CMO Responsibilities in Generative AI

“I’m proud to report that Marketing is leading the AI initiatives at our company,” said a CMO at a $400M SaaS firm. No one rolled their eyes. Heads nodded. This wasn’t bravado; it's just business as usual, at least in our community. But that’s not the story we typically hear, is it? In the broader narrative, AI is the wild west. CMOs are either “dabbling,” “overwhelmed,” or drowning in vendor pitches. Most exec teams are still in the what do "we do with this thing?" stage. And yet, in three separate Huddles this month, we saw something different: a quiet revolution in motion. CMOs weren’t just experimenting with GenAI. CMOs were orchestrating it. Driving it. Owning it. Here’s how... Start with a Strategy (and a Few Custom GPTs) Savvy CMOs aren’t chasing shiny objects. They’re setting clear priorities—starting with branded GPTs to unify team voice and content quality. These tools act as internal brand guardians, enabling everyone to write like the company should sound, drawing from the same trusted sources. Support Sales Like a Strategist Forget static battle cards. The frontrunners are building GPTs for the sales org—loaded with objection handling, persona insights, competitive intel, and CRO-style tone. When a rep says, “I’ve got a frustrated IT buyer at 2pm,” the AI spits out prep faster than you can say “closed-won.” Creative First Drafts? AI’s Got It 100% of the 40+ CMOs who joined June’s Peer Huddles are using GenAI for content creation. From Jasper to custom GPTs to MidJourney for visual exploration, AI handles messy first drafts while humans apply the polish. One team runs content through two GPTs; one for writing, one for scrubbing out buzzwords, emojis, and em dashes. Time-Saving Workflows (Built by CMOs) One CMO used Replit and HubSpot to build a one-click campaign generator that assembles emails, landing pages, and social posts in under five minutes. Another swapped three time-sucking workflows for AI-powered alternatives and asked the team to do the same. Digital Doubles & Strategic Smarts Here’s where it gets spicy. Some Huddlers are building digital twins of their CEO, CRO, and CFO; GPTs are trained in executive tone, past presentations, and Slack history. The goal? Sanity checks before board meetings and messaging alignment without the calendar chase. Listening at Scale = Synthetic Empathy Perhaps the most exciting: Using AI to mine thousands of customer conversations from Gong, support, and win/loss calls to build “customer truth engines.” These CMOs aren’t guessing what customers want; they hear it in stereo. The result across all these use cases? Not just faster work. Smarter teams. Better alignment. Sharper strategy. Most importantly, CMOs are earning a seat at the AI strategy table (often at the head). So yes, Marketing is leading AI. The only question is: Are you? I'll share much more from this month's Peer Huddles in the June Huddle Up newsletter. If you're not a subscriber, now's a good time 🐧 💜

AI from a CMO’s perspective ⭐️ I’ve been using Gen AI in marketing for almost three years. 👩💻 At first, it was basic—summarising reports, copywriting, research and financials (always double-checking for hallucinations). Interestingly, most of AI’s highest-value use cases today are tactical—focused on improving media performance, customer service, and some pricing. I think we are in the Slope of Enlightenment phase, though - so the next stage, where agents become useful, is where it gets more interesting. 🚀 High-Value AI Use Cases ✅ Performance Marketing Optimization – bidding, targeting, and creative testing. ✅ SEO & Content Strategy – keyword clustering and topic ideation. ✅ Email Personalization – Predictive send times, dynamic content, and segmentation. ✅ Predictive Analytics & Customer Insights – churn, LTV, and behaviour forecasting. ✅ Conversational AI & Chatbots – customer service. ✅ Marketing Automation – lead nurturing and campaign optimisation. ✅ Social Listening & Sentiment Analysis – brand perception tracking and competitor insights. ✅ Creative Asset Generation – copy, images, and ad variations. ✅ AI-Powered Media Buying – Autonomous budget allocation based on performance data. ✅ Pricing & Promotion Optimization – dynamic pricing and offer personalization. ⚖️ Medium-Impact AI This is the "in development" zone—where AI is making progress, models aren’t quite there yet, and human expertise is essential. This is where I am learning how to program LLMs more to get the output I want to see from a creative and critical-thinking perspective. 🔸 Brand Strategy Development – insights; strategy is still human-led. 🔸 Creative Concepting & Ideation – AI suggests ideas but lacks true creative intuition. 🔸 Influencer Marketing & Partnerships – AI finds influencers, but human vetting is essential. 🔸 Public Relations & Reputation Management – AI monitors sentiment, but can’t manage crises. 🔸 Customer Journey Mapping – AI identifies patterns, but brands define the experience. 🔸 A/B Testing & Experimentation – AI runs tests, but humans decide what to test and why. 🔸 AI-Powered Video Editing – AI automates some editing, but storytelling remains human. 🔸 Speech & Audio Generation – AI-generated voices are improving, but tone and nuance still need human refinement. 🔸 Basic Copywriting – AI drafts content, but brand voice, depth, and storytelling need a human touch. 🛠 Low-Impact AI These areas are already well-served by existing tools or offer AI alternatives. That said, they still save time—and time is money. ⚡ Meeting Transcription & Summarization – Speeds up workflow ⚡ Stock Image & Background Removal – Convenient, but not a differentiator. ⚡ Automated Social Scheduling – AI optimizes timing, but engagement still requires a strong strategy. ⚡ Simple Graphic Design (Canva, AI Tools) – Good for quick assets, but lacks originality. ⚡ Basic Reporting & Dashboard Creation – AI automates, but interpretation is still key.

