This week: Why your GTM strategy is a systems problem, how AI is creating hybrid human-agent teams, and why smaller companies are winning the AI race. And the $10 billion risk of ungoverned AI, plus how to finally prove marketing’s impact on revenue.

Your GTM Is a Systems Problem, Not a Marketing Problem

If your growth has stalled, the issue likely isn’t your marketing campaigns—it’s your revenue architecture. Many leaders treat marketing as a series of sugar highs, chasing quick wins with new campaigns while ignoring the leaky bucket underneath.

The real problem is often structural: misaligned teams, a broken handoff process, and no shared definition of success. According to RevOps architect Ian Feder, marketing problems are almost always revenue architecture problems. Before you pour more budget into ads, you have to diagnose the system. Are sales, marketing, and product all chasing different metrics? Is there a documented process from first touch to final sale?

This requires a shift in mindset from campaign manager to systems architect. Your job is to align the entire revenue function around a single set of goals and a shared understanding of the customer. As B2B Marketing panel participants agreed, the role of the modern CMO is to be a commercial marketer who can orchestrate this entire system. As Peep Laja notes, you earn the right to do strategy by first proving you can execute.

Comment Insights

• Jason M. Lemkin notes that B-tier executives slow down the pace of an organization, making alignment and high-performance culture even more critical.
• Brian Halligan points out that startups have an advantage in making bold moves because they have nothing to lose, unlike large companies with an installed base to protect.

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The Human-AI Hybrid Team Is the Future of GTM

The debate is no longer about whether AI will replace sales and marketing jobs. It’s about how it will redefine them. The future of go-to-market isn’t a battle between humans and machines; it’s a blended model where humans orchestrate teams of AI agents to achieve new levels of productivity.

This new structure creates the "Agentic Enterprise," where AI handles scale and humans eliminate friction. As Aaron Levie explains, AI makes specialized skills abundant, allowing a single person to do more. But it also makes experts in any given field far more potent, raising the bar for what a job entails. Instead of replacing roles, AI is transforming them.

For CMOs, this means preparing for a significant shift in team structure and skill sets. The most valuable employees won’t just use AI; they will manage and direct it to drive business outcomes. The SDR becomes an orchestrator of AI workers, and the marketing ops leader becomes a GTM engineer. As Dan Martell notes, the jobs that survive are the ones directing the work, not just doing it.

Comment Insights

• Jason M. Lemkin shares that at SaaStr, they replaced employees who left with AI agents, finding the outcome to be "more work but better."
• Dharmesh Shah reflects on HubSpot’s journey into CRM, noting that AI makes the mission of creating a simpler, more unified platform even more exciting.

The New Economics of AI: Why Small Companies Are Winning

A counterintuitive trend is emerging in AI adoption: smaller, more agile companies are seeing a faster and more significant return on investment than their larger enterprise counterparts. While the narrative often focuses on massive AI budgets at Fortune 500s, new data suggests that agility and a willingness to redesign workflows are more critical than the size of the investment.

According to a 2025 AI Adoption Report from Wharton, 75% of all companies see a positive ROI on AI. But as Aaron Levie highlights, the delta is stark: smaller companies report much higher rates of significant gains and are far less likely to be stuck in the pilot phase. The reason is simple. The true value of AI is unlocked not by plugging it into existing processes, but by fundamentally changing how work gets done.

This is a direct challenge to the idea that only companies with massive resources can win with AI. For CMOs, the takeaway is that you don’t need a nine-figure budget to see a return. Success hinges on your team’s ability to be nimble and rethink processes from the ground up. As a McKinsey report on corporate venturing confirms, companies that serially build new ventures with AI are seeing quicker returns.

Proving Marketing’s Revenue Impact

In a market where every dollar is scrutinized, marketing teams are under immense pressure to prove their contribution to the bottom line. Yet, a staggering number of marketers still struggle to connect their efforts to revenue. This disconnect often stems from a reliance on outdated attribution models that fail to capture the complexity of the modern B2B buyer journey.

The problem with traditional last-touch attribution is that it oversimplifies a long and winding path. As a RevSure webinar on attribution explains, B2B buyers interact with multiple touchpoints—ads, blog posts, webinars, peer reviews—before ever speaking to sales. Attributing a deal solely to the final click on a demo request form ignores the crucial brand-building and educational content that influenced the decision. This leads to misallocated budgets and a marketing engine optimized for short-term conversions, not long-term growth.

To gain credibility with the C-suite, CMOs must shift from vanity metrics to revenue-focused KPIs. As brand marketer Liam Moroney points out, you can’t answer "how will you increase results?" without first understanding the total addressable demand. This means adopting multi-touch attribution models, tracking brand recall through search, and providing a holistic view of the entire funnel.

The $10 Billion Risk of Ungoverned AI

While the promise of AI is immense, so are the risks. Forrester predicts that B2B companies will lose more than $10 billion by 2026 due to the ungoverned use of generative AI. This financial fallout will stem from everything from inaccurate information eroding buyer confidence to legal and brand safety crises.

The core of the problem is that while companies are rushing to adopt AI, their governance practices haven’t kept pace. As buyers increasingly use genAI for research, they are also growing more skeptical of its outputs, with 19% reporting decreased confidence in purchasing decisions due to unreliable AI-generated information. This has led to a counter-trend: Forrester also found that 30% of buyers will prioritize interactions with human product experts over AI tools for critical purchase stages.

This isn’t just an IT or legal issue; it’s a GTM and brand trust problem. CMOs must lead the charge in establishing robust AI governance, not as a restrictive measure, but as a way to build trust and ensure AI is used effectively and ethically. This includes democratizing governance efforts and boosting the "AI intelligence quotient" of their teams. As NTT DATA’s report on the ethical considerations of GenAI makes clear, building trust through safety, fairness, and transparency is paramount.

Sound Bites

• 🎥 Auto-Reply System That Books Meetings in Under 5 Minutes: A detailed walkthrough of a multi-touch, speed-to-lead playbook using Clay, Slack, and LinkedIn to automate replies and book meetings from cold email.
• 🎙️ The Importance of Strategy & Measurement to Scale your B2B Tech Brand: Gearoid Buckley, former marketing leader at LinkedIn, shares insights on marketing to marketers, the importance of customer understanding, and building a clear measurement framework.
• 🎥 The LinkedIn Ads Strategy Behind $1.2M in Pipeline: A full-funnel strategy for LinkedIn Ads, covering top-of-funnel retargeting, bottom-of-funnel conversion, and a mid-funnel content strategy built around social proof and education.

That’s all for this week. The throughline is clear: AI is a powerful accelerant, but it can’t fix a flawed strategy. The leaders who will win in 2025 are those who are doubling down on the fundamentals—a deep understanding of their customer, a differentiated message, and a relentless focus on proving their impact on revenue.