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Most branded content teams now have AI tools, but this hasn't solved the branded content bottleneck. It's simply moved it. Taking an AI-generated idea to an on-brand and interactive piece is still a process that takes a long time, involes a lot of people, and breaks down at the production stage.
To learn more, we spoke to Tine Karlsen, CEO of Vev, about the realities of how enterprise content teams are working today and how Vev helps provide a solution.
Currently, branded content teams are under more pressure than ever to produce faster. Where do you see the biggest bottlenecks?
I see two patterns right now that worry me.
The first is that advertisers are starting to believe AI can replace editorial judgment — and with that comes an expectation that content should cost less. I had a conversation recently with Georg Burtscher, Managing Director of Russmedia, and he shared something striking: their branded content pieces often have longer reading times than their editorial news articles.
His reflection was that branded content has brought back something news media lost in the fast cycle — the willingness to go deep on human stories behind the logos and products.
The real work is finding the angle that makes someone actually want to stay. And the reading time and conversion numbers prove it works — dramatically outperforming what you'd get from programmatic alternatives.
More advertisers should recognise the value publishers bring: knowing how to ask the right questions, talk to real people, and craft stories that genuinely engage.
The second pattern is advertisers arriving at publishers with AI-generated designs and saying "just publish this." It sounds simple, but it misses how good branded content actually works.
The teams producing award-winning work in Vev don't start with a design and retrofit a story into it. They start with the story. They go on-site and brief the photographer on exactly what's needed — short clips of people in action for stoppable video moments, stills paired with key quotes, visuals that serve the narrative. The design and the storytelling are one process from day one. That's what makes it perform, and that's exactly what gets lost when you try to shortcut it with a pre-made AI layout.
AI tools are everywhere, but a lot of teams are still struggling to make them work in practice. Why do you think that is?
Most teams have figured out AI for text. You can iterate on copy with AI and end up with something that's genuinely good and true to the writer's voice. That part works.
Where it breaks down is with everything visual and interactive. We've tested this ourselves — when you prompt AI to build a full interactive branded content piece, it draws on what it knows from the web. And what does most of the web look like?
SaaS landing pages.
So you end up with something that has the layout logic of a software product page, not a story. The sections are generic, the hierarchy is wrong for editorial content, and there's no relationship between the design and what the text is actually saying. A creative director takes one look and kills it.
That's the deeper problem: AI has no taste, and no understanding of context. It can generate something that looks like a branded content piece, but it can't tell you whether it actually feels right for the brand, whether the interaction design serves the story, or whether the visual weight is in the right place. You still need a creative to judge quality and a developer to validate feasibility.
That's why we see teams getting excited about AI, trying it, and then hitting a wall. The output looks promising at first glance but can't survive the review process. The gap isn't in idea generation. It's in getting from an idea to something publishable at a level of quality you'd put your brand behind.
Vev has been moving towards being an AI-powered platform. What does that actually mean in terms of how teams work day-to-day?
There are really two layers to how AI works in Vev today, and a third we're developing.
The first is Element AI, which is live and working well. A content editor can prompt a single interactive component — a calculator, a quiz, a data visualization — and it generates within the context of their existing design. They can feed it reference images to guide the style, so it stays on brand.
And critically, the output isn't a black box. You can edit it visually, ask the AI to leave editable content areas so the element is reusable, and get visual editing access so you can restyle it for a different brand without re-prompting. That's what makes it a production tool rather than a party trick.
The second is Page AI, which we've recently launched. It takes your content, a chosen design library, and a prompt, and builds a starting point for an entire article or page. I want to be honest about what that means: it's a starting point.
It's genuinely difficult for AI to read a full text and understand how to break it into an interactive story where the design choices are tightly connected to the context — where this paragraph needs a stoppable video moment, and that section needs a data visualisation, and here's where the pull quote should land.
Page AI is good enough today to save real time on assembling the foundation, getting you to a structured draft that's ready for human tweaking. But it's not replacing editorial and design judgment.
And that's exactly the challenge we see across AI builders right now — they produce generic web design.
They can generate something that looks like a page, but it doesn't understand the relationship between content and presentation. It doesn't know that this part of the story deserves more visual weight, or that the reader needs an interactive pause here.
Which brings me to where we're heading: the next step is breaking the content down into sections where you can visually ideate with the AI — section by section, deciding where to use a library component, where to use Element AI to create something bespoke, and where the AI might suggest a creative approach you hadn't considered. That's the leap from AI as an assembly tool to AI as a creative collaborator, but with the editor always in control of the decisions.
What would your practical advice be to a branded content team that wants to get more out of AI in the next 12 months?
For most branded content teams, time isn't lost in writing — it's everything around it: waiting for design assets, adapting layouts to each new client's brand, building interactive elements from scratch, revision rounds when something doesn't look right.
First, build your design system before you scale AI. AI works best when it operates within constraints — a defined brand palette, component library, typography rules. Without that foundation, AI output is generic and your creative team will reject it. With it, AI can generate things that actually look like they belong.
Second, invest in the brief — and I mean the creative brief, not just the client brief. The teams getting the most from AI are the ones spending more time upfront on how to tell the story, not less. Break your text into sections early. Think about which moments need interactivity, where the reader needs to pause, what kind of content you need to go capture. That upfront thinking is what separates branded content that performs from content that just exists. AI amplifies whatever you feed it. A thoughtful brief produces something worth publishing. A lazy one produces another SaaS landing page.
Third, and if I'm being direct: I see a lot of branded content teams operating without anyone in a creative role. If that's your situation, my advice is to hire — because this connects directly to my first point. Someone needs to build that design system. Hire technically strong creatives with good taste. AI makes those people dramatically more productive but AI doesn't replace the taste itself. Without someone who can judge whether the output is actually good, you're just producing faster versions of mediocre work.
About VeV
Vev is a visual content creation platform that sits on top of an organisation's existing CMS, enabling teams to build interactive, branded digital experiences without developer dependency. The angle for this interview is specifically about how AI is changing branded content production workflows, and what that looks like in practice.