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Why classic production can no longer keep up with SMM
— In classic production, a brand could prepare a large pool of content ‘for the future’: come to the studio, assemble a team, shoot dozens of videos, arrange them according to a calendar, and publish them over several months.
Today, this is no longer possible. The reason is simple: what works now may lose its relevance in a month.
Algorithms change, audiences burn out, trends shift. Classic production is designed for campaigns with a long life cycle: TV, outdoor advertising, brand image.
One perfect video no longer does the job: dozens of versions and hypotheses are needed. If every video is made like a mini-film, budgets and deadlines no longer match.
This is where the gap between how classic production works and how modern marketing works arises.
AI has become the tool that bridges this gap. With its help, you can do what used to require a large team and complex production. There is a myth that neural networks do everything ‘with one click.’ In reality, the quality of the final product depends 90% on the specialist who puts together what the AI has generated.
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Why can’t AI work on its own yet?
Detailing: a neural network can come up with a great idea or a piece of background, but only a human can ‘glue’ the video together so that the character opens their mouth naturally or interacts with the product correctly.
The trap of mediocrity: the market is already tired of typical neural network content. To prevent the user’s eye from being caught by the ‘plasticity’ of the image, manual refinement, keen observation and professional editing are required.
For the user on social media, there is almost no difference.
If a video elicits a reaction, it gets views. If not, neither the film crew nor expensive equipment can save it.
Sometimes it is necessary to indicate that the content was created using AI, but this does not affect its effectiveness. People react not to the technology, but to the idea and presentation. And if AI is used carefully, most users don’t even notice that they are looking at a generated image.
The audience is tired not of AI, but of poor content: template faces, strange emotions, and visual noise. When a neural network becomes a tool and a specialist adds the finishing touches, the technology ceases to be conspicuous.
How to quickly find effective creatives with AI
Modern SMM is not just about ‘pretty pictures,’ but about creatives that deliver results. AI allows you to test the effectiveness of an idea before publication, turning A/B testing from an intuitive process into a precise tool.
4 advantages of AI in creative testing:
- Instant hypothesis generation: instead of 2-3 ideas, the team gets dozens of scenarios formulated according to the ‘if-then-because’ business logic.
- Production scaling: creation of dozens of variations (different CTAs, headlines, styles) without involving additional designers and overloading staff.
- Pre-attention analysis: neural networks predict where the user will look in the first 2 seconds, allowing you to refine the layout before launch.
- Budget optimisation: you weed out weak options at the draft stage, without spending money on their rotation in advertising accounts.
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