Vedran Obradović, founder, Vizura Studio®
there is a strange mismatch developing in AI. the products are becoming more specific while the public signals around them are becoming less specific.
one company might be building infrastructure for portable workloads, another might be solving a narrow security problem, another might be automating a particular professional workflow. underneath, those products can have completely different operating logic, risks and buyer consequences. then you open the websites and much of that difference disappears into the same familiar language about intelligence, speed, transformation and the future.
i do not think that is simply a visual trend. for a buyer, it becomes a comprehension problem.
working with B2B and technology companies, i keep coming back to the same question: how much of the real product difference survives first contact? not after the demo, not after a technical deep dive, but in the first few minutes when someone is trying to understand what the company actually does, why it matters and whether it deserves more attention.
every category develops shorthand, and shorthand is useful. a security company does not need to look like a bakery to prove it is distinctive. a developer product can use conventions technical users already understand. an enterprise platform still needs to signal maturity and trust. familiarity lowers the cost of comprehension.
the problem begins when familiarity starts doing almost all of the work.
if the headline, proof points and visual language could move to three competitors without feeling out of place, the brand may still look polished, but it is not carrying much proprietary meaning. that distinction matters because credibility and specificity are not the same thing. a company can look credible and still leave the buyer unable to explain why this product is different from the next one.
AI makes the tension sharper because plausible execution is getting cheaper. another competent headline can be generated in seconds. another interface direction, another abstract symbol, another campaign image, another variation of the same familiar promise can appear almost immediately. none of this makes the tools bad. i use AI where it helps with research, exploration and operational work. the interesting consequence is that polished output is becoming less scarce.
when production becomes abundant, selection becomes more important.
that changes what i look for before design begins. what is the product actually changing for the buyer? which capability would still matter if every fashionable adjective disappeared? what evidence supports the strongest claim? which category conventions are helping the audience understand the product, and which ones are hiding the difference behind familiar language?
those questions sound simple, but they force a company to choose. and that choice is usually harder than generating another version.
a useful test is the competitor name swap. remove the company name from the homepage and imagine the same message under a competitor’s logo. if very little feels wrong, the company is probably describing the category more clearly than it is describing itself.
another test is memory. after five minutes, what would a buyer actually repeat to someone else? not the slogan, but the idea. if the answer is only „AI for finance“, „AI for security“ or „AI for operations“, the company may be understandable without yet being memorable.
i also like tracing claims back to something concrete. if a company says it is secure, what does that point to? if it says it gives users more control, where does that control exist in the product or operating model? if it promises speed, what specifically becomes faster and why does that matter? a claim becomes more useful when it has somewhere real to lead.
this is where branding can either reveal the product or flatten it.
the weak version begins with a mood: make it innovative, premium, AI native, enterprise ready. those words can be useful as internal direction, but they do not tell us what should belong uniquely to the company. without a more specific idea underneath, design usually ends up decorating the category.
the stronger version starts with product logic. perhaps the meaningful difference is portability, ownership, verification, a particular workflow, a different trust model or a way of reducing risk that competitors do not handle in the same way. that logic may eventually influence language, visual identity, product presentation or the way proof is structured. the point is not to turn every technical detail into a graphic motif. it is to make sure the identity grows from something the company can actually own.
this matters especially in B2B because buyers rarely receive the whole truth at once. they see a search result, a website, a deck, a recommendation, a short sales conversation. before they verify the technology, they are already building a mental model of the company. if the public signals turn a specific product into generic category language, the buyer has to work harder to discover the difference that already exists.
there is a temptation to answer this by making everything louder or stranger. i do not think that helps. distinctiveness without comprehension creates a different problem. the useful question is not „how do we look unlike everyone else?“ it is „which familiar signals are helping, and where should familiar stop so proprietary meaning can begin?“
sometimes that means keeping a familiar interface pattern while becoming much more specific in the verbal idea. sometimes it means using a restrained identity but making product proof unusually concrete. sometimes it means choosing one recognizable principle and repeating it consistently enough that the market starts connecting it with the company.
the best outcome is not novelty. it is recognition with meaning attached.
AI products are likely to keep diverging. infrastructure will become more layered, vertical tools more specialized, workflows narrower, governance choices more consequential. if the brands around those products keep converging, the market becomes harder to read exactly when buyers need more clarity.
for me, that is the real opportunity. not making AI companies look different for the sake of difference, but helping real product differences become easier to see, explain and remember.
when execution is easy to generate, the durable advantage moves further upstream. it sits in judgment, in deciding what deserves emphasis, what should be removed and what idea is specific enough to belong to one company rather than the whole category.
author information
Vedran Obradović
founder, Vizura Studio®
based in
Zagreb, Croatia
studio
independent one-man branding studio
experience
8+ years in branding and identity
focus
B2B and technology branding, including SaaS, AI, cybersecurity, consulting and finance
about
Vedran Obradović is the founder and designer behind Vizura Studio®, an independent branding studio in Zagreb focused on B2B and technology companies. his work spans positioning, brand strategy, visual identity and digital experience across AI, SaaS, cybersecurity and other technically complex or trust-heavy categories.
useful links
studio website
https://www.vizurastudio.hr/
selected work
https://www.vizurastudio.hr/work
about
https://www.vizurastudio.hr/about
LinkedIn
https://www.linkedin.com/in/vedranobradovic/
personal site
https://www.vedranobradovic.com/
public project references
Breach
https://www.vizurastudio.hr/hr/work/breach-b2b
selected portfolio
https://www.vizurastudio.hr/work
editorial note
the links above are public references the editor can use for verification or supporting context. additional high-resolution project imagery can be supplied separately if requested. please feel free to shorten or edit the article for publication while preserving the meaning and first-person voice.