From the new SaaStr “Swapping Notes” podcast series – essential listening for every B2B founder and marketing leader navigating the AI transformation
The AI Marketing Revolution: Key Insights from G2’s CMO on How B2B Buying Has Forever Changed
From the SaaStr “Swapping Notes” podcast series – essential listening for every B2B founder and marketing leader navigating the AI transformation
Speaker Bios
Sydney Sloan, CMO at G2
Sydney Sloan brings over a decade of B2B marketing excellence to her role as Chief Marketing Officer at G2, the world’s largest software marketplace. Previously, she led marketing initiatives at high-growth companies including SalesLoft and Adobe, where she honed her expertise in scaling go-to-market strategies. Beyond her operating role, Sydney is an active LP at Stage 2 Capital and part of the Scale Ventures network, where she advises founders on growth strategies. Her unique position at G2 gives her unparalleled visibility into both sides of the B2B buying equation – how buyers research and how sellers adapt.
Guillaume Cabane, Co-Founder and General Partner at HyperGrowth Partners
Guillaume Cabane is Co-Founder and General Partner at HyperGrowth Partners, where he advises approximately 20 of the best B2B companies annually on accelerating growth. His impressive operating background includes building growth teams at segment-defining companies like Segment, Drift, and Gorgeous, followed by leading all of marketing at Ramp, the fast-growing fintech company. With over 10 years of hands-on B2B marketing experience, Guillaume has developed a reputation for identifying and implementing growth strategies that work at scale.
Amelia Lerutte, Chief AI Officer at SaaStr
Amelia Lerutte serves as Chief AI Officer at SaaStr, where she leads the organization’s AI strategy and implementation across all verticals. She hosts the “Swapping Notes” podcast series, focusing on practical AI applications in B2B software. Her role puts her at the center of the AI transformation happening across the SaaS ecosystem, working directly with founders and operators implementing AI strategies.
The Three Pillars of AI’s B2B Marketing Disruption
The conversation revealed three fundamental ways AI is reshaping B2B software marketing, each representing a seismic shift that demands immediate attention from every marketing leader.
1. AI as “Always Included” – The New Table Stakes
Perhaps the most striking finding from G2’s latest buyer behavior report: 88% of buyers won’t even consider software that doesn’t include AI capabilities. This isn’t about nice-to-have features anymore – it’s about basic viability in the market.
“You absolutely have to be able to add AI and AI capabilities to existing platforms,” Sloan emphasized. “The fastest people to switch are enterprises. Usually enterprises aren’t the ones that adopt it first, but that is what the data showed us – enterprise were first movers here and they were doing it because of the productivity gains.”
This enterprise-first adoption pattern breaks conventional wisdom about technology adoption curves. When large organizations with complex buying processes are moving fastest, it signals that AI isn’t just a trend – it’s becoming foundational infrastructure.
Action Items for Marketing Leaders:
- Audit your current product messaging to ensure AI capabilities are prominently featured
- Develop competitive positioning that highlights your AI differentiation
- Create content that speaks to enterprise buyers’ productivity gain expectations
- Train sales teams to lead with AI value propositions in enterprise conversations
2. The Agentic Strategy Revolution
Beyond adding AI features to existing platforms, buyers are now developing comprehensive “agentic strategies” – determining which platforms will serve as the foundation for their AI agent implementations.
This creates a fascinating dynamic where software selection isn’t just about current functionality, but about a platform’s potential to serve as an AI development environment. Buyers are asking: “Can I build my ideal AI workflows on this platform?”
Sloan noted: “People are now at the point of setting their agentic strategy and then trying to determine which platforms they want to use to build out their agent. So you’ve got this really interesting time where AI is being added to platforms, and you can build now with AI.”
Strategic Implications:
- Product roadmaps must consider extensibility and AI-building capabilities
- Marketing must speak to platform potential, not just current features
- Sales enablement should include conversations about buyers’ broader AI strategies
- Partnership opportunities emerge with AI development tool companies
3. LLM-First Buying: The Death of Traditional Funnel Marketing
The most disruptive change is how buyers now start their research journey. Traditional marketing funnels assumed buyers would discover solutions through search engines, content marketing, or referrals. Now, they’re going directly to Large Language Models for their initial research.
“They’re going to LLM first which is then changing the marketers world of how we have to think about marketing in the age of LLM – the new LLM buying process and PPC is no longer the way that we can buy our way,” Sloan explained.
