[Interview] Vedran Obradović, Founder, Vizura Studio

Marketing Report spoke to Vedran about Brand OS, his approach to turning brand guidelines into an everyday working system, and what AI means for the future of brand management.

As generative AI becomes increasingly embedded in marketing and content creation, maintaining brand consistency is becoming a new challenge for businesses.

Vedran Obradović, Founder and Brand Designer at Vizura Studio, believes the answer lies in making brand strategy more accessible and usable across people, platforms and AI tools.

What problem did you see in the market that led you to create Brand OS?

Brand OS came from a problem i kept seeing after branding projects were supposedly finished. The identity itself could be strong, but using it was still scattered across PDFs, folders, freelancers, internal teams and, increasingly, tools like ChatGPT or Claude.

A small task could still become a surprisingly long chain: find the right file, check the guidelines, brief somebody, explain the context, wait for the work and review it. Six months after a launch, sales might describe the company one way, the website another, social a third, while an AI tool produces something generic because it was never given enough context.

That made me realise the handoff was the weak point. The useful part of a brand system is not only documenting decisions. It is making those decisions reusable when people are actually doing the work. Brand OS grew from that idea.

How does Brand OS change the way companies use and manage their brand guidelines in everyday work?

The main change is that the guidelines stop behaving like a reference document people open only when something goes wrong.

Brand OS puts positioning, identity rules, approved assets, templates and practical tools in one live place. A founder can find the correct logo without asking a designer. A marketing person can check a colour combination or prepare a routine social asset without starting a new design request. A freelancer can understand the key rules without a long onboarding call.

I do not think companies need more rules for the sake of rules. They need the correct action to be easier. If the approved asset, the explanation and the boundary are already where the work happens, consistency becomes much more natural.

You describe Brand OS as having an “AI context layer.” What does that mean in practical terms?

In practical terms, it means the important brand context is made usable by AI tools instead of being trapped in a PDF written for humans.

The context layer can include the company's positioning, what it does and does not claim, audience, tone of voice, preferred language, messaging boundaries and the rules that should stay consistent. That context can then be given to a tool such as ChatGPT or Claude before asking it to write.

The important distinction is that Brand OS is not asking AI to invent the brand. The strategic decisions still come first. The AI layer gives the model a better starting point so it is working from the same logic the company is using rather than reconstructing the company from a vague prompt every time.

Does generative AI pose risks to brand consistency or make brands more accessible internally?

Both, and the two are closely connected.

AI makes production easier, which is useful. A small team can explore more variations, draft faster and remove a lot of repetitive work. But the same accessibility means more people can create brand output without understanding why the brand works the way it does.

The risk is not only that AI produces something obviously bad. The bigger risk is competent, plausible output that slowly pulls the company toward generic category language because every prompt starts from incomplete context.

The opportunity is to make the brand more accessible without making it looser. If the system gives people and AI tools the same core context, teams can move faster while still preserving the decisions that make the company recognisable.

What’s the biggest misconception about using AI for brand communication?

That the model is usually the main problem.

People compare tools, prompts and model versions, but a lot of weak output starts earlier. The company itself has not clearly decided what it wants to be known for, which claims are truly ownable, how the voice should behave, or what the model should never improvise.

AI is very good at amplifying available context. That makes clear brand decisions more valuable, not less.

Why focus Vizura Studio on B2B, tech and AI brands, and what makes branding in these sectors different?

I like businesses where the value is real but not immediately visible.

A B2B or technical product can be excellent and still be difficult to understand from the outside. Buyers often meet the homepage, deck or sales story before they can properly evaluate the technology. That creates an interesting branding problem: the job is not to make complexity disappear, but to make the important part legible quickly enough that somebody wants to keep looking.

These sectors also have strong category habits. Words such as fast, secure, intelligent, scalable and flexible can all be true, but competitors often say the same things. The visual language can converge just as quickly.

So the work becomes a balance between familiarity and distinction. The brand has to help people understand the category while giving them a clear reason to remember this company.

Where’s the biggest gap between brand strategy and day-to-day use?

Companies often think of branding as something they complete, while the people inside the business experience it as a stream of small decisions.

The strategy deck and guidelines may be excellent, but Monday morning still arrives. Somebody needs a partner logo, a sales slide, a social post, a new landing page or a quick answer from an AI tool. If the system is difficult to use, people create shortcuts. Not because they dislike the brand, but because they are busy.

That is the gap i care about most. A brand can be strategically correct and visually strong, yet still fail operationally if everyday use depends on somebody remembering where a file lives or how a rule was intended.

Good brand management should reduce that friction rather than simply document it.

How will AI reshape brand management and everyday marketing?

I think the brand book is moving from documentation toward infrastructure.

Static guidelines will still have value because teams need a clear record of the system. But more of the real brand experience will happen inside tools: content systems, websites, templates, design software and AI assistants. The useful question becomes whether those tools are working from the same decisions.

That means brand management will become more operational. Positioning, approved claims, voice, assets and visual rules will need to be structured so both people and software can use them.

I do not see that removing designers or brand leaders. It changes where their value sits. Less time should go into policing routine output and more into making the underlying decisions strong enough that the system can scale them.

www.vizurastudio.hr

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