FOMO: AI Marketing in 2025
FOMO: Salaries through the roof. Ruthless poaching. Money flooding in and out of tech.
Look, AI has been in the background for a number of years. In my opinion, it’s gone ballistic this past year mainly because of FOMO; the race to be first, the poaching wars, the insane salaries, and the flood of investment. And that’s just the tech companies. Add in the “supporting cast” — operations, sales, marketing — and most organizations are beyond perplexed. Do we dive in? How much do we spend? Does anyone even know how to use this stuff?
From a marketing perspective, I talk to folks who are way ahead of the curve in building and experimenting with AI agents, but even they are still testing outcomes. Meanwhile, agencies promise the impossible in daily social posts. That’s why I want to use this blog to cut through it — to talk about what’s real, and what’s only promised.
AI doesn’t think. It doesn’t strategize. It predicts.
Large language models and AI search systems are essentially giant calculators. They pull from vast databases of text and data to predict the most likely next word or answer. That makes them powerful tools, but not replacements for human strategy.
Why October 2025 Matters
The hype tells a different story. Marketers are being told they can “own” AI search results or dominate the space the way SEO once promised top spots in Google. Investment is soaring: the global AI marketing market is projected to hit $47.3 billion in 2025 [1]. Executives want clarity, and agencies are rushing to sell it. But much of what’s being sold is noise.
The reality?
Only 1% of enterprises consider their AI efforts mature, with median ROI stuck under 6% [6].
95% of generative AI pilots fail to produce measurable business impact [5].
80% collapse because teams chase tools without framing the right problem [5].
Executives are pouring money into AI projects — but most of it ends up in “pilot purgatory.”
The Hype: The Illusion of AI Dominance
If you’ve scrolled LinkedIn lately, you’ve seen the pitch: “We’ll make your brand the default answer in AI search.” It’s a compelling story — but it isn’t how these systems work.
There is no #1 slot in generative AI. Platforms like Google’s Search Generative Experience (SGE), ChatGPT, and Perplexity don’t rank results in a neat list. They synthesize answers by pulling from clusters of authoritative, consistent sources. The louder claims — that someone can guarantee AI dominance — are more sales pitch than strategy [2].
The Reality: What’s Really Driving AI Search
AI systems don’t “rank” like Google search. They assemble patterns. That means clarity, authority, and consistency matter more than keyword tricks.
As of March 2025, about 13% of queries trigger AI overviews, and nearly 88% of those are informational [2].
Deloitte reports that 60% of marketing leaders experimented with AI this year, but only 29% are confident they can use it to drive outcomes [3].
Translation: AI shows up most often when people want background knowledge — not when they’re ready to buy. Yet budgets are being sunk into “AI optimization” with little clarity on ROI.
Meta’s Walled Garden Advantage
Some platforms do deliver results better than others. Meta’s AI-powered ads look almost magical at times. Why? Because Meta owns something few others do: a closed-loop dataset of billions of behavioral signals. Every click, like, purchase, and comment across Facebook, Instagram, and WhatsApp feeds the machine.
That makes Meta’s AI powerful. But let’s be clear: this isn’t strategy. It’s optimization inside a walled garden. And if you feed bad creative, bad positioning, or bad audience assumptions into Meta’s system, it will happily amplify that noise at scale [2].
What Actually Matters
When you strip away the hype, the same fundamentals remain.
Depth and clarity of content. AI systems surface authoritative insights, not shallow listicles.
Consistency. Repetition of themes builds an entity signal AI can recognize.
Metadata and schema. Technical hygiene (titles, schema, descriptions) still matters.
Backlinks and mentions. External validation reinforces authority.
Budget discipline. Marketing budgets remain flat at ~7.7% of company revenue [4]. Leaders don’t have the luxury of chasing hype.
The Grey Areas
AI search is still evolving. Unsettled dynamics remain:
Zero-click risks. AI overviews sometimes reduce traffic to source sites [2].
Lack of standards. Schema and transparency vary widely between Google, Perplexity, and ChatGPT.
Governance gaps. Deloitte notes benefits rise when trust is built, but bias and risk remain under-managed [3].
Shifting expectations. Consumers using AI assistants will continue to demand speed, personalization, and credibility.
Executive Checklist: How to Pressure-Test Your AI Strategy
Before you invest more AI dollars, ask your team:
Is every AI project tied to a P&L lever? Lower CAC, improve retention, accelerate pipeline - not “more content.”
Do we have clean, integrated data? AI will absolutely amplify noise when CRMs and martech are fragmented. In my view, this may be the single biggest issue facing organizations today.
For years, I have witnessed companies treating data governance like a hot potato; bouncing ownership between marketing, sales, IT, and CX. The result is duct-taped systems and dirty databases. Now, as AI adoption accelerates, those cracks won’t stay hidden. They’ll only get louder. Fast.
Is our message clear and defensible? Weak narratives don’t get stronger when scaled.
Are we tracking real impact? Revenue, not vanity metrics.
Do we have oversight in place? Guardrails, reviews, and accountability.
If the answer to any of these is “no,” you’re betting on luck … not leverage.
Who Leaders Should Turn To
The hardest part isn’t knowing the checklist. It’s knowing what to do with it. Most executives don’t need another AI vendor pitch. They need someone to pressure-test strategy, frame the right questions, and separate signal from noise.
There are capable partners out there, but it’s not always easy to tell who’s adding real value and who’s just promising the moon. That’s where an outside perspective matters.
At CLINTONSCOTT, we don’t sell AI tools or bolt on the latest trend. We work with leadership teams to:
Align marketing with business outcomes: ensuring every AI experiment connects to real P&L levers.
Cut through vendor noise: helping you see which tools add value and which waste dollars.
Translate complexity into clarity: building narratives and structures AI can actually amplify.
Partner across teams: bringing marketing, sales, and tech together so AI investments don’t stall in silos.
The right partner doesn’t promise “AI dominance.” They ensure your business is disciplined enough to use AI as leverage, not distraction.
The Strategic Truth
AI will not save broken strategy. It will not replace positioning.
What it will do is magnify:
Clarity or confusion
Signal or noise
Focus or fragmentation
The leaders who act on this difference will cut through the hype, protect their P&L, and own the signal in a noisy market.
For a deeper dive check out our full Perspective: The Real Shift in Marketing: Adapting Strategy for the AI Era
Sources
[1] SEO.com. “AI Marketing Statistics 2025.” https://www.seo.com/ai/marketing-statistics/
[2] Semrush. “AI Overviews Study.” https://www.semrush.com/blog/semrush-ai-overviews-study/
[3] Deloitte. “Six out of Ten Marketing Leaders Used AI in Their Activities.” https://cmosurvey.org/media-articles/deloitte-study-six-out-of-ten-marketing-leaders-used-artificial-intelligence-ai-in-their-activities-over-the-last-year/
[4] CMSWire. “Flat Budgets, Rising Demands: The CMO’s AI Balancing Act.” https://www.cmswire.com/digital-marketing/flat-budgets-rising-demands-the-cmos-ai-balancing-act/
[5] Amra & Elma. “Marketing AI Implementation Failure Statistics.” https://www.amraandelma.com/marketing-ai-implementation-failure-statistics/
[6] Roithm. “Successful AI Implementation in Marketing.” https://www.roithm.com/successful-ai-implementation-in-marketing-your-2025-roadmap-from-pilot-to-profit/
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