The legacy vendor AI repositioning problem
There is a particular kind of pressure that doesn't get talked about in deep tech marketing conversations, because the companies feeling it most acutely are the ones least likely to admit it publicly.
They've been in market for twenty, thirty years. They have real customers, real revenue, and a reputation earned the hard way across generations of product cycles. And somewhere in the last two years, the conversation shifted. The buyers they've been selling to are now asking a different set of questions. The competitors they've spent years outmaneuvering have repositioned as AI companies. The analysts who used to write about them in predictable ways are starting to frame the category differently.
The problem isn't that these companies don't have an AI story. Most of them do. But like everyone else who stamped AI on their product, it sounds like everyone else's.
There's a version of AI repositioning that almost every legacy vendor defaults to. They take the existing product description, add the words 'AI-powered' or 'AI-enabled', update the website headline, and brief the PR team to find an AI angle for the next product launch. It ticks the box. It does not move the market. I’ll admit I’ve been asked ‘Can you make this more AI-washed?’ and the best answer in my experience tends to be ‘no’.
The reason it doesn't work is that technically sophisticated buyers; the CTOs and architects and procurement leads at the OEMs and hyperscalers and enterprise customers that these companies are trying to reach have seen this exact skulduggery from fifteen different vendors in the past eighteen months. They know what it looks like, they have a filter for it and when your repositioning looks like wallpaper, you don't just fail to gain credibility — you actively lose it, because the attempt signals that you don't have a story worth telling.
What Arm went through is a useful reference point. The business had built its position over three decades on a clear, defensible model: IP licensing to chip designers who built the hardware that everyone else then built on top of. That model was well understood. The relationships built around it were real and deep. And then the AI infrastructure buildout created a moment where the architecture question — what compute is the world's most demanding AI workloads going to run on — was genuinely up for grabs.
The challenge wasn't technical. Arm's position in AI infrastructure was already strong. NVIDIA runs on Arm. AWS, Google, Microsoft, and Meta were all building custom silicon on Arm Neoverse. The trajectory was there, but the challenge was commercial: how do you reposition as a company at the center of the AI infrastructure story without disrupting the licensing relationships that built the business, and without making claims that your ecosystem of partners will immediately fact-check and find wanting?
The answer wasn't a campaign. The proof points that were specific, verifiable and credible to a technical audience. The broader narrative came second, built around those proof points rather than built in advance of them. And the message was calibrated differently for each audience: for the investor, the story was about where AI compute was concentrating and why Arm's architecture was structurally advantaged; for the OEM and the chip designer, the story was about what specifically had changed in the tools, the ecosystem, and the programme support available to them.
That sequencing, with proof before narrative, and different narrative for each seat is what most legacy vendor AI repositioning gets wrong. The instinct is to announce the position before the proof is assembled, because the competitive pressure feels urgent and the board wants to see something in market. The result is a claim without substance reaching the exact audience most skilled at identifying claims without substance.
The other failure mode is narrowing too early. Legacy vendors often try to claim AI relevance in the specific product category they already occupy, because that's the safest ground. What they miss is that the more interesting and defensible AI story is often structural — about where they sit in the supply chain, what they enable that nothing else can, and why the AI transition makes that position more valuable rather than less. That's a harder argument to make, but it's the one that lands with the buyers and investors who are trying to understand what the next five years look like.
The companies getting this right are the ones who've accepted that AI repositioning is not a marketing exercise. It's a commercial strategy question that marketing then has to express. The sequence is: understand where you actually sit in the AI value chain, build the proof that substantiates that position, then build the narrative. In that order. Reversed, it produces exactly the kind of repositioning the market has learned to ignore.
Dale Kaszycki is a Co-Founder of Latent