I read many studies. But the new McKinsey State of Marketing study really made me sit up and take notice. For the second time in a row, CMOs prioritize branding at number 1. AI, on the other hand, plays only a surprisingly small role on their priority list and only lands at number 17. 72 percent of the surveyed decision-makers plan to increase their marketing budget, while 94 percent have not made significant AI progress. This is a symptom of an industry that has been shaken up by the AI transformation but has not yet sorted out its strategic response to it.
The study is an excellent, holistic inventory of marketing across all industries. It does not claim to be B2B-specific. That is exactly why it is so valuable. Because when you read it through the lens of a B2B marketer who has worked for years in the German SME sector and for technology companies, patterns become visible that get lost in the general discussion.
This article is my commentary on the results – an assessment from a B2B perspective.
The general finding (McKinsey): The study is clear in its diagnosis. The stagnation on the topic of AI is not due to a lack of will, but to two specific bottlenecks: missing technical skills in the teams and – more importantly – the lack of a clear, overarching AI strategy. Companies sense that they need to do something and react with the most obvious reflex: more budget.
My B2B interpretation: From my perspective, the root of the problem lies deeper. Many AI tools are designed for scaling and process optimization. In B2B marketing, especially with complex capital goods, this is often not the real challenge. It's not about producing as much content as possible. It's about winning the trust of a handful of highly specialized decision-makers with the right content at the right time.
In the decisive moments, B2B marketing is not linearly scalable. It is a relationship business based on competence and trust. Those who try to cure a non-process-oriented business with pure process optimization tools are investing in solving part of the problem, but not the core. This could be the actual problem for many companies.
The general finding (McKinsey): Topics such as branding, data protection, and authenticity rank 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, the recognizable brand that stands for genuine expertise and trust becomes the decisive competitive advantage.
My B2B interpretation: In the B2B context, this finding takes on an even sharper meaning. "Branding" here 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 the implementation is different. It is about systematically building demonstrable authority through technical articles, studies, and conference contributions.
The general finding (McKinsey): The 6% who achieve measurable competitive advantages have a clear strategy and the appropriate skills in their team.
My B2B interpretation: Übertragen auf das B2B-Geschäft bedeutet das: Diese Unternehmen nutzen KI nicht, um ihre Experten zu ersetzen, sondern um ihnen mehr Zeit zu geben. Sie nutzen KI, um Marktdaten zu analysieren, erste Entwürfe für Fachartikel zu erstellen oder Präsentationen vorzubereiten. Die strategische Entscheidung, die inhaltliche Tiefe und die finale Qualitätskontrolle bleiben aber bei den Menschen, die das Geschäft, die Technologie und die Kunden wirklich verstehen.
AI is becoming a tool that amplifies human competence rather than simulating it. The lever is not the automation of content, but the freeing up of time for strategic priorities. An expert who, thanks to AI, optimizes and refines a marketing asset or a technical article makes a more important contribution than an 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 are not the answer when strategy is lacking. For B2B marketers, the message is even clearer: The decisive question for 2026 is not: “How can I produce more content with AI?“ 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 answering this question – in AI-powered, human expert skills and in a clear strategy – create the conditions to be among the few true AI pioneers. The rest optimize processes that are not decisive in B2B marketing alone.
Why is AI scaling in B2B marketing less important than in B2C?
In B2B marketing, especially for complex capital goods, trust and expertise matter more than sheer frequency. A single, highly relevant expert article can achieve more than hundreds of social media posts. The bottleneck is not the amount of content, but strategic depth and human relationships.
According to McKinsey, what are the main reasons for the AI stagnation in marketing?
The study cites two main reasons: a lack of technical skills in the teams and – more importantly – the absence of a clear, overarching AI strategy. Many companies purchase tools without knowing which problem they actually want to solve with them.
How can a mid-sized B2B company use AI effectively?
The best approach is to view AI as a tool to support experts, not as a replacement for them. Meaningful use cases include researching market data, creating initial text drafts, or analyzing campaign performance. Strategic control and final quality assurance must remain with 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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