What Happens When AI Learns "Best Practices"
AI learns from data. From texts, images, patterns. It learns what worked. What performed well. What counts as "best practice."
That is its strength. But also its limitation.
AI can replicate. It can optimize. It can vary.
But it cannot create something truly new. Something that did not exist before.
When all B2B companies use the same AI tools to create content, something predictable happens: the output converges. Everyone writes about "innovation." Everyone promises "transformation." Everyone positions themselves as a "leading provider."
The Harvard/BCG study shows this measurably: 40% less creative diversity.² Not because the tools are bad. But because they are based on the same training data. Because they have learned the same patterns.
The problem intensifies with every company that adopts AI. Homogenization emerges. Everyone sounds similar. Everyone looks similar. Everyone promises similar things.
In a market where everyone says the same thing, the winner is not the one with the best content. It is the one with the clearest identity.
What AI Cannot Do – and Why That Becomes Decisive
AI can write texts. Generate designs. Automate processes. McKinsey estimates: by 2030, 30% of working hours could be automated.³
But there is something AI cannot do: develop values.
It cannot have a point of view. It cannot decide what a company stands for. It cannot define what makes a brand unique.
AI is an amplifier. It amplifies what is already there. If a brand is unclear, it amplifies unclarity. If a brand is clear, it amplifies clarity.
That is the rule: without a clear foundation, AI becomes a problem. With a clear foundation, it becomes an accelerator.
Lauren Shufran, content strategist, puts it this way: "AI will get better at voice, but it will never develop values. The companies that win will be the ones who knew what they believed before they ever touched AI."⁵
That is exactly the point. The question is not: how well are we using AI? The question is: do we know who we are?
What Brand Identity Really Means in B2B
Brand identity is not the logo. Not the colors. Not the tagline.
Brand identity is the foundation on which everything else is built. Three questions define this foundation:
1. What do we stand for?
This is not the "what" (what do we sell), but the "why" (why do we exist). It is the perspective through which a company views its market. The filter through which decisions are made.
Slack stands for: "Work should be pleasant." Not just productive. Pleasant. That is a point of view. It shows in the language (humor instead of corporate speak), in the design (playful instead of sterile), in the features (emojis, GIFs, integration instead of isolation).
This point of view cannot be developed by AI.
2. What makes us different?
Not: what do we do better. But: what do we do differently.
Ahrefs could have positioned itself as a "better SEO tool." Instead, they position themselves through original research. They publish data no one else has. They reveal insights not available elsewhere.
This expertise is not created by AI. It emerges from years of work, proprietary data, specific knowledge.
3. Who are we for?
Mailchimp deliberately targets small business, not enterprise. They want to make marketing "easier," not "powerful." This decision consciously excludes. And that is precisely what makes it strong.
This foundation forms the basis for everything visible:
- How do we speak? (Brand Voice)
- How do we look? (Visual Identity)
- How do we feel? (Brand Experience)
Mailchimp speaks differently than HubSpot. HubSpot speaks differently than Salesforce. Not because they have different target audiences. But because they have different identities.
This identity cannot be invented by AI. But AI can make it inconsistent if it is not clearly defined.
What This Concretely Means: Strategic Judgment in the AI Era
The challenge is not using AI. The challenge is knowing which of what AI produces actually fits the brand.
20 AI-generated variations of a text. Which one is right?
This is not a matter of taste. It is a strategic question. It requires a combination of strategic judgment and a feel for language and design.
In many B2B companies, this clarity is missing. Five people on the team describe the brand differently. There is no common language. No clear guidelines. No defined decision criteria.
In this environment, AI becomes a problem. It produces a lot. But what fits? What is "on-brand"? Without a clear answer, content becomes arbitrary.
That is why some companies succeed with AI – and others do not. Not because some have better tools. But because they know what they stand for.
What B2B Can Learn from Successful Brands
Successful B2B brands have something in common: they do not just produce more content. They produce consistent content.
Consistency does not come from AI. Consistency comes from clarity.
