Brand Strategy & Design
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.
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