke to sales. In deals $25K-$50K, 42% self-served entirely. Even in deals over $50K, 23% completed evaluation and purchase without requesting sales contact.
These weren't unqualified leads abandoning the funnel—they were qualified buyers with budget and authority who chose to buy without sales conversations. They researched alternatives, evaluated our product, compared pricing, assessed fit, and made purchase decisions entirely through self-service channels.
The traditional buyer journey assumed prospects would request demos, talk to sales, negotiate pricing, and require human assistance to complete purchase. That assumption is breaking down.
Modern buyers prefer to research independently. They read documentation, watch product videos, try free trials, consult peer reviews, compare features on third-party sites, and make decisions without sales pressure. The companies winning these deals aren't the ones with the best sales reps—they're the ones whose positioning, documentation, and self-serve experience enable buying without sales support.
This shift changes product marketing fundamentally. Instead of enabling sales reps to explain our value, I need to enable prospects to discover our value independently. Instead of creating sales narratives, I need to create self-serve buyer journeys. Instead of equipping humans to answer questions, I need to create content and experiences that answer questions automatically.
The customer for my positioning work is shifting from sales reps to AI agents and self-directed buyers who never talk to humans.
What AI Agents Actually Do in Buyer Journeys
The self-serve buyers I tracked weren't just reading static content—they were interacting with AI agents that guided their evaluation.
Our chatbot answered product questions, suggested relevant case studies, compared our features to competitors, explained pricing, recommended the right plan tier, and even negotiated minor discounts automatically. Prospects asked questions like "how does your security compare to [competitor]?" and got instant, detailed answers pulling from our documentation, competitive battlecards, and compliance certifications.
Then I checked what happened on third-party sites. AI tools like ChatGPT, Perplexity, and Claude were becoming research assistants for buyers. Prospects would ask "compare the top five analytics platforms for mid-market SaaS companies" and get recommendations based on publicly available information, reviews, and positioning.
The scary part: these AI agents were making recommendations based on how discoverable and well-structured our information was, not how good our product was. Competitors with inferior products but better documentation and clearer positioning were getting recommended more often because their information was easier for AI to find and synthesize.
I tested this myself. I asked ChatGPT to compare our product to three competitors. It recommended a competitor with worse features but better API documentation because it could actually find details about their capabilities while our documentation was scattered and poorly structured.
That's when I realized: AI agents are becoming the primary research assistants for buyers, and they're making recommendations based on information accessibility, not product quality. Product marketing's job is shifting from persuading humans to informing AI agents so they recommend us accurately.
Optimizing for AI Discovery vs. Human Persuasion
I spent the next month redesigning our positioning and content for AI discoverability instead of human persuasion. The differences were significant.
Human-optimized positioning focuses on emotional resonance, storytelling, and building trust through social proof. AI-optimized positioning focuses on structured data, clear feature descriptions, and easily parseable comparisons.
I rewrote our homepage from marketing copy designed to build excitement to structured information designed to be AI-readable. Instead of "Transform your analytics with AI-powered insights that drive results," I wrote "Real-time product analytics platform with SQL querying, cohort analysis, and predictive modeling. Integrates with Segment, Snowflake, and BigQuery. SOC 2 Type II certified."
The second version converts worse with human readers—it's boring and feature-focused. But it converts better with AI agents because it clearly states capabilities in structured, parseable language.
I applied the same thinking to competitive positioning. Instead of subtle competitive traps designed for sales conversations, I created straightforward feature comparison tables, clear pricing breakdowns, and direct capability statements. AI agents don't appreciate clever positioning—they appreciate clear, factual information they can synthesize into recommendations.
I tested this by creating structured comparison content and monitoring AI recommendations. Within six weeks, our mention rate in AI-generated buyer research increased 34%. We weren't changing our product—we were making our positioning more discoverable and AI-readable.
I started using platforms like Segment8 that help structure competitive intelligence and messaging for both human and AI consumption. The insight wasn't just creating battlecards—it was ensuring that competitive positioning was formatted in ways AI agents could parse and present accurately to prospects during research.
The Death of Traditional Sales Enablement
If buyers aren't talking to sales reps, traditional sales enablement becomes irrelevant. Battlecards, pitch decks, objection handlers, discovery scripts—all designed for human sales conversations that increasingly aren't happening.