The new buyer journey looks like this:
- LLM Research: Buyers start with ChatGPT, Claude, or other LLMs for initial discovery
- Source Verification: They visit the sources cited by the LLM (often user-generated content sites)
- Peer Review: They check peer review sites like G2 for validation
- Shortlist Creation: LLMs help build RFP templates and vendor shortlists
- Direct Engagement: Only then do they visit vendor websites or marketplaces
The Trust Transfer: From Marketers to Machines
A sobering reality emerged from the conversation: buyers trust LLMs more than they trust marketers. As Guillaume Cabane put it: “Us marketers from the consumer’s perspective have never been worthy of trust. We’ve been trying to cue the perception. There’s some soft lying that has been happening forever. And so now we’re getting disrupted. We’ve lost some of that trust.”
This trust transfer creates two distinct categories of marketing that will survive:
AI-Proof Marketing
- Social proof and influencer relationships: Human connections remain valuable
- User-generated content: LLMs love and prioritize authentic user content
- In-person events and experiences: Physical interactions build trust
- Direct personal outreach: Trusted relationships bypass AI intermediation
AI-Influence Marketing
If you can’t build direct trust, you must influence the AI systems that buyers trust. This requires a fundamental shift from SEO (Search Engine Optimization) to what industry experts are calling GEO (Generative Engine Optimization).
GEO differs from SEO in crucial ways:
- Focus on answers, not clicks: Content must directly answer questions
- Jobs-to-be-done orientation: Write content around what buyers need to accomplish
- LLM-preferred formats: Listicles, user-generated content, and structured data
- Source credibility: Being cited by trusted sources becomes critical
The Content Strategy Revolution
The shift to LLM-first buying demands a complete content strategy overhaul. Instead of creating content designed to drive website traffic, marketers must create content designed to train AI systems.
Sloan shared a practical example: “If I’m a salesperson and we’re selling contact data for sales, maybe that’s a challenge they have to research. But if you think about their entire jobs to be done, they also want to know negotiation skills or they might want to know other things. Well, you can still build content for that. You can still add value to every single question that they’re going to ask the LLM.”
The Hidden Website Strategy
Cabane revealed an emerging tactic: “I’m seeing more and more companies build hidden websites completely hidden to humans. It’s an entire other index, an entire other web tree for the purpose of AI agents to scrape that was not allowed in a Google-centric world because Google wanted to see exactly what the humans were going to see and you were penalized for doing that. You’re not being penalized now.”
This represents a fundamental shift in how we think about content architecture. Companies are creating dual content systems:
- Human-facing content: Traditional websites optimized for human readers
- AI-facing content: Structured, comprehensive content designed for LLM consumption
The Future of Sales: Sell by Chat
The conversation revealed an emerging trend that could reshape B2B sales entirely: “sell by chat.” SaaStr has seen a 50/50 split between traditional website purchases and AI-driven chat sales for their events.
“We’re literally seeing it 50/50 now. Some people prefer to buy via chat. We call it sell by chat,” Lerutte shared. “Our AI is basically selling tickets to future SaaStr events all via email, all automated.”
This trend points toward a future where:
- LLMs become sales channels: AI systems don’t just research – they transact
- Context switching disappears: Buyers complete entire purchase journeys within chat interfaces
- Websites become data sources: Traditional websites serve AI systems rather than human visitors
Practical Implementation: The 8-Month Timeline
Sloan predicted that the industry has approximately 8 months to adapt to these changes: “I see us being at that point in the next 8 months – people are going to reimagine the experience and build for that.”
Immediate Action Items (Next 30 Days)
- Audit AI presence: Ensure AI capabilities are prominently featured in all marketing materials
- Begin GEO research: Identify the questions your buyers ask LLMs about your category
- Content inventory: Catalog existing content for LLM optimization potential
- Tool adoption: Force daily LLM usage across the marketing team
Medium-term Initiatives (3-6 Months)
- Develop hidden AI-facing content: Create comprehensive, structured content for LLM consumption
- Build chat-first experiences: Implement conversational interfaces on key web properties
- Establish measurement frameworks: Track LLM citation and influence metrics
- Train sales teams: Develop “sell by chat” capabilities and processes
Long-term Transformation (6-12 Months)
- Website redesign: Reimagine web experiences as conversational interfaces
- Agent handoff systems: Build seamless transitions between AI and human interactions
- Agentic platform capabilities: Develop platform features that support buyer AI strategies
- Partnership ecosystems: Align with AI development and orchestration tool providers
The Resource Allocation Reality Check
Perhaps the most challenging insight came from Cabane’s observation about budget allocation: “I’ve been in multiple CMO rooms and settings lately where I’ve asked who is spending 25% of their budget and headcount on LLM appearance. No one raised their hand. And that doesn’t make sense because that’s where we’re heading 12 months from now.”