CMOs, Don’t Let the CIO Define Your AI Strategy. By now, every marketing leader has seen the pitch: “AI will replace your writers. Your strategists. Your creatives. Your campaigns.” But what if the real disruption isn’t in marketing, it’s in the boardroom’s view of it? AI isn’t just changing execution. It’s rewriting expectations for how marketing shows up at the executive table. Here’s what I mean: - 92% of companies plan to increase their AI investments in the next 3 years - But only 1% say they’ve reached maturity in execution (McKinsey & Company). - Meanwhile, employees are 3× more likely to be using gen AI in their workflows than leaders even realize. What’s the blocker? Leadership fluency. If your only AI use case is cost-cutting, you’re already trading trust for speed. And you’ll feel it in 2026. We don’t need marketers who just adopt tools, we need CMOs who redefine marketing’s value in an AI-augmented org. That means: ▪️ Explaining where AI adds value (and where it still needs human oversight) ▪️ Showing how AI scales outcomes; brand memory, market timing, message clarity, not just output ▪️ Building guardrails that protect reputation while enabling speed ▪️ Challenging assumptions that efficiency equals replacement The AI conversation isn’t just about automation. It’s about ambition. The best CMOs won’t just learn the tools, they’ll lead the transformation: ▪️Translating technical potential into board-level impact ▪️Framing AI as a force multiplier, not a replacement ▪️Elevating trust, not just targeting I’ve seen teams roll out unreviewed gen AI content that missed core positioning. It didn’t save time, it cost market trust. This moment is less about fearing obsolescence and more about embracing reinvention. Let’s not just adopt AI. Let’s set the strategy for defining the next era of growth. What’s your AI playbook at the executive table? Drop it below. #MarketingLeadership #AIstrategy #BoardReadiness #ExecutiveInfluence

𝑯𝒐𝒘 𝑪𝑴𝑶𝒔 𝑨𝒓𝒆 𝑺𝒖𝒄𝒄𝒆𝒆𝒅𝒊𝒏𝒈 𝒘𝒊𝒕𝒉 𝑮𝒆𝒏𝒆𝒓𝒂𝒕𝒊𝒗𝒆 𝑨𝑰 Generative AI (GenAI) is everywhere. The news. Social media. Even office water coolers. Talk about GenAI disrupting marketing is ongoing. Go beyond headlines like this one, courtesy of Salesforce: “Marketers estimated GenAI could save them up to 5 hours per week” and you’ll often see that these claims boil down to nothing more than easy-win productivity gains, resulting from automation of mundane marketing tasks. So, I’ve been thinking – is GenAI a valuable asset in a CMO’s toolkit? The answer is “yes”, 𝒃𝒖𝒕 𝒏𝒐𝒕 𝒊𝒏 𝒊𝒔𝒐𝒍𝒂𝒕𝒊𝒐𝒏. To achieve long-term success, GenAI use cases need to be deeper than surface-level automation. Winning CMOs will be combining GenAI with existing or new Customer Relationship Management (CRM) approaches, leveraging their human capital, and remaining conscious of GenAI’s limitations. → Combine 𝘸𝘪𝘵𝘩 CRM Consumers demand a highly-personalised journey, which hinges on data, but data-driven decisions are easier said than done, especially with the looming cookie cut-off. High-quality first-party data will be imperative and GenAI will be crucial for crunching out meaningful and usable insights to inform product development, market segmentation and campaigns. → Use GenAI 𝘢𝘭𝘰𝘯𝘨𝘴𝘪𝘥𝘦 your people You may be tempted to cut headcount after making some low-hanging productivity gains, but to do so would be incredibly shortsighted. GenAI is a helpful starting point to generate ideas and create early drafts, and tools like Midjourney support generalists in completing specialist tasks such as graphic design. But for compelling, relatable content, human insight is needed to finetune outputs.   → Leverage GenAI 𝘳𝘦𝘴𝘱𝘰𝘯𝘴𝘪𝘣𝘭𝘺 Risk accompanies opportunity. Questions remain about the data security, potentially reputationally damaging biases, and even the legality of outputs from GenAI, but choosing to wait or ignore GenAI altogether is not an option – employees will find a way to use it with or without your consent. Put yourself in the driving seat by introducing guidance and training early on. GenAI has the potential to support CMOs achieve their sales, growth or lead targets. Who wouldn’t want the 10-20% sales ROI uplifts suggested by McKinsey & Company’s research? But you need to be smart: > Automate the right processes – likely at the back-end where GenAI is invisible to the customer > Have a strategy – don’t use GenAI just because everyone else is, find the use cases that achieve the greatest ROI > Don’t reinvent the wheel – blend GenAI with your existing processes, people, and tools to maximise the utility of your data Have you explored GenAI yet? Thoughts? 👇 #generativeAI #artificialintelligence #marketing Source: CB Insights