I found myself in a strange position: spending weeks creating sales collateral that a growing percentage of deals never used. The $47K self-serve deal I mentioned earlier? The buyer never downloaded a single sales asset. They consumed help documentation, API docs, pricing pages, and customer reviews. All the traditional sales enablement materials were invisible to their journey.
This forced me to rethink what "enablement" means when the primary buyer journey is self-serve. Instead of enabling sales reps, I needed to enable prospects to buy without sales support.
That meant different content priorities. Comprehensive help documentation became more important than pitch decks. Clear pricing pages became more important than pricing negotiation scripts. Product demo videos became more important than sales demo preparation. API documentation became more important than technical sales training.
The uncomfortable shift: traditional sales enablement was designed to give sales reps information asymmetry. They knew things prospects didn't, creating dependency on sales conversations to get information. Self-serve buyer journeys eliminate that asymmetry. Prospects expect to access all information independently.
Product marketing for self-serve means publishing everything openly instead of gating it behind sales conversations. Pricing transparency instead of "contact us." Feature details instead of "schedule a demo to learn more." Competitive comparisons instead of "ask us how we differ from competitors."
This transparency feels risky—won't we lose negotiation leverage? Won't competitors see our strategy? But the data showed buyers preferred companies that published information openly versus those that required sales contact for basic details. The companies winning self-serve deals weren't the ones protecting information—they were the ones making it freely accessible.
Conversational Commerce and the PMM Role
The AI agents handling buyer conversations aren't replacing sales reps with worse substitutes—they're creating better buyer experiences by providing instant answers, personalized recommendations, and frictionless purchasing.
I watched our chatbot handle complex product questions better than junior sales reps because it had instant access to all documentation, competitive intelligence, and customer examples. It could answer "how does your data retention compare to [competitor]?" in 10 seconds with specific details and documentation links. A sales rep would need to research and follow up.
The chatbot could also personalize recommendations based on company size, industry, and use case without the awkwardness of sales qualification questions. "Based on your team size of 50 and usage of Salesforce, I'd recommend our Growth plan with the Salesforce integration. Here's a comparison of Growth vs. Enterprise features for teams your size."
This conversational commerce is evolving faster than most PMMs realize. AI agents aren't just answering simple questions—they're guiding complex evaluations, handling objections, comparing alternatives, and facilitating purchases for deals up to $100K without human involvement.
The PMM role in this world shifts from crafting sales narratives to training AI agents. Instead of writing pitch decks, I'm writing knowledge bases that chatbots query to answer prospect questions. Instead of creating objection handlers for reps, I'm creating structured responses AI agents can surface contextually. Instead of coaching sales on competitive positioning, I'm ensuring AI agents have accurate competitive data to present when prospects ask for comparisons.
The skills required are completely different. I need to think in information architecture, structured data, and conversation design rather than persuasive narratives and sales enablement.
What PMMs Should Do Now
The shift to AI-mediated buyer journeys is already happening for a significant portion of deals. Waiting to adapt until it's the majority of deals means playing catch-up when you should be leading.
Three actions I'm taking now:
First, auditing buyer journeys to understand what percentage complete evaluation and purchase without sales contact. Track which content they consume, which questions they ask AI agents, where they get stuck, and what information gaps cause them to abandon. This reveals where your self-serve experience succeeds and fails.
Second, restructuring positioning and content for AI discoverability. Make pricing transparent. Create structured feature comparisons. Write documentation AI agents can parse accurately. Publish competitive positioning openly instead of hiding it in sales battlecards. Optimize for being recommended by AI research assistants, not just ranking in search engines.
Third, shifting from sales enablement to buyer enablement. Invest in comprehensive documentation, self-serve demos, transparent pricing, and AI chatbot capabilities instead of traditional sales collateral. Make it possible for qualified buyers to evaluate and purchase without sales conversations.
The companies that figure out AI-optimized positioning and frictionless self-serve journeys will win the deals where buyers prefer not to talk to sales. The companies still optimizing exclusively for human sales conversations will lose them.
The future of product marketing isn't about enabling sales reps to sell better—it's about enabling buyers to buy without sales reps at all. That future is already here for a growing segment of deals. The question is whether you're building for it or still building for the past.