Slack uses humor. Not because it is trendy. But because it fits their mission: "Make work life more pleasant." Every post, every email, every help article reflects this.
Mailchimp is playful. The chimp mascot, the soft colors (pink, yellow, green), the accessible language. Everything pays into the same identity. They target small business, not enterprise. They want to make marketing "easier," not "powerful." That is a conscious decision.
Ahrefs focuses on substance. Original research, detailed analyses, deep insights. Their content strategy is based on proprietary data. No one can copy that. Not even with AI.
What unites these brands: they knew who they were before they scaled. AI now helps them scale that identity. But it did not create it.
The 60/40 Rule: Why Long-Term Brand Building Pays Off
The LinkedIn B2B Institute, together with Les Binet and Peter Field, researched what makes B2B brands grow. The result: long-term brand building beats short-term tactics.⁴
The most successful companies invest 60% in long-term brand building, 40% in short-term sales activation.⁴
Why does this work?
Brand creates trust. Trust shortens sales cycles. In complex B2B buying decisions with multiple stakeholders, trust is the decisive factor. Not features. Not price. Trust.
When two providers are technically comparable, the one the buyer group trusts wins. And trust does not come from campaigns. It comes from consistency over time.
That is why short-term AI-accelerated content production alone is not enough. It can create reach. It can generate attention. But trust? Trust requires substance. And substance requires time.
The Window of Opportunity – Why Now Is the Right Time
AI has enabled democratization. Small teams can now produce output that previously required large agencies. That is an opportunity.
But it is also a turning point. Because the moment everyone has access to the same tools, competition shifts. Away from "Who has the resources?" Toward "Who has the clarity?"
There is a window of opportunity. Right now. In the next 12-24 months, it will be decided which B2B brands remain differentiated – and which become interchangeable.
Those who invest in brand identity now have an advantage. This work takes time, external perspective and a systematic approach. But it is the investment that pays off.
Those who wait will have a harder time. Because the more companies produce generic AI content, the more valuable differentiation becomes.
This is not esoteric. It is business.
What to Do Now
Three steps:
First: Answer the three questions. What do we stand for? What makes us different? Who are we for? Not superficially. But with depth. With consistency. With clarity.
Second: Create collective clarity. Five people on the team should be able to describe the brand the same way. If that does not work, there is no shared understanding. Everyone produces different content. Everyone writes different AI prompts. The result is not a brand, it is randomness.
Third: Define forms of expression. How do we speak? How do we look? What visual language fits? What typography? What tone? These are not matters of taste. They need clear criteria: what is on-brand? What is not? These guidelines make AI an amplifier – for language AND design.
This is not a quick exercise. It requires strategic thinking, creative consistency and systematic implementation. But it is the work that makes the difference.
Conclusion: The Uncomfortable Truth About AI in B2B Marketing
AI makes everyone faster. But speed is not a strategy.
The uncomfortable truth is: many B2B companies do not have a clear brand identity. For years, that was fine. Features and price were enough. Not anymore.
AI amplifies what is already there. If the foundation is unclear, the output is unclear. If the foundation is clear, the output is clear.
The decisive question is not: how do we use AI better?
The decisive question is: do we know what we stand for?
B2B buyers are people. They do not make decisions purely rationally. They make them based on trust. And trust does not come from features. It comes from brand.
Those who act now have an advantage. Those who wait risk becoming one of many.
The question is no longer whether, but when.
Sources
¹ ON24 (2024): The State of AI in B2B Marketing. Survey of 500+ B2B marketers
² Dell'Acqua, F., McFowland III, E., Mollick, E., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2023): Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality – Harvard Business School Working Paper No. 24-013 / Boston Consulting Group
³ McKinsey (2024): The State of AI in 2024: GenAI adoption spikes and starts to generate value
⁴ LinkedIn B2B Institute / Binet, L. & Field, P.: The 5 Principles of Growth in B2B Marketing - Research on balancing brand building and sales activation
⁵ Shufran, L. (2025): LinkedIn Post on AI and brand values