I believe GenAI is a game changer for marketers. I have experienced first-hand with my teams & my clients how it boosts marketing efficiency, time to market, and helps us innovate in the customer experience. However, I also believe AI ethics are critical to reap these benefits, and CMOs have a key role to play. I recently had the pleasure of speaking to Marketing Week's Ian Burrell about this. As marketers, key decisions surrounding the ethical use of AI are within our influence and control. Some lessons I’ve learned: 💡 Transparency is crucial in order to maintain trust. As more GenAI assistants enter the market, we need to let our audience know whether they are interacting with AI or people. 💡 Brand guidelines around naming, representation, and voice of AI should sit with the CMO. Will you use a human or robotic voice? Will you give the AI a female or male name? 💡 The trend of AI assistants with female personas poses a long-term societal risk. What will happen if we condition a generation to consistently give orders to compliant female assistants? At Boston Consulting Group (BCG), we’ve issued brand guidelines around AI and have decided to use robotic voices and names with our technology to avoid these biases and promote a more neutral, inclusive approach. As the world continues to use AI and GenAI, addressing these ethical considerations is critical to ensuring responsible AI use. So to my fellow CMOs - are you set up to have a voice on AI ethics? Because we as marketers can lead the way! You can read the full piece here (although behind a paywall) https://lnkd.in/epy_izmz

One thing is clear: Artificial Intelligence (AI) is no longer a niche technology—it's the new electricity, shaping every facet of business. But here’s the question every CEO must ask: Who should lead your AI transformation? If you said the CTO, think again. A compelling article by Steven Wolfe Pereira argues that the Chief Marketing Officer (CMO), not the CTO, should drive AI strategy. Here's why: 1. AI is About Customers, Not Just Tech: While CTOs understand the technical infrastructure, CMOs live and breathe customer insights. AI’s primary impact lies in enhancing customer experience—through personalization, chatbots, dynamic pricing, and more. These are domains where CMOs already excel. 2. The Business Case for CMO Leadership: Studies show 80% of AI projects fail because they’re treated as science experiments instead of solutions for real-world problems. A CMO-led approach focuses on aligning AI initiatives with customer needs, business outcomes, and brand trust. 3. A Symphonic Approach: Steven proposes a collaborative model: The CMO as the conductor, setting the strategic direction, while the tech team acts as enablers, ensuring seamless execution. Steps for CMOs to Lead AI Strategy Educate: Gain a deep understanding of AI use cases and best practices. Collaborate: Partner with CTOs/CIOs to assess data readiness and capabilities. Prioritize Customers: Develop a roadmap addressing ethical considerations and real customer needs. Measure: Define clear metrics to track the business impact of AI initiatives. Why This Matters In 2025, companies optimizing for technology instead of people risk falling behind. Fortune favors the brave—and in this case, the brave are CMOs who put customers first. As Steven rightly puts it: "Deploying AI isn’t just about tech—it’s about serving customers better. The CMO should be the master electrician, ensuring AI is everywhere, solving real problems." https://lnkd.in/gb62fiym

From Chief Marketing Officer → Chief Market Orchestrator 🎯 A year ago, I was managing a 180-person marketing org. Today, I orchestrate 10 humans and more than a dozen AI and automation agents, tools, apps across content, pipeline, research, outreach, and GTM. It’s not a downgrade. It’s an upgrade in complexity. Being a CMO used to be about budgets and branding. But now it seems to be about: Coordinating multi-modal workstreams across AI agents, analysts, contractors, and internal teams. Driving go-to-market and product direction based on signal data from dozens of daily marketing experiments Running cross-functional orchestration: product, sales, content, comms, and market feedback loops in real time. 📍In Q2, in one 90-day sprint: We rewrote product positioning based on agent outputs and B2B buyer feedback We built a messaging engine that fed real-time campaign data into product launches We ran weekly orchestration sessions that merged pipeline blockers with use case prioritization We built a system where the marketing team was responsible not just for MQLs but for helping shape what should be built. This isn't just accomplished with delegation. This is real stretch operating. As Nikki Vegenski put it: “The CMO seat today is less about ownership and more about orchestration.” “You’re syncing humans and machines to move in harmony toward real growth.” Deloitte backed it up: 95% of CMOs are on the hook for revenue. But only 32% feel equipped to grow market share. Meanwhile, AI-native orgs are compressing execution time from months → days. I have seen this first-hand What used to take weeks - a segment analysis, a message test, a partner activation - can now be triggered, launched, and measured in a 48-hour window with the right orchestration model. But this is not easy. The work is heavier and the compleity is non linear. Keeping evertyghin in my mind sometimes feels impossible. Is this working out? Time alone will tell. But it has been the best kind of stretch. The modern marketing leader is an MARKET OPERATOR working at the intersection of: Tech (agents, automation, AI) Narrative (messaging, ICP, feedback loops) Revenue (pipeline, motion, pricing) System Design (how it all runs together Are you seeing this shift in your org too? Comment below and let me know!