41% of organizations are already using Gen AI in marketing. Another 41% are planning to. But 22% still can’t scale beyond pilot. Stuck in pilot is where a lot of smart teams are losing ground right now. AI isn’t a future consideration anymore. It’s the operating condition. The tension Beverley Eve describes in this video is real and I hear it across industries: do more, show results, don’t add headcount. Leveraging AI to deliver real results is a leadership imperative. Microsoft’s “Modern Marketing Guide” is the smart and practical AI resource CMOs need now. The Estée Lauder example in the guide is worth the read alone. They used AI to collapse insight discovery from days to seconds! That’s not incremental improvement. That’s a structural shift in how marketing decisions get made. The framework the guide closes with is practical and refreshingly grounded: start in 90 days, build for scale. Not a transformation manifesto. A workable path. If you’re a CMO, marketing leader, or strategist trying to move from experimentation to pipeline impact, Beverly’s walkthrough is a great starting point and the e-book is worth adding to your reading list. Recommendation? Watch Beverley’s video, then grab the full guide 📕: https://bit.ly/3OkFGvB Microsoft in Business #MicrosoftAmbassador #B2BMarketing #AIMarketing #MarketingStrategy

Most of us are building our AI stacks backward. We start with tools. That is literally the last decision, not the first. There are over 3,800 AI marketing tools available right now. 54% of CMOs still say key tools are missing from their stack. More tools did not close the gap. Because the architecture was never built. Here is how I think about it. You need to build the four layers. Strategy first. Brand positioning, ICP, growth thesis, campaign intent. If you hand this to AI before you have defined it yourself, the AI will hallucinate your strategy. That too, confidently. Voice second. Tone, narrative, messaging hierarchy, and content guardrails. Most of us skip this and wonder why everything we produce sounds the same as everyone else. Execution third. Content, personalization, paid automation, and agentic workflows. This is where most of us start. We buy execution tools before we know what we are executing. Measurement last. Attribution, business impact, revenue influence. Measuring the volume of content generated by AI is not a measurement. That is just counting. AI is delivering ROI through time efficiency for 49% of CMOs and cost efficiency for 40%. That ROI only compounds when the first three layers are solid. The stack is not the strategy. It never was. It will never be, as long as you're building brands for humans. :-) Which of these four layers is your weakest right now? [Most don't even know what this is. I can see that.] ----- #BrandStrategy #AIMarketing #CMOLeadership

Marketing's "gold rush" toward AI. Marketing departments are racing to "do AI," yet many are not sure what they're racing toward. Pilots are launched. Tools are licensed. Prompt experiments abound. Six months in, the CMO is asked what has changed — and the honest answer is that we're faster at the work we shouldn't have been doing in the first place. That's not an AI problem. It's a readiness problem. Here’s a three-point readiness approach that marketing leaders can use: how ready is our marketing function to use AI across how it makes decisions, how it operates, and what it produces? *How does the department decide? Are AI use cases mapped to the top strategic priorities, or is the team chasing efficiency without effectiveness? If this is weak, AI will accelerate the wrong work. Pause activation. Align first. *How the department works. Is the infrastructure provisioned but not adopted? Does the team have the literacy, the prompt skills, and the workflow design to operationalize AI in daily work? This is the most common gap. Tools exist. Adoption doesn't. *What the department produces. Can you control what AI puts into the market? In financial services and healthcare, AI-generated content that fails to meet FINRA 2210 or HIPAA isn't an efficiency problem. It's a regulatory incident. Governance, brand-voice guardrails, human-in-the-loop review, and audit trails must exist before scale, not after. The shape across those three helps you make informed decisions: *Strong on decisions, weak on workflow → you know what to do but can't execute it. *Strong on workflow, weak on decisions → you're doing the wrong work faster. *Weak on output control in a regulated industry → you're one piece of non-compliant content away from discrediting the entire initiative. A CMO can act on that. A CIO respects it. A CFO can fund a plan to fix it. The marketing departments that succeed with AI aren't necessarily the ones with the most tools or the largest budgets. Instead, they view AI as a comprehensive system. They honestly assess all three dimensions and prioritize fixing the weakest one first — not the easiest. #AIinMarketing #MarketingStrategy #FinancialServices #CMO #AIGovernance

The marketing funnel has shifted. AI models are synthesizing answers instead of sending traffic. If your site is not built for ingestion, you do not exist to the buyer. Here is what a modern search strategy actually requires. 1) Engineer for extractability: Make your data machine-readable. If an AI agent hits friction pulling your pricing or features, it moves to your competitor. 2) Build citation mass: Traditional links matter less than mention velocity. You need a consistent footprint where real humans talk to force the model to recognize your brand as an entity. 3) Track Share of Model Presence: Stop guessing about brand awareness. Measure how often you actually appear in AI-generated answers. Your website is no longer the final destination. It is the authoritative source of data for the tools your buyers already use. How are you handling AI visibility tracking right now? If you need to establish your baseline, there is a link in my bio to book a call. We can look at your current footprint and identify where the gap is.

