Keeping track of millions of online posts, memes, and discussion threads every day is impossible for humans – but effortless for artificial intelligence. Powered by neural networks, complex algorithms analyze vast amounts of data in seconds, spotting recurring subjects and active discussions, and processing content faster than any human ever could.
Neural networks focus on three main aspects to predict trends.
First, language models continuously scan posts, comments, and hashtags, spotting popular phrases and frequently asked questions, and detecting hidden patterns. AI algorithms can detect trends like a sudden increase in “winter space memes” online search queries long before the trend becomes mainstream.
Second, video. AI recognizes narratives and formats, identifying which transitions, challenges, or memes are gaining popularity. Some systems can even analyze viewer reactions, determining which videos elicit positive or negative emoji responses and which ones viewers skip.
Third, audience. Neural networks segment users based on behavior and interests, enabling the prediction of trending topics within specific demographics. For example, users interested in devices will receive relevant content about a new iPhone days after its announcement — before mainstream media coverage.
A prime example of such neurosystems is Google Trends and ChatGPT, which provide real-time lists of rising queries in any niche within minutes. Neural networks assist not only in topic discovery but also in content personalization. For instance, integrating generative images into ads boosts targeted actions by 10–15%, while in SMM, it increases engagement by precisely aligning with audience interests.
According to Yandex, one in ten advertisers on Yandex Direct now uses AI-generated images from YandexART. This demonstrates how rapidly AI is being integrated into daily visual content workflows.
Thus, trends today emerge not just from the minds of creatives but also through AI-driven data analysis, with neural networks detecting them first.
Neural networks as new assistants for SMM analysts
Previously, creating viral content required an entire team: analysts, copywriters, designers, and video editors. Now, neural networks handle all these tasks — identifying trends, suggesting ideas, and even producing ready-made videos.
For text, popular tools include ChatGPT, which scans social media and search queries to propose trending topics, and Jasper.ai, capable of crafting catchy headlines, engaging posts, and effective CTAs. Visual content is generated by MidJourney (stylized images) and Pictory (text-to-video with automated editing and captions). For audio, Mubert generates music tracks for any mood, from upbeat rhythms to meditative melodies.
Industry analysts predict that neural networks will generate up to 90% of internet content by 2026. This transformation is already underway, with major corporations positioning themselves for this shift. McKinsey & Company research reveals that 67% of businesses are planning to boost their AI investments over the next three years.
The efficiency gains are substantial. Traditional design work that once required 1-2 hours for image selection now takes just 10 minutes with AI assistance. This efficiency translates to approximately 20 hours of freed-up time monthly, allowing professionals to focus on high-level strategic initiatives. Social media managers can leverage automated AI workflows to handle repetitive tasks, maximizing their creative potential.
How to create a viral reel and bypass algorithms: A 4-step framework
Begin with comprehensive keyword research using platforms like Google Trends or AnswerThePublic. This research reveals which content generates engagement, identifies audience pain points, and shows where viewers spend the most time.
Break down trending content into specific formats. AI tools like ChatGPT can analyze current popular video types, such as: reaction videos to unconventional life hacks, time-lapse content with surprising conclusions, or dynamic transformation comparisons. These format templates serve as blueprints for creating content that aligns with current audience preferences.
When crafting a story, it is helpful to follow the trend + emotion + action formula. For instance, in a timelapse video showing the creation of a beaded bag, you could add an unexpected twist along with a prompt to your audience, such as “Can you try this yourself?” A simple challenge like this could boost viewer engagement and interest.
Editing has become much easier due to AI-powered tools such as CapCut and Pictory. These platforms allow you to quickly add visual effects, pick music, and organize your video, making it possible for even beginners to produce quality social media content in about 15 minutes.
Avoiding the pitfall of AI patterns
Despite the impressive capabilities of neural networks, experts often liken their use to fast food: quick and convenient but lacking a unique flavor, thus becoming boring. When everyone relies on similar templates and tips, content becomes repetitive and loses its individuality, that special spark that makes it stand out.
That’s why it is essential to inject humanity into your content. Share your personal stories, customer experiences, or even your failures. Incorporate authentic footage: just a few seconds of genuine emotion can outshine the flashiest AI-generated backgrounds. You might also consider filming your reaction to a certain event or news, creating behind-the-scenes clips, or adding your voiceover to an AI avatar.
What comes next for neural networks?
Today, the applications of neural networks extend beyond marketing; they are also used in customer service (54% of implementations), research (49%), and even IT (31%). This goes to show that generative AI is a versatile tool for a wide scope of tasks.
Yet, neural networks are not a full replacement for creativity. Instead, they act as powerful accelerators, saving time on data gathering and editing. Ultimately, unique content still comes from the human touch.
By Ruslan Gilmanov, social media promotion and development expert, founder of Blackgrizzly