This suggests a massive disconnect between where the market is heading and where marketing organizations are investing. The implication is clear: marketing teams need to reallocate resources dramatically and immediately.
Recommended Budget Reallocation
- 25% of budget toward LLM influence and optimization
- Reduced spend on traditional search and display advertising
- Increased investment in user-generated content creation
- New roles: AI orchestration specialists and GEO experts
The Toolstack Revolution
The conversation highlighted several categories of tools that have become indispensable:
Content Creation and Optimization
- Voice AI tools: Whisper and similar tools for rapid content creation
- AI writing assistants: For persona-based messaging and rapid iteration
- Content workflow automation: Tools like GoLinks and AirOps for scaled content production
Conversation and Analysis
- Meeting AI tools: Granola and similar tools for automated note-taking and summarization
- Strategic thinking partners: LLMs configured as specialized consultants for rapid strategic development
Conversion and Sales
- Intelligent workflows: Automated lead qualification and meeting booking
- Chat-based sales systems: Conversational commerce tools
- Agent handoff platforms: Seamless transitions between AI and human interactions
The Mindset Shift: From Campaign Thinking to Ecosystem Thinking
The fundamental change required isn’t just tactical – it’s philosophical. Marketing leaders must shift from thinking about campaigns and funnels to thinking about ecosystems and influence networks.
Traditional marketing asked: “How do we get buyers to our website?” AI-era marketing asks: “How do we ensure AI systems recommend us when buyers ask relevant questions?”
This requires:
- Brand building at scale: Influence across multiple trusted sources
- Content ubiquity: Presence in every relevant conversation and knowledge base
- Relationship mapping: Understanding the network of influence that affects AI recommendations
- Trust architecture: Building credibility that transfers through AI intermediation
Preparing for the Webless Future
Both Sloan and Cabane painted a picture of a future where traditional websites become largely irrelevant for buyer interactions. Instead of HTML rendering in browsers, AI systems will connect directly to databases and APIs to access product information and complete transactions.
“It is not hard to imagine that the front end of the web disappears,” Cabane noted. “You can just have the LLM connect to the databases – ‘What do you sell? What’s the product description?’ And then complete transactions.”
This shift requires marketing leaders to think beyond web properties toward:
- API-first content strategy: Structured data that AI systems can easily consume
- Database optimization: Product information organized for programmatic access
- Integration readiness: Systems designed for AI agent interaction
- Transaction enablement: Commerce capabilities accessible through conversational interfaces
The Competitive Advantage Window
The most urgent message from this conversation is that competitive advantages in AI marketing are available now, but the window is closing rapidly. Organizations that implement these strategies in the next 6-12 months will establish positions that become increasingly difficult to replicate.
As Cabane emphasized: “The sooner you get there, the more influence you’ll have. It’s going to be outsized.”
The leaders who understand this transformation, allocate resources accordingly, and execute quickly will define the next era of B2B marketing. Those who wait will find themselves competing for relevance in a world where their traditional advantages no longer apply.
The Reset Button Has Been Pressed
Sydney Sloan’s observation that “everybody’s at the starting line” captures the unprecedented nature of this moment. AI hasn’t just created new opportunities – it has fundamentally reset the competitive landscape.
For marketing leaders, this represents both the greatest challenge and the greatest opportunity in decades. The frameworks, tactics, and strategies that built successful B2B companies over the past 20 years are being replaced in real-time.
The question isn’t whether this transformation will happen – it’s whether your organization will lead it or be left behind by it.
The AI marketing revolution is here. The only question left is: What’s your move?
For more insights on AI in B2B software, subscribe to the SaaStr “Swapping Notes” podcast series and join us at the upcoming SaaStr Annual + AI Summit in May 2026, where 36% of attendees are CEOs sharing cutting-edge AI strategies.
