by Olgah Atellah
B2B product naming for tech company AI offerings is sparking diverse brand architecture strategies, reflecting different priorities and branding philosophies. Why does IBM rely on structured, descriptive names while OpenAI opts for simplicity and intrigue? In a competitive landscape, naming AI products is more than semantics, it is a vital part of brand architecture and market positioning. In the competitive B2B marketing landscape, a well-crafted AI brand architecture is more than naming AI products and services. It is a strategic asset which helps companies communicates the value of their AI solutions, build trust, and position themselves as leaders in AI innovation.
Will tradition prevail in B2B product naming, or will innovation and creativity redefine how B2B companies name their AI offerings?
The B2B tech space is rapidly evolving, with companies both established and emerging seeking to carve out their niche. Amid this evolution, the naming conventions of AI products play a pivotal role in shaping perception and building customer trust.
B2B companies approach naming AI products in two distinct ways: a structured, descriptive strategy exemplified by brands like IBM and Microsoft, and a more creative, evocative strategy employed by companies like OpenAI and Amazon.
IBM’s structured and reliable approach to B2B product naming for AI offerings
IBM has a history of leadership in enterprise technology. Its naming conventions reflect Gerstner’s commitment to the corporate brand, and this has caused problems by making the company look monolithic and not innovative. This was why the company finally took the decision to break out of naming everything IBM to signal innovation by calling its AI-powered cognitive computing platform “Watson.” While referencing IBM’s original founder, the Watson name is different and relevant in the AI space, while evoking the reliability and trustworthiness of the legacy brand. Watson has become a powerful portfolio AI product brand, with a clear value proposition. So, we now have “IBM Watson Studio” for AI development and “IBM Watson Assistant” for conversational AI.
IBM’s B2B product naming strategy for its AI offerings exemplifies a meticulous, structured approach. The company’s flagship AI platform, Watson, acts as the master brand, anchoring a family of solutions that span industries and use cases. It’s a cohesive brand architecture that conveys reliability and maximizes the power of the Watson brand and the efficiency of marketing spend put behind it. All of this contributes to reinforcing trust and long-term engagement.
But even IBM does not consistently follow its system. So, in addition to all the Watsons, we have IBM Cloud Pak, IBM OpenScale, IBM PowerAI, which don’t fit with the overall portfolio approach. And it creates the danger that the IBM corporate brand encountered—by calling everything Watson, it makes it more difficult to call out truly disruptive products.
Microsoft’s unbalanced B2B product naming strategy
Microsoft has a history of brand architecture spinning out of control with each division creating hosts of new and totally different names. About every 7 years, Microsoft tidies it up, then it quickly starts to unwind again. Microsoft recently conducted a company-wide attempt to rationalize its naming. AI threatens to undo this again. But Nadella has done a brilliant and heroic job of uniting the previously warring Microsoft divisions together under his leadership. Will he manage to do the same with Microsoft’s AI brand architecture?
For its AI related products, Microsoft uses a whole variety of names of different types. We have purely descriptive names—“Cognitive Services”, “Workplace Analytics”. Then there are industry vertical designations—“AI for Healthcare”, “AI for Retail”, etc. Then there are pure coined names—“DeepSpeed” (not DeepSeek!), “ONNX”. And there are benefit-related names—“AI for Good”, “AI for Sustainability”.
The nearest there appears to be to any organizing B2B product naming principle is names related to the specific Microsoft product families which they are part of—“Azure”, “Power”, “365”.
There is no consistent relationship to the Microsoft brand. It’s not locked up with most of the AI products, but is for some—“Microsoft AI for Retail”, “Microsoft 365 Copilot”. In some cases, it’s locked up with the product family brand—“Azure”, “Power”, etc.. In others it seems to have a name not specifically linked to anything—“AI for Good”, “ONNX”, “DeepSpeed”.
Microsoft is missing an opportunity to reset and start with a consistent brand architecture of AI products. Instead, it is replicating the inconsistencies and confusion of prior Microsoft architecture structures. Neither Microsoft’s AI brand architecture, nor Microsoft’s overall brand architecture follow any consistent model. Branded House, House of Brands, Unitary brands, etc.—it’s all over the place.
OpenAI’s simple yet innovative B2B brand naming strategy
In stark contrast, OpenAI’s approach to B2B product naming is clear, simple and evocative. There are far fewer names. They are short. They are all coined in one way or another. There is no clear system, it’s just a collection of products. The nearest there is to a system is a product family for “OpenAI”—“OpenAI API”, “OpenAI Gym”, “OpenAI Robotics”. While being coined, the names meet best practices principles in that they all communicate an idea of the product’s benefit. “OpenAI” communicates free and available to all. “ChatGPT” summons up the idea of a chat bot answering all your questions. “DALL-E” is both creative and evokes what the product does—creates images from a description in natural languages, like Salvador Dali!
It’s the technology, the open-source strategy and being first to market that has created the power behind the OpenAI brands, and made the company so desirable that Elon Musk is trying to buy it for $97.4B—an offer that Sam Altman and the Board have derisively rejected. But the power and value of the OpenAI portfolio is unquestionably enhanced by its portfolio naming strategy. It’s the OpenAI brands that have become the industry standards, the brands that have the highest recognition among tech geeks and the average consumer alike. 
Amazon—an organized and benefit-driven approach
Amazon has one of the most consistent AI product naming brand architectures of any company. It follows a Masterbrand endorsement strategy—all product names are locked up with the Amazon brand in most cases, and the AWS brand in others, in a co-brand system.
Almost all the AWS AI names follow a consistent B2B product naming strategy using a real word in the imperative to powerfully and clearly describe the benefits that the product brings—“Amazon Transcribe”, “Amazon Translate”, “Amazon Comprehend”, etc.
There are some coined names—“Amazon SageMaker”, “Amazon Rekognition”, “Amazon Kendra”. Most of them also reference what the benefit does and its benefits—“Rekognition” recognizes things, “Kendra” knows things (an old Celtic word meaning ‘knowing’).
It’s not surprising. Jeff Bezos has from the start had a sophisticated, far-sighted and strategic approach to brand naming. He did not name the original Amazon online bookstore “BooksOnline.com” (though somebody else did). He adopted a more ambitious approach, widely criticized at the time, naming his offer after the Amazon, a broad river that sweeps everything into it. The name has allowed him to expand easily into multiple other services. Amazon is now one of the world’s most valuable brands, while BooksOnline has been forgotten.
The importance of consistency and audience alignment
These varying approaches to naming AI products and services illustrate the broader challenges of brand architecture in the B2B landscape. Structured and descriptive names offer clarity and build trust, particularly among enterprise clients seeking reliable solutions. Conversely, creative and evocative names can foster excitement and differentiation, appealing to innovators and early adopters.
Ultimately, the key to effective AI product naming lies in consistency and alignment with the company’s brand identity and target audience. Whether adhering to tradition or embracing innovation, companies must prioritize a thoughtful and strategic approach to B2B product naming for their AI offerings.