Brand Strategy & Design
by OneZeroEight
Sept 15, 2026
4 mins read
AI is giving B2B companies more capability than ever. Oddly, it is also making many of them harder to tell apart. As AI becomes common across enterprise products and services, B2B brand positioning has to work harder than simply proving that the technology exists.
Open a few B2B technology websites and a familiar vocabulary starts appearing: AI-powered. Intelligent. Agentic. Automated. Enterprise-grade. Built for the future.
None of these claims is necessarily wrong. That's what makes the problem interesting.
Many of these businesses have genuinely strong technology. Yet when everyone describes that technology through the same handful of ideas, real product differences start getting flattened by familiar language.
AI isn't making B2B products identical. It is making generic descriptions of those products easier to produce and easier to copy.
That sounds contradictory. It isn't.
McKinsey's 2025 global survey found that 88% of respondents said their organisations were using AI in at least one business function, up from 72% in 2024 and 55% in 2023.
The money is moving just as quickly. Menlo Ventures estimates enterprise generative AI spending grew from $11.5 billion in 2024 to $37 billion in 2025, with $19 billion going to AI applications.
So AI clearly matters.
But widespread adoption changes what the label communicates. When relatively few companies could credibly say they used AI, the claim itself created interest. When nearly every software category can make that claim, it starts behaving more like table stakes.
There is a difference between having differentiated AI capability and simply calling a company AI-powered.
AI is becoming more commercially important at exactly the same time that saying “we use AI” is becoming less commercially distinctive.
For B2B companies, this isn't merely a copywriting issue.
6sense studied nearly 4,000 B2B buyers in 2025 and found that 95% of winning vendors were already on the buyer's Day One shortlist. Buyers had also ranked their shortlisted vendors before speaking to sellers in 94% of cases.
In plain language: much of the competitive battle happens before sales gets a chance to explain why one company is different.
Now AI is stepping into that early research process too.
G2's 2026 research of more than 1,000 B2B software buyers found that 51% start software research with an AI chatbot more often than Google, while 71% use AI chatbots somewhere during research.
That creates a new wrinkle for B2B brand positioning.
A company now needs to be clear enough for a person to understand and distinct enough for an AI system to describe accurately when someone asks, “Which vendors should I consider, and what makes them different?”
Generic language doesn't give either audience much to work with.
The instinctive response is often to say more.
Add the models. Add the agents. Add the integrations. Add the industries. Add every technical capability the company has accumulated.
Soon the proposition reads like a product backlog.
Yet buyers are becoming more demanding about proof, not less. G2 found that 40% of software buyers now consider evaluation the longest stage of the buying journey. It also found that 87% were more likely to buy from a vendor offering transparent AI than from a cheaper black-box alternative.
The signal here is useful.
Buyers still care about AI. But once AI gets a company into the conversation, harder questions begin: What does it actually change? Why is this approach credible? What risk does it remove? Where is the proof?
Harvey offers a telling example. It is unmistakably an AI business, yet its homepage currently leads with “Build a Frontier Legal Organization”, then grounds the proposition in high-stakes legal work.
The technology remains central, but the business context carries the position.
AI explains the mechanism. The market position explains the meaning.
B2B companies rarely suffer from having too little to say.
More often, they have too much.
A growing technology business may have several products, multiple services, strong engineering capability, years of experience, proprietary systems, sector expertise and a long list of integrations. Internally, all of it feels important.
Externally, that can become noise.
When every capability receives equal weight, nothing creates a clear memory.
This is where positioning becomes less about writing a clever line and more about deciding
what deserves to lead.
What problem does the company understand better than most?
Which audience does it know deeply?
What business outcome does it consistently create?
What capability is genuinely difficult to replicate?
What does the company believe about its category that shapes the way it works?
Those questions sit underneath the messaging.
Without that layer, even polished communication tends to drift back towards category language.
Our approach to B2B positioning starts outside the company.
Before deciding what a brand should say, we look at what the category already says.
Which claims appear everywhere? Which terms have become basic expectations? What are competitors using as proof? What does the market already understand, and where is everyone repeating one another?
That context matters because a statement can sound strong inside a meeting room and still disappear the moment it is placed beside ten competitors.
The next step is separating capability from relevance.
A company may be proud of its technical architecture, product breadth or delivery model. Those can be real strengths. But the strongest internal capability is not always the strongest market position.
The useful territory usually sits where three things meet:
what the business can genuinely prove, what the buyer values and what the category does not already own collectively.
From there, the idea has to travel.
It needs to remain clear across the website, identity, product experience, sales communication and marketing. Otherwise positioning becomes a line in a strategy deck while the market encounters something far more generic.
This is why we see positioning as a business decision before we see it as a communication decision.
AI will make producing competent websites, campaigns and messaging easier. That is good news for execution.
It also means competent communication will become more abundant.
The scarce part moves upstream: deciding what deserves to be said in the first place.
AI can generate a hundred polished ways to describe an enterprise platform. If the underlying position is generic, it simply produces better-written sameness.
And this is where the next competitive shift may happen.
As technology becomes easier to access and communication becomes easier to produce, businesses will need stronger reasons to be remembered.
Not louder claims. Clearer meaning.
Capability creates substance. Positioning makes that substance legible.
AI can help express that position.
It cannot create one where none exists.
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