
Last updated: April 13, 2026
AI means marketers don’t need all the answers, but instead must ask the right questions and have the taste and experience to vet AI’s suggestions. Without the right tools or talent to fact-check responses, AI will “mansplain” to you, speaking confidently about things it doesn’t truly understand.
AI will change what makes customers feel special or seen as personalized marketing becomes cheap, ubiquitous, or even uncanny. Marketers have to thread the needle to come off as clever but not creepy.
But when applied with proper caution and creativity, AI is a massive force multiplier for small teams—it will allow them to refocus on strategy and empathy while AI handles the execution at scale. In turn, that could shift the makeup of teams, from including lots of junior employees implementing a top-down strategy to having fewer, more creative teammates experimenting and iterating with AI. Those who fail to adapt to using AI may find themselves obsolete: past shifts in technology were slower, but these new tools are proliferating too quickly to let employees ride out the rest of their careers relying on traditional skills.
Tofu and one of our investors, SignalFire, recently assembled a roundtable of CMOs from late-stage and public companies. Our goal was to define how AI is changing the pillars of marketing. Here are the top insights.

Finally, one surprising secondary effect of AI is that it’s creating an “authenticity vacuum” that businesses can fill by doing marketing that AI can’t: events. As customers get more skeptical of AI-personalized marketing, atoms-based real-world marketing such as events carry more weight for building trust and deepening relationships. And with remote work leading fewer people to get their social needs met by office life—and long-distance business travel shifting towards Zoom—it’s become easier to get people to attend local events, where you can envelop a prospect in your brand.
CMOs are using AI to scale content production, personalize outreach, summarize customer conversations for sales reps, and automate CRM updates. Platforms like Tofu enable senior marketers to do the work of multiple teammates by automating content generation and campaign execution across channels.
AI is shifting team composition rather than eliminating marketing entirely. CMOs report that senior content marketers equipped with AI can handle workloads that previously required larger teams. The focus is shifting from execution to strategy, curation, and creative direction.
Key risks include inconsistent outputs from LLM provider changes, potential data leaks from entering confidential information into AI tools, and brand damage from unedited AI content. Regulated industries like healthcare and finance face additional compliance considerations. Always edit and refine AI outputs before publishing.
AI is automating CRM updates (which consume up to 70% of sales reps' time), summarizing past customer conversations, and surfacing patterns across large datasets to identify effective strategies. Tools like Tofu help generate personalized sales collateral at scale, while platforms like People.ai prioritize prospects and troubleshoot funnel problems.
Chat engine ranking is the new SEO—it refers to how products and brands are recommended by AI interfaces like ChatGPT, Perplexity, and Google AI Overviews. Marketers are now seeking ways to influence and measure their visibility in AI-generated responses, not just traditional search results.
Popular tools among CMOs include Tofu for AI-native B2B content and campaign automation, ChatGPT for copywriting, Midjourney for imagery, People.ai for sales intelligence, Otter.ai and Fathom.ai for meeting transcription, and CreativeX for brand guideline adherence. The best approach is bottoms-up experimentation to find what works for your team.
AI is creating an "authenticity vacuum" as personalized digital marketing becomes ubiquitous. In-person events carry more weight for building trust because they offer experiences AI cannot replicate. With remote work reducing office socialization, professionals are more willing to attend local events, making them a high-value marketing channel.

As Generative AI transforms B2B marketing campaigns, measuring the ROI of these AI-driven initiatives presents new challenges and opportunities. By leveraging AI's analytical capabilities to gain deeper insights into customer engagement, conversion patterns, and revenue impact, B2B marketing leaders can develop a more comprehensive view of the customer journey and accurately assess the true impact of their campaigns on the bottom line.

How generative AI is transforming B2B lead nurturing with personalized content at scale, data-driven buyer journey optimization, and creative campaigns that deepen customer connections.

The rise of generative AI is transforming the skills landscape for B2B marketers, demanding a blend of technical proficiency, creative acumen, and ethical awareness. As CMOs navigate this shift, fostering a culture of innovation, continuous learning, and responsible AI usage within their teams will be crucial to harnessing the power of these tools.

Generative AI has emerged as a game-changer in B2B marketing, bridging the gap between data analytics and creative strategy. By leveraging the power of AI to generate personalized, data-driven content and campaigns, B2B marketers can enhance efficiency, drive innovation, and strengthen brand building efforts.

Ipsos B2B Marketing Benchmark Report for 2023 unveils the transformative role of personalized content and Generative AI in redefining customer engagement and loyalty. As leaders navigate economic uncertainties and increasing competition, leveraging these tools emerges as a strategic imperative for securing long-term growth and resilience.

Discover how AI-powered content creation can help you build stronger relationships, demonstrate a deep understanding of your prospects' needs, and ultimately drive more significant revenue growth in your ABM campaigns.

Discover six ways generative AI is revolutionizing content repurposing and personalization, enabling B2B marketers to create hyper-personalized, engaging content at scale in a matter of minutes.

Discover the do's and don'ts of using generative AI for B2B content marketing. Learn how to create personalized, engaging content that resonates with your audience while avoiding common pitfalls.

Five essential tips for integrating generative AI into your B2B marketing strategy.
A playbook for 1:1 marketing in the AI era
"I take a broad view of ABM: if you're targeting a specific set of accounts and tailoring engagement based on what you know about them, you're doing it. But most teams are stuck in the old loop: Sales hands Marketing a list, Marketing runs ads, and any response is treated as intent."
"ABM has always been just good marketing. It starts with clarity on your ICP and ends with driving revenue. But the way we get from A to B has changed dramatically."
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"ABM either dies or thrives on Sales-Marketing alignment; there's no in-between. When Marketing runs plays on specific accounts or contacts and Sales isn't doing complementary outreach, the whole thing falls short."
"In our research at 6sense, few marketers view ABM as critical to hitting revenue goals this year. But that's not because ABM doesn't work; it's because most teams haven't implemented it well."
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"To me, ABM isn't a campaign; it's a go-to-market operating model. It starts with cross-functional planning: mapping revenue targets, territories, and board priorities."

"With AI, we can personalize not just by account, but by segment, by buying group, and even by individual. That level of precision just wasn't possible a few years ago."
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This comprehensive guide provides a blueprint for modern ABM execution:
8 interdependent stages that form a data-driven ABM engine: account selection, research, channel selection, content generation, orchestration, and optimization
6 ready-to-launch plays for every funnel stage, from competitive displacement to customer expansion
Modern metrics that matter now: engagement velocity, signal relevance, and sales activation rates
Real-world case studies from Snowflake, Unanet, LiveRamp, and more
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