Grant McDougall

2025 CMO Survey The 34th edition of The CMO Survey shows that CMOs are aligned with their C-suite on most things—but one critical piece may still be missing. https://lnkd.in/e4pRA87W

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A Call for Conscious Capitalism: Rethinking Our Investment Priorities - On October 29, 2025, Nvidia achieved an unprecedented milestone—becoming the world’s first company to reach a $5 trillion market capitalization[1]. Yet this historic valuation raises a critical question about how we, as a society, are deploying capital. The Paradox of Market Concentration Nvidia’s $5 trillion valuation, now $1 trillion more than Microsoft—the next-closest competitor[1]—reflects the current global obsession with artificial intelligence. Major institutional investors, including Vanguard, BlackRock, and Fidelity Investments, have poured unprecedented capital into this single company. However, this concentration of wealth in a company with a relatively lean workforce reveals a troubling misalignment between shareholder returns and societal benefit. Employment as Economic Foundation Here lies the contradiction: Nvidia creates far fewer jobs than other trillion-dollar tech giants. Unlike Amazon, which employs 1.5 million people, or Microsoft, with 228,000 employees, Nvidia operates with just 36,000 workers. While efficiency and technological advancement matter, this disparity underscores a fundamental problem—capital is flowing disproportionately toward companies that generate the least employment opportunity. The Real Cost of Misallocated Capital Meanwhile, millions of college graduates worldwide struggle to find meaningful work. Without employment, individuals cannot participate in the economic cycle that sustains healthy societies. They cannot consume, cannot contribute, and cannot build dignified lives. This isn’t just a personal crisis; it’s a systemic economic failure. Supply Chain Vulnerabilities Adding to this concern, Nvidia faces significant challenges regarding access to rare earth minerals essential for semiconductor production. Overconcentrating capital isn’t the solution for the supply chain constraints, instead diplomacy and fair trade agreements. A Path Forward We need a fundamental shift toward conscious capitalism—investment strategies that prioritize job creation, workforce development, and companies that enable people to live with dignity and contribute meaningfully to society. The question isn’t whether we can afford to invest in people; it’s whether we can afford not to. #Investors #NVIDIA #BigTech #Capitalism #Leadership #Vanguard #BlackRock #Fidelity #StateStreet https://lnkd.in/eeF8GmG2

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WPP released a remarkably well-crafted white paper on their AI strategy. It reads like a Hollywood screenplay - compelling narrative, impressive scale, ambitious vision. But strip away the storytelling, and WPP’s AI is skin deep. I mean that figuratively and literally, their innovation is mainly skins. While WPP showcases workflow optimisations and off-the-shelf integrations, Publicis builds proprietary technology with 20,000+ engineers. While WPP announces partnerships with existing AI platforms, Accenture and Deloitte construct commercial moats through genuinely proprietary tools. WPP is essentially reskinning other people’s innovations rather than creating their own. They lack the technical competence to build truly differentiated technology, so they’ve chosen the path of sophisticated workflow management. This isn’t necessarily wrong (you do your best with what you have) but it’s not strategically defensible, and better clients can tell. Those impressive investment figures WPP cites? The vast majority are non-cash. They’re valuing employee training time at client billable rates - as if every hour spent learning ChatGPT was charged at £300/hour consultancy rates. It’s accounting theater that makes internal capability development appear like massive capital investment. This represents the fundamental choice facing every agency: workflow optimisation versus technological differentiation. Publicis chose differentiation. Their CORE AI platform and Epsilon integration create genuine competitive moats. Clients can’t replicate this elsewhere. Accenture chose technological mastery. Their build-operate-transfer model requires proprietary capabilities that justify premium pricing and recurring revenue models. Deloitte chose enterprise integration expertise that transforms them from consultants to strategic technology partners. WPP chose operational efficiency. They can deliver current work faster and cheaper - but any competitor with similar tools can replicate their offering within months. Here’s what WPP’s strategy can’t solve: they remain trapped in time-based pricing models because they don’t control the underlying technology. When you’re orchestrating other people’s tools, you’re selling process management, not technological capability. That’s a consultancy play, not a transformation play. Meanwhile, agencies building proprietary technology can price on outcomes because they control the full commercial stack. WPP’s approach might optimise current operations, but it doesn’t create future competitive advantage. In three years, when AI workflow optimisation is commoditised, what differentiated capability will WPP own? https://lnkd.in/ehCYNA8E

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Learn how AI can assist you in building thought leadership within your industry by recommending you as a provider of unique insights and valuable perspectives. The video underscores the necessity of going beyond basic information to offer original analysis, predictions, and innovative solutions. Discover how your unique experiences and perspectives can help you stand out in a way that AI can't replicate.