One of the biggest AI mistakes marketing teams make is assuming more content automatically creates more momentum. It does not. More content without better strategic direction usually just creates more average performance. The activity increases. The dashboards get busier. The business impact stays mostly the same. AI amplifies whatever system already exists behind it. A strong campaign strategy becomes faster and more efficient. A weak strategy becomes louder and more crowded. That is why mid-year reviews matter so much. The numbers eventually expose whether AI is improving outcomes or simply increasing production volume. The brands pulling ahead right now are not just publishing more. They are learning faster from campaign data and adjusting faster than competitors. Momentum comes from optimization, not activity. Is your AI workflow helping your team learn faster or just produce faster? #AIMarketing #BulletproofMarketer #MarketingStrategy #B2BMarketing #ContentMarketing #MarketingLeadership #DataDriven

Cognitive overload, anyone?! Who else is both excited by AI's opportunities and also a bit overwhelmed? Chatting to a couple of AI experts recently, they themselves see plenty of this overload in the businesses they deal with. It's hard to keep up. The speed of AI creates pressure. It's difficult to focus. There's so much choice. These are not new challenges. The same thing happens in marketing. > Hard to keep up. > The perceived need for speed creates short term pressure but not necessarily value either in the short or long-term. > It can be hard to focus on the real priorities that will make the most difference. > There's huge choice of tools and channels! In marketing (as with AI), the starting point is to take a step back. Understand the challenge. Diagnose what's working or not and why. Agree your end point. Look at the right tools for the job. Create a plan and keep on the path. DM me if you're finding marketing overwhelming.

I'll be on a panel for the AI Marketing Summit presented by CMO Alliance. I got a sneak peak at the questions, and this one really has me thinking. "Looking ahead a few years, what do you think marketing teams will regret automating too aggressively?" My answer may change by next week, but I think we'll remove the human from the loop too quickly—our reporting, analysis, workflows, our content, our creative, our optimizations, and our decisions. We'll feel really confident that #AI can do all these things for us, at an unbelievable scale. Then we'll want it to be faster, and remove that human bottleneck. Things will work, maybe better than ever. You'll take your eye off the ball. The original human system architects leave or are deemed redundant. A change happens somewhere, sometime. Nothing breaks, it just slowly veers off course. The decisions we've empowered it to make is powered by bad data, reports, and analysis. Content, design, and experiences slowly get enshitified. Then someone steps back in, without the context or expertise, so they can't unwind what's been done. What do you think? What will we regret automating to aggressively? #AIMarketing

91% of marketing agencies now use AI. Up from 63% just one year ago. But here is the number nobody is talking about: only 34% are actually reimagining how their business works with it. The rest are plugging AI into the same old processes and expecting different results. That is not transformation. That is automation with a new label. The agencies pulling ahead in 2026 are not the ones using the most AI tools. They are the ones who rebuilt around AI as infrastructure, not as an add-on. Strategy, content, media buying, analytics. All connected. All informed by real-time data. The shift from 2025 to 2026 was not about adoption. Everyone adopted. The shift was about intention. Brands that treat AI as a foundation are seeing measurable gains in efficiency, margin, and speed to market. The ones treating it as a shortcut are seeing diminishing returns and a growing gap between their output and their competition. The question is not whether your agency uses AI. The question is whether AI is shaping how you think, not just what you produce. What does AI actually drive inside your marketing right now? Drop it in the comments. #DigitalMarketing #AIMarketing #MarketingTechnology #DigitalEstatePro #AIGrowthSolutions

There’s a stat going around that 40% of agentic AI projects will be canceled by 2027. Not because the technology doesn’t work. Because the business value isn’t clear. And governance comes too late. That tracks. In marketing, this shows up in the operating layer. What actually breaks: • No clear definition of success • Decisions aren’t defined or monitored • Ownership is unclear when things go wrong • Marketing and IT aren’t aligned on outcomes • Impact gets measured in efficiency, not revenue AI just exposes all of this faster. There’s another gap that matters more. Most marketers say AI is critical. Very few feel ready to deploy it. That’s not a skills gap. It’s a foundation gap. Data isn’t connected. Context is incomplete. Systems don’t reflect how work actually happens. So when AI gets layered on top, it doesn’t fix anything. It just moves faster on top of the same ambiguity. The teams making progress aren’t the most advanced. They’re the most deliberate about what sits underneath: Clear definitions Connected data Shared ways of working Without that, you’re not implementing AI. You’re scaling confusion. ⸻ (Based on recent Gartner and industry research on AI adoption and readiness.) #MarketingOperations #AIinMarketing #MarketingLeadership #OperatingModel