AI does three things to existing practice: it accelerates, automates, and democratises. In brand and naming, each sounds like progress. Each carries a specific risk that is going largely unexamined.
None of this changes the fundamentals of what makes a brand system work. But it makes ignoring those fundamentals more consequential than it has ever been.
Acceleration: when speed hits a long term decision
In most marketing disciplines, mistakes made quickly can be corrected quickly. Campaigns are revamped. Content is updated. Messaging evolves.
Names are different. A name is among the most permanent decisions a business makes . It will be embedded in organisational identity, customer memory, contracts and trademark registrations. Getting it wrong can lead to years of compounding confusion and structural repair that is almost always more expensive than getting it right the first time would have been.
The friction that can slow naming decisions down - the time required to brief properly, to evaluate rigorously, to align stakeholders - is not inefficiency. It is a structural safeguard. Remove it and you don't just move faster. You remove the mechanism that is doing quiet but essential work.
Too often we have had to correct bad naming decisions because launch dates overruled careful consideration and validation. Today, with seemingly viable candidates and easy rationale at our fingertips, shortcutting the process has never been more tempting.
Automation: the compounding problem
Automation is only as good as the structure it operates on. Applied to a brand architecture with clear strategic logic, AI can add genuine value: analysing portfolio complexity, mapping competitive positioning, identifying overlaps and gaps. These are real capabilities.
But AI works within the architecture. It cannot determine it.
The business logic decisions — what to keep, what to consolidate, what to retire — require direct connection between brand structure and business intent. At the highest level of complexity they stop being brand decisions entirely, impacting the entire C-suite, not just the brand team.
Automation can support thinking, implementation and governance. But when it runs on a weak foundation it doesn't simply fail to help. It compounds the weakness at speed and scale. A brief without strategic logic produces AI output without strategic logic, which produces naming decisions without coherence, leading to a portfolio that makes local sense at every individual decision point but doesn’t add up.
Architecture problems have always had this character. They accumulate silently — one proposition added here, one acquired brand left in place there — until the portfolio no longer effectively supports the business it serves. By the time the problem is visible, the cost of fixing it feels larger than the cost of living with it. That perception is almost always wrong. But it is consistently powerful enough to delay action for years.
AI doesn't change that dynamic. It amplifies it.
We just finished a complex portfolio architecture and grade-coding nomenclature of a chemical company with a buy and build strategy. The challenge was to construct a foundation with long term value platforms that absorb products of the acquisitions seamlessly and remain customer friendly. The level of internal and external complexity, industry knowledge, and leadership vision provided the essential tailored insights and scrutiny that AI will not produce for quite a while.
Democratisation: the averaging of distinctiveness
Here is what makes the current moment particularly acute: most AI use in brand and naming is not institutional. It is individual, informal, ungoverned, below the radar of anyone with the authority to notice or correct it. Teams reach for general-purpose AI tools as a personal shortcut, not as part of a strategic process. The outputs enter the work quietly, without the scrutiny that a formal brief or an external partner would bring.
The consequences are already visible. Naming conventions have always been set by first movers and followed by the category — Apple, then Tangerine, then Apricot, then Blackberry, then Orange, then Raspberry. That cycle once took years. AI compresses it to months, because generative tools are trained on what already exists and oriented, by their nature, toward the center of existing patterns. They identify what works in a category and produce variations of it. They cannot originate the convention. They can only replicate it. Disruption is not truly on the table.
Recently, three separate teams of a client presented the same name independently, for three very different propositions, within the space of three weeks. Whether AI generated those suggestions directly is almost beside the point. The convergence was real. The distinctiveness was gone before anyone had noticed it happening. And be honest: how many “Allure’s” can one portfolio carry?
When everyone uses the same tools with the same absence of strategic framework, everything starts to look, sound, and feel alike. Relevant distinctiveness — the quality that makes a brand genuinely valuable — is precisely what these tools are least equipped to produce.
The white spot: brand architecture and naming strategy
These three risks share a common root, and it is not AI. It is the absence of sound brand architecture to give AI something coherent to work within.
Brand architecture is the strategic logic that organises an entire portfolio into a coherent, scalable, and resilient system. It precedes naming. It determines what gets named, how names relate to each other, what the master brand carries and what it delegates, and how the system absorbs the growth and transformation still coming. Without it, naming decisions accumulate into a portfolio that reflects the organisation's history rather than its direction.
The decisions that determine the architecture cannot be generated. They sit at the intersection of brand strategy, business strategy, and organisational reality. They require judgment built through experience, not produced on demand. That is the layer AI does not cover. Not because the tools are immature, but because the decisions are inherently human.
When that foundation is in place, something shifts. A brand system built on sound architecture doesn't just add up. It multiplies. An effective architecture makes naming faster and more coherent. Coherent naming creates clarity, internally and externally. This consistent identity builds the recognition and trust that compounds over time. And what compounds in brand ultimately compounds in business advantage.
AI can accelerate the compounding. It cannot create the conditions for it.
The prediction
Within two years, a clear divide will be visible.
On one side: companies that used this period of transformation to get their brand architecture right, building naming systems with real structural logic, designed for resilience, capable of absorbing the business change still coming. They will have a distinct, visible advantage in market clarity, acquisition efficiency, organisational coherence, and readiness for AI powered acceleration.
On the other side: companies that generated their way through the uncertainty without the right foundation. They will either be rebranding. Again. At significant cost, and at significant disruption. Or quietly leave the compounding advantage on the table. Which, over time, is equally costly.
The question is not whether to use AI in your brand and naming process. It is whether you have the architecture in place to give AI something coherent to work within.
If you're not sure, that's exactly where the conversation should start.
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Joachim ter Haar is Managing Partner at Skriptor. With offices in Amsterdam and Stockholm, Skriptor has helped companies build brand architectures and naming strategies across Europe and beyond.