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This, from WARC, is among the emerging body of good research that demonstrates that there are no shortcuts to LLM discoverability. Thanks Sofie Sue Rutgeerts for sharing, and Kathy Newberger for signposting.

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When #GenAI is embedded intentionally in meetings it can elevate group thinking, sharpen decisions, and unlock deeper alignment. Harvard Business Review shares how #AI can improve team meetings from Elisa Farri and Gabriele Rosani: https://lnkd.in/e6BufZxx #DigitalTransformation

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Fractional CMOs are changing the marketing game. They offer companies access to senior strategic guidance, without the full-time headcount or cost. In fact “Fractional CMOs cost a fraction (approximately 50-75%) of the annual salary and benefits of a full-time CMO” (MOGXP). In markets like the U.S., it's become a natural part of the growth journey. But in Europe? We're still lagging behind. 🌎 United States – Leading the way. Over the past five years, adoption has grown by 60%. Startups and scaleups understand the value: flexibility, experience, and real marketing strategy from day one. (CMO Index) 🇪🇺 Europe – Still catching up. And it's costing us. I’ve spoken with several startups and scaleups recently and the pattern is worryingly consistent: they focus on aggressive outbound marketing, pushing to get sales quickly to cover costs and are very product focused. They miss a real storyline, no coherent brand strategy, no clear go-to-market vision - in short they didn’t do their homework and it shows in their lead generation. If we want our startups to scale effectively and compete globally, this mindset needs to shift. Marketing is not an optional extra, it’s the baseline for growth - and now it's available at reasonable cost. 🇦🇺 Australia – Seeing strong traction, especially among SaaS and tech firms looking for lean but expert leadership. (YorCMO) 🌏 Asia – Early-stage adoption. Multinationals and ambitious startups are experimenting with the model, but traditional full-time roles still dominate. (Geisheker) The world is moving toward on-demand leadership, and for good reason. It gives companies access to the right expertise at the right time, especially during high-stakes growth phases. Here’s the latest on how fractional CMOs are making a difference - worth the read! https://lnkd.in/gpR8-Fdu 💡 Curious how fractional marketing leadership could work for your business or why it hasn’t taken off in your sector yet? Let’s talk. #cmo #marketing #leadgeneration #brand #fractional #costeffective #startups #scaleups

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🚀 From pioneering contextual advertising to spearheading AI-driven innovation, Michael Yavonditte has consistently been ahead of the curve. One insight from his recent interview really stood out: AI should enhance, not replace, humans. Here at Yieldmo, we're building “human-in-the-loop” systems, where technology does the heavy lifting but humans remain in control of critical decisions. It’s a balanced approach that ensures transparency, creativity, and accountability while positioning Yieldmo to lead when the market is ready for full automation. https://lnkd.in/g8-zWvtA

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Year-end recaps and look-aheads are now almost identical - the same prompts, the same sources, generated by #AI. With a few exceptions. Here's one: 👽 Let me join the chorus of interest in Jon Miller's 4th "B2B Go-To-Market" Predictions - they're groovy 👽 When Scott Brinker makes an exception and circulates a guest post ... 👽 Miller is co-founder of Adobe Marketo and Engagio (acquired by Demandbase) and the best-known content marketers' marketer until ... Luma? Facts that struck me: 💥 World Uncertainty Index (a real thing) is 2X higher than 2020 and 6X higher than during the 2008 crisis 💥 16-20% decline in employment for AI-exposed positions like software devt, customer care and (eek) marketing (Stanford) 💥 81% of AI use is 'assist-only' right now Now the theses skew realistic b/c Miller "grades" his predictions each year. My favorite 3: 👉 👉 "AI will completely transform legacy SaaS martech - but not in 2026" Note that last caveat. Forecasters adore front-loading the future, projecting backward likely shifts, getting them closer to home. Faux relevance; false timelines. Miller is more measured. "Yes," he says, "AI will reshape marketing technology - but it will take the next 2-5 years." And most of this reshaping will be operatic only at the edges of the machine. Meaning that part of the 120 martech tools used by the avg. enterprise that can be coded by AI ... or (dare I say) vibe-coded by me. We're not talking abt replacing your #CRM. 👉 👉 "Composable stacks will be mainstream by 2030, but <20% will adopt in 2026" So composability is a valid topic and part of forecasts last year and the year before. Miller is obviously right when he says the martech stack - let's say the enterprise stack - is increasingly "composed" of layers: ->> Data layer - customer data ->> Decision layer - segmentation, models etc ->> Delivery layer - probably over APIs right? We should point out that "composable" is a principle and *not* a product; the goal is modularity and flexibility. Good software is all composable. But "composability" collapses when it's part of the song of "X is Dead!" ... CDPs are Dead! Marketing Clouds are Dead! ... which they're not ... and really it's just smart start-up marketing. (This is me talking not Miller or Brinker.) 👉 👉 "Journey orchestration shifts from rules to AI playlists ..." I like this metaphor: AI reasoning engines (like Agentforce) can and will increasingly pull personalization options from a hit-list of likely contenders based on all available data, like Spotify, and this list changes on the fly. This is different from rules-based 1:1 #personalization; or rather, it's the same but the rules are different. Of course you should read the article itself (link below); there's much more. Happy Marketing in 2026 ... and beyond!

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AI is now a standing agenda item. It shows up in QBRs, board packets, and 2026 budget plans with a big expectation stamp on it. CMOs are being asked to operationalize it fast, prove value in workflows, and keep risk, governance, and tool sprawl under control. To get specific about what to prioritize next, I spoke with Guy Yalif (Webflow), Andy Dé (Lightbeam Health Solutions), and Kevin Briody (DisruptedCMO). Together, they focus on how CMOs can move from scattered experiments to intentional AI adoption across people, process, and technology, and what it takes to make AI a trusted part of how marketing runs. In this episode:  🤖 Guy shares an AI fluency maturity model and explains why the shift to operational excellence is a change management challenge.  🤖 Andy breaks down agentic AI and workflow automation with examples from CI, outbound, RFPs, content, and AEO, using “why, what, how, so what.”  🤖 Kevin focuses on the people and platform side, from job anxiety and culture to vendor shakeouts and MarTech-level discipline. Plus:  + Centering AI plans on people and fluency so it feels additive, not threatening.  + Using councils, fast-track approvals, and guardrails to scale safely.  + Balancing efficiency with human experience and customer acceptance.  + Treating AI tools like core MarTech, with scrutiny around contracts, integrations, and vendor longevity. If you want your 2026 AI plan to feel like a strategic advantage instead of a collection of pilots, this conversation will help you decide what to run, what to scale, and what to skip. Listen via the link in the comments.

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Stop Using AI as a Tool. Start Using It as Your Co-Pilot. 🚀 Forget everything you thought you knew about the CMO role. This year at Cannes Lions, the message was clear: AI isn’t just a tool, it's a strategic co-pilot, and the CMO is the one who must lead this transformation. The CMO Insider Breakfast confirmed what I've been saying for years with my Lean AI philosophy: the future of marketing is about leveraging data and automation to drive efficient growth, freeing up human creativity to focus on what truly matters. As I followed the key themes resonating from those conversations, it became clearer that AI has moved from a buzzword to a business imperative. This is the Lean AI philosophy I’ve championed for years—using data and automation to do more with less, drive efficient growth, and free up human talent to focus on what truly matters. 👉 From Automation to Autonomy: The AI Maturity Curve Many marketers started their AI journey with simple automation: think chatbots for customer service or automated A/B testing. This is a crucial first step, but the real value lies in moving up the AI maturity curve. The leaders at Cannes are already embracing a more autonomous approach. They're using AI to: -Orchestrate complex, cross-channel campaigns -Dynamically allocate budgets in real-time -Personalize user journeys at scale This isn’t just about speeding up tasks; it’s about making marketing smarter. It’s about leveraging machine learning to uncover insights and take actions that a human team, no matter how skilled, couldn't do at the same speed or scale. 👉 The New CMO: Part Technologist, Part Storyteller This shift doesn’t diminish the role of the CMO; it elevates it. The new CMO must be a hybrid—part technologist, part creative strategist. We must understand the capabilities of these new tools while retaining our core focus on brand, emotion, and storytelling. AI can handle the data-crunching and optimization, but it's up to us to define the brand narrative and ensure emotional resonance. The future growth team will be leaner and more focused on interpreting AI's insights to make high-level, strategic decisions, not number-crunching. The consensus at Cannes was clear: the winning strategy is a human-machine partnership. We need to see AI as a co-pilot, not a replacement. By embracing this mindset, marketers can not only survive the age of AI but thrive in it, building more efficient, more personalized, and ultimately, more human-centric marketing. This is the new era of marketing, and it’s a journey we’re just beginning. Read more: https://lnkd.in/gKKqrEyN #CustomerLoyalty #LoyaltyPenalty #Innovation #Marketing #FutureOfBusiness #CMO #Startups #Branding Erica Iacono Business Insider

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Large enterprise CMOs are facing a critical challenge: Drive AI transformation while doing right by the teams that built your organization. The C-suite wants AI transformation yesterday. Their teams—many with decades of institutional knowledge—are skeptical, exhausted, or both. Here's what I keep hearing: "I know we need to move fast. But I can't just blow up my team in the process." These leaders aren't stuck because they don't understand AI. They're stuck because they understand people. They need a plan for that first and foremost when the org gets to a certain size. They know that legacy expertise is still valuable and long-tenured employees deserve honesty about what's coming, not false promises. Transformation that breaks trust isn't really transformation—it's just chaos with better tech. This is the real leadership challenge of AI transformation - navigating the human complexity of change in organizations where relationships, tenure, and culture run deep.

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The race for AI advantage isn't just about models anymore. It's about agents. We're seeing a clear pivot: enterprises are moving beyond generic AI to highly specialized, self-learning agents. This shift, exemplified by recent acquisitions like CoreWeave and OpenPipe, underscores the critical role of reinforcement learning in achieving true performance on complex reasoning tasks. It's about tailoring AI to 𝘺𝘰𝘶𝘳 specific operational needs, not just adopting off-the-shelf solutions. This evolution demands a new level of engineering clarity and system design. Building trust into these autonomous systems isn't an afterthought; it's foundational. At Kombee, we recognize that unlocking the power of data for these advanced agents requires robust, scalable architectures designed for both innovation and reliability. This transition brings distinct challenges: 𝘔𝘰𝘷𝘪𝘯𝘨 𝘧𝘳𝘰𝘮 𝘣𝘳𝘰𝘢𝘥 𝘈𝘐 𝘤𝘢𝘱𝘢𝘣𝘪𝘭𝘪𝘵𝘪𝘦𝘴 𝘵𝘰 𝘱𝘳𝘦𝘤𝘪𝘴𝘦, 𝘢𝘨𝘦𝘯𝘵𝘪𝘤 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦. Ensuring data integrity and ethical guardrails in self-learning systems. • Scaling computational demands without compromising efficiency or trust. How are you approaching the architectural and ethical considerations of deploying truly intelligent, customized AI agents within your enterprise? #CTOInsights · #TechLeadership · #AIAgents · #DigitalTransformation · #KombeeTech

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The search landscape just shifted beneath us—and most brands aren't ready. New McKinsey data reveals that 50% of consumers now intentionally use AI-powered search to make buying decisions, with $750 billion in US revenue set to flow through these channels by 2028. Yet only 16% of brands systematically track AI search performance. Here's what keeps me up at night: Traditional brand strength is no longer a predictor of visibility. Market leaders are showing 20-50% lower share of voice in AI-powered search versus traditional SEO. Some category leaders are completely absent from AI Overview results. The fundamental issue? SEO focused on owned content. But AI-powered search pulls from a radically different mix—only 5-10% comes from brand sites. The rest? Publisher content, user-generated reviews, affiliate sites, and academic sources that vary by LLM, category, and question type. The winners will be those who move beyond SEO to Gen AI Engine Optimization (GEO)—rethinking content strategy, understanding the diverse sources shaping AI answers, and optimizing for LLM consumption across the entire consumer decision journey. This isn't incremental change. It's a fundamental restructuring of how consumers discover, evaluate, and choose brands. The question isn't whether to invest in GEO capability—it's whether you can afford to be six months behind. What's your organization's activation plan? https://mck.co/4hE7sNU

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Here's a great example of AI-first adtech creating real business value for media companies. Aperiam portco Gray Swan is partnering with Operative to bring AI-powered observability to media companies managing converged linear, streaming, and digital advertising operations. GraySwan's agentic AI layer continuously monitors performance signals across supply, demand, pricing, and delivery. It automatically surfaces anomalies, inventory and pricing optimizations, and incremental revenue opportunities in real time. No more hours spent pulling reports or missing critical signals. As Zeev Neumeier, GraySwan's Founder and CEO, put it: media is now a data-driven business, and the power comes from turning that data into action. Proud to support the team GraySwan as they bring this vision to the world's leading media brands.

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Billions are spent on creative work every year. Yet most brands struggle to connect specific creative choices—like visuals, language, or emotional tone—to measurable business outcomes. We’ve been working on that problem. We can now map how elements like facial expressions, color, tone, and cultural signals shape real business outcomes. And our work focuses on helping brands connect those creative details to results they can actually measure. Because great creative deserves the same clarity and evidence as any business decision. I’ve shared more in my latest piece: https://lnkd.in/g-PcJ8Jw #CreativeEconomy #DigitalistHub #MarketingROI #BrandPerformance #BrandStrategy #ShortyAwards CC: NEC X Inc. Shorty Awards holMedia VoxQI - Qualitative Intelligence

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After reading five articles on the Omnicom–IPG restructuring, I still can’t keep the new, overlapping Omni-clature straight. But the agencies that were sunset or merged? Those names I remember. They mattered in a way that a corporate "Branded House" naming architecture never will.

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During Marlabs recent “2026 State of AI in Enterprise” fireside chat, our esteemed panelists shared real-world insights outlining the strategic roadmap from AI ambition to successful adoption. Thank you again to panelists Teoman Buyan, Anand Rao and Brian Rowe for sharing their insights and predictions.

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