I read a lot of studies. But the new McKinsey State of Marketing study really caught my attention. For the second year in a row, CMOs have ranked branding as their top priority. AI, on the other hand, plays a surprisingly minor role on their list of priorities, ranking only 17th. 72 percent of the decision-makers surveyed plan to increase their marketing budget, while 94 percent have not made significant progress with AI. This is a symptom of an industry that has been shaken up by the AI transformation but has not yet figured out its strategic response to it.
The study provides an excellent, comprehensive overview of marketing across all industries. It does not claim to be specific to B2B. That is precisely why it is so valuable. When viewed through the lens of a B2B marketer who has worked for years with German SMEs and technology companies, patterns emerge that are often overlooked in the general discussion.
This article is my take on the results—an analysis from a B2B perspective.
The overall finding (McKinsey): The study is clear in its diagnosis. The stagnation in AI is not due to a lack of will, but to two specific bottlenecks: a lack of technical skills within teams and—even more importantly—the absence of a clear, overarching AI strategy. Companies sense that they need to do something and respond with the most obvious reflex: more budget.
My take on B2B: In my view, the root of the problem runs deeper. Many AI tools are designed for scaling and process optimization. In B2B marketing, however—especially when it comes to complex capital goods—that’s often not the real challenge. It’s not about producing as much content as possible. It’s about using the right content to the right time to win the trust of a handful of highly specialized decision-makers.
At critical moments, B2B marketing isn’t linearly scalable. It’s a relationship-driven business based on expertise and trust. Anyone who tries to fix a non-process-oriented business with pure process optimization tools is investing in a solution to part of the problem, but not in the core issue. That, precisely, could be the real problem facing many companies.
The general finding (McKinsey): Issues such as branding, data protection, and authenticity are high on CMOs’ agendas. This is the logical response to a world flooded with generic, often flawed AI-generated content. When anyone can produce anything, a recognizable brand that stands for genuine expertise and trust becomes a decisive competitive advantage.
My take on B2B: In a B2B context, this finding takes on even greater significance. Here, “branding” is the answer to the question: “Who is the leading expert for my specific, highly complex problem?” In a world of information overload, a strong, expertise-based brand becomes the most important filter for buyers and technical decision-makers. Prioritizing branding is therefore absolutely correct from a B2B perspective, but implementation is another matter. It involves systematically building demonstrable authority through professional articles, studies, and conference presentations.
The general finding (McKinsey): The 6% that achieve measurable competitive advantages have a clear strategy and the right skills within their team.
My take on B2B: Applied to the B2B sector, this means: These companies do not use AI to replace their experts, but to give them more time. They use AI to analyze market data, draft initial versions of technical articles, or prepare presentations. However, the strategic decision-making, the depth of content, and the final quality control remain in the hands of the people who truly understand the business, the technology, and the customers.
AI is becoming a tool that enhances human expertise rather than simulating it. The key is not the automation of content, but freeing up time for strategic priorities. An expert who uses AI to optimize and refine a marketing asset or a white paper makes a more significant contribution than AI automation that generates 20 mediocre blog posts in the same amount of time.
The McKinsey study is a wake-up call. It shows that more budget and more tools aren’t the answer when there’s no strategy. For B2B marketers, the message is even clearer: The key question for 2026 isn’t “How can I use AI to produce more content?” It is “How can I use AI to produce the best and most relevant content that solves complex problems, builds trust, and supports strategic decisions?”
Those who invest their budget in addressing this question—in AI-powered human expertise and a clear strategy—create the conditions necessary to become one of the few true AI pioneers. The rest focus on optimizing processes that, on their own, are not decisive in B2B marketing.
Why is AI scaling less important in B2B marketing than in B2C?
In B2B marketing, especially when it comes to complex capital goods, trust and expertise matter more than sheer frequency. A single, highly relevant expert article can have a greater impact than hundreds of social media posts. The bottleneck isn’t the volume of content, but rather strategic depth and human connection.
According to McKinsey, what are the main reasons for the stagnation of AI in marketing?
The study cites two main reasons: a lack of technical expertise within the teams and—even more importantly—the absence of a clear, overarching AI strategy. Many companies purchase tools without knowing exactly what problem they are trying to solve.
How can a mid-sized B2B company make effective use of AI?
The best approach is to view AI as a tool to support experts, not as a replacement for them. Useful applications include researching market data, drafting initial text, or analyzing campaign performance. Strategic oversight and final quality control must remain in the hands of human experts.
Stefan is co-founder of EPOS and has been involved in B2B marketing and communications for more than 20 years.
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