Social media, the Internet, and technological platforms are closely intertwined: Complementing each other, and helping one another to expand and innovate. 

Did you know that the Internet we know wouldn’t have been possible without social media inventions? ARPANET or Advanced Research Projects Agency Network was fuelled by early social media features such as online chatrooms, protocols for file sharing, and more, which gradually developed into the Internet by the early 1970s.

Hence, the concept and idea of social media is older than the Internet itself. 

Now, with the Artificial Intelligence revolution sweeping our normal day-to-day activities, it’s imperative to have AI influence and impact social media, taking it to the next level of innovation, personalization, and disruption.

We will showcase how AI can revolutionize social media for businesses, by incorporating data-led innovations and human-centered ideas, never seen before. 

And why AI-integration in Social Media is not a luxury anymore, but an inherent necessity, and how we at TechAhead can turbocharge your social media with powerful, creative, and intelligent AI use cases.

But before that, let’s surprise you by revealing some stunning data related to AI usage in social media, which has already started on a massive scale!

AI Usage In Social Media: The Revolution Has Begun

AI Usage In Social Media
  • A McKinsey study found that 77% of senior business leaders believe creativity is a major component of growth. 
  • Facebook reported upto 7X more ROI on ad campaigns, that are powered by AI.
  • AI-led creative content has triggered upto 75% more users inside Facebook Groups. 
  • Almost one-fourth of US social media users trust and appreciate AI-led content creation, but 59% are worried because they don’t understand, how AI algorithms work.
AI Usage In Social Media
  • 75% of US executives strongly believe that the benefits of AI-led creativity and content generation will outweigh the potential risks involved.
  • As per a Capgemini study, 75% of social media users and internet users trust content being created by Generative AI tools.
  • Around 63% of Marketers will deploy AI tools for different marketing campaigns like Influencer Marketing.
  • AI will add $25 trillion to the world’s economy in the next 5 years, with approximately $300 billion being spent by the retail industry alone on marketing and communication.

The trends are very clear and crisp: Artificial Intelligence, especially Generative AI will impact, influence, and transform Social Media App Development, and if you are ignoring AI, then you are forcing your brand to lose relevance in this new world.

AI-integration in Social Media: The New Frontier Of Innovation & Disruption

Years before OpenAI-led ChatGPT made Generative AI popular among the masses, social media platforms and brands have been leveraging the power of AI to empower their platforms and communities.

For example, TikTok, the viral sensation, has been using AI-powered algorithms to hook viewers via precise recommendations, and compelling them to spend hours on their platform, swiping super-short videos, one after another. 

AI-integration in Social Media: The New Frontier Of Innovation & Disruption

In 2016, that is 6 years before ChatGPT’s debut, Google had already introduced Machine Learning and AI-powered Smart Bidding, which enabled thousands of permutations and combinations to generate better, smarter advertisements for Google Ad managers.

In 2011, Apple had already introduced Siri, an AI-powered voice chatbot, that unleashed a new era of voice-enabled support and human-machine interaction, which paved the path for more ideas, more innovations, and more disruption in the space.

We can, in fact, go back to the 1970s and 1960s to find out how Artificial Intelligence and Machine Learning have been slowly but sharply developing, the results of which are now visible in the magic of AI-integration in Social Media, impacting billions of users worldwide.

10 Ways AI Is Transforming Social Media & Digital Businesses

10 Ways Artificial Intelligence Can Revolutionize Social Media Marketing For Businesses

Now, let’s find out 10 ways how Artificial Intelligence is being used by leading social media brands, apps, and Internet companies to engage users, increase their revenues, and generate more traction via seamless AI-integration in social media:

TikTok’s Personalized Feed Leveraging AI & Massive Data

TikTok uses collaborative filtering AI to analyze each user’s interactions (likes, comments, shares) and content consumption patterns across hashtags and categories. This data trains machine learning models to curate the infinite “For You” feed with videos perfectly tailored to each individual’s unique interests and preferences.

Facebook’s Ad Platform Triggering Higher ROI

Facebook’s AI ad manager leverages machine learning models like logistic regression and deep neural networks. These ingest thousands of user data points to optimize ad targeting, delivery timing/sequencing, and real-time bidding strategies. The AI continually tests variations to maximize conversion rates and ROI.

Instagram Content Moderation For Safer Social Media

Instagram employs an AI system combining natural language processing and computer vision models. These detect and flag potential policy violations like hate speech, nudity, violence, etc. in text/image/video content. Flagged content then goes through human review before possible removal.

The role of AI in content moderation

Brandwatch Sentiment Analysis For Human Emotions

Brandwatch uses AI and natural language processing to analyze the sentiments, