Date:
Author:
Anastasiia Pohyba
001
AI has made production more accessible. But creative ideas still matter the most.
AI content creation has evolved rapidly from an experimental marketing tool to a production option that brands actively budget for.
Companies in Dubai are already commissioning AI commercials, social videos, campaign visuals, digital characters, product content, and performance ads. A production process that once required locations, casting, equipment, crews, and several weeks can now begin with a laptop.
This has created an unusual market.
The technology is impressive, yet access to it tells you very little about the quality of the work.
The same video models are available to an independent creator, an advertising agency, an internal marketing team and an AI production studio. They can generate with the same software and end up with completely different work.
The difference usually appears much earlier than generation.
It starts with the idea.
For the first few years of generative AI, technical execution itself attracted attention. A realistic person generated from text was interesting. A cinematic scene created without a physical shoot felt novel. An artificial character remaining recognisable across several frames was an achievement.
That novelty has a short lifespan.
Models improve, interfaces become easier, and techniques that required specialist knowledge gradually turn into standard functions.
By 2026, the advertising industry is already discussing the consequence.
McKinsey described one of the dominant conversations at Cannes Lions 2026 as “mediocrity at scale”: enormous amounts of creative output being produced through a relatively small number of models, creating a tendency towards visual and conceptual sameness. Its conclusion was that judgment, storytelling, taste and cultural intuition become more valuable as execution becomes easier to access.
That is the shift brands need to understand.
AI is making production cheaper. It is making average creative easier to produce too.
The competitive advantage is moving somewhere else.
AI Content Creation Is Becoming a Commodity
There was a short period when the production method itself was enough to earn attention.
A realistic person generated entirely through AI felt interesting.
Character consistency across several scenes was impressive.
An impossible camera movement made people ask how the video had been created.
Those achievements still require skill, particularly in complex production. Their novelty is declining rapidly.
Models improve.
Interfaces simplify.
Functions that once required complicated workflows become buttons, presets or standard features.
Creative productivity is already moving accordingly. McKinsey reported in 2026 that some organisations were seeing two- to fivefold increases in creative productivity and reductions of 10% to 30% in creative costs as AI became integrated into marketing production.
That is commercially important.
It also creates a new problem.
When everyone can produce more, producing more stops being a meaningful advantage.
The scarce resource becomes the ability to recognise what deserves attention.
002
Why expensive AI content can still look cheap
There is a particular kind of AI film that has become easy to recognise.
Every individual frame looks beautiful.
There is dramatic lighting, detailed texture, cinematic movement, impressive transitions and a level of production polish that would have been extremely expensive to recreate physically a few years ago.
Then the film finishes and almost nothing remains in your memory.
The problem usually starts before generation.
There was no sufficiently strong creative idea.
A good campaign needs internal logic: an observation about the audience, a tension, a character, a joke, a distinctive visual device, a particular world, a behaviour people recognise or an idea that says something about the brand.
AI makes it possible to start producing before any of that has been solved.
A team can generate the first beautiful frame within minutes.
Then another.
Then twenty more.
Production starts to feel like progress.
Fifty polished shots later, the campaign can still have no reason to exist.
This is one of the stranger consequences of generative production.
The lower the cost of making an image becomes, the easier it is to waste time making the wrong image.
003
Creative Direction Starts Before the Prompt
The quality of AI creative is sometimes discussed as though the difference sits primarily in prompting or model selection.
Those things matter.
They sit quite far downstream in the process.
Before a prompt exists, someone has to understand the commercial brief.
What does the audience currently believe?
What needs to change?
What should they remember?
What part of the product is genuinely interesting?
What visual territory already belongs to competitors?
What could this brand credibly own?
Which idea can survive ten executions rather than one attractive frame?
These are creative and strategic decisions.
Once those decisions exist, AI becomes an extraordinarily powerful production environment.
Without them, it becomes an extraordinarily efficient way to generate options.
Those are very different outcomes.
Single-image generation can disguise weak creative direction surprisingly well.
Campaign systems expose it.
Once an idea has to survive a brand film, several social assets, paid-media variations and multiple scenes, unresolved decisions start appearing everywhere.
The character changes slightly.
The product behaves differently between shots.
The environments have no visual relationship.
Camera language shifts constantly.
Styling changes because each frame was generated as an isolated exercise.
The campaign begins to look like a collection of impressive prompts rather than one world.
Some of these problems are technical.
Many are art-direction problems.
A creative director still has to define casting, composition, framing, lens language, movement, colour, styling, rhythm and visual hierarchy.
An editor still needs to know when a shot has stayed on screen too long.
Sound design can change the entire interpretation of a sequence.
The product has to remain accurate.
The brand has to remain recognisable.
Consistency is increasingly becoming production hygiene rather than the creative idea itself.
Models will keep getting better at solving it.
The bigger question is whether the visual system is distinctive enough to belong to the brand.
A useful test is brutally simple:
If the logo disappeared, would anyone know whose campaign this was?
AI Advertising Has a Harder Job Than AI Art
A beautiful AI film and an effective advertising creative are different assignments.
Advertising operates in a less forgiving environment.
People scroll.
The opening seconds determine whether most viewers will ever see the rest.
The proposition needs to become understandable quickly.
A visual can interrupt the feed, but interruption alone does not create interest in the product.
The concept also needs enough flexibility to evolve once performance data arrives.
This is why advertising experience matters when selecting an AI content agency.
A visually sophisticated portfolio proves production capability.
It says less about whether the team understands hooks, positioning, audience psychology, offer structure, conversion behaviour or creative testing.
Generative AI can make the asset.
Someone still needs to understand what job that asset has been hired to do.
004
What We Learned Using AI Avatars for Performance Advertising
We recently used AI-generated characters in paid social advertising for a consumer app in the US.
The product helps women explore different hairstyles virtually, so the advertising needed to make the transformation understandable almost immediately while addressing different motivations around appearance and choosing a hairstyle.
The interesting part was not the avatar itself.
The avatars gave us a creative production system.
We could develop different women, hairstyles, situations, hooks and messaging angles without arranging a new physical production every time we wanted to test a hypothesis.
That changed the economics of iteration.
Instead of treating one finished video as the deliverable, we could treat creative as something that continued developing once audience behaviour started giving us information.
Some concepts could be expanded.
Others could be stopped.
A winning hook could lead to another scenario.
A character could support several variations.
Performance data could influence the next creative decision.
That is where AI production becomes much more interesting commercially.
The question moves away from How cheaply can we produce this video?
It becomes:
How quickly can we learn what creative actually works?
The campaign ultimately has to be judged through business metrics such as CPA, conversion and revenue.
The audience does not owe the production method any admiration.
The creative has a job.
It has to perform.
005
AI Changes the Economics of Creative Testing
Traditional production naturally encourages concentration.
If a brand has invested substantially in locations, casting, crew, equipment, logistics and post-production, it wants to extract as much value as possible from the assets created during that shoot.
Generative production allows a different model.
A concept can branch.
A successful performance ad can lead to several new hooks.
A campaign character can enter another situation.
A static visual can develop into motion.
One visual world can expand into different executions across paid social, organic content, digital media and campaign assets.
This creates enormous potential for performance marketing because more creative hypotheses can reach the market before testing costs become disproportionate.
Volume, however, has almost no value by itself.
Twenty variations of an uninteresting idea give an advertising platform twenty opportunities to confirm that nobody cares.
Creative iteration becomes commercially useful when there is something worth iterating.
The winning AI production model therefore looks less like:
generate → generate → generate → publish
and more like:
insight → idea → creative system → production → market response → learning → next iteration
AI dramatically accelerates the middle of that process.
It can increasingly accelerate the learning loop too.
It still needs a hypothesis.
006
What Should a Brand Pay an AI Creative Agency For?
This is where procurement needs to evolve.
If the main value proposition is access to particular software, that advantage will probably depreciate quickly.
Brands should be paying for capabilities that remain valuable as the tools improve.
Can the team find the creative idea?
Can they translate a commercial problem into a campaign concept?
Can they develop a recognisable visual system instead of a collection of attractive assets?
Can they protect existing brand codes?
Can they direct a story across several scenes?
Can they design creative that can evolve based on performance?
Can they recognise when AI is the wrong production method for the idea?
Can they make decisions about what should be generated before production begins?
These questions reveal considerably more than asking which models a studio uses.
The technology stack will change.
Judgment compounds.
As AI-generated people and content become harder to distinguish from conventional production, audiences are becoming more conscious of authenticity and disclosure.
That does not mean brands need to make AI the subject of every piece of communication.
It means the decision to use synthetic people, simulated testimonials or realistic representations should be treated as a brand and trust decision, rather than purely a production decision.
The technology allows increasingly convincing simulation.
The creative team still needs judgment around where simulation helps the idea and where it creates unnecessary reputational risk.
This will become increasingly important as platforms, regulators and audiences develop stronger expectations around AI-generated commercial content.
How to Choose an AI Content Creation Agency in Dubai?
Start with the portfolio.
Then mentally remove the words AI-generated.
Would you still want the work?
If the answer changes once the novelty of the production method disappears, the technology may be carrying too much of the creative proposition.
Then investigate how the work was developed.
What was the original business problem?
What idea came before generation?
How was the visual language defined?
How did the team maintain the product and brand?
What happened in post-production?
What changed after client feedback?
If the work was advertising, what happened after it entered the market?
Can the team discuss performance rather than aesthetics alone?
The Next Advantage Belongs to Brands With a Point of View
There is an interesting parallel happening in search.
Google's 2026 guidance for generative AI search explicitly recommends unique, valuable, non-commodity content and encourages publishers to contribute first-hand experience and a distinctive point of view rather than reproducing information that could easily be generated elsewhere.
Creative production is facing a similar economic pressure.
If almost anyone can generate competent imagery, competent imagery becomes abundant.
A brand still needs something specific to say.
A creative team still needs an observation worth developing.
Someone still has to choose one idea from a hundred possible ones.
Someone has to recognise what belongs to this brand and reject what could belong to any brand.
Someone needs to understand the audience well enough to distinguish an aesthetically impressive execution from an idea people might actually remember.
AI creates an extraordinary production environment.
It also removes one of the old excuses for average creative: production limitations.
When almost anything can be made, the quality of the decision about what to make becomes much more visible.
That is where I think the next competitive advantage in AI content creation will sit.
We develop AI-led advertising, campaign films, digital characters, performance creative and branded visual systems for companies in Dubai, the UAE and international markets, combining creative direction with generative production and commercial marketing experience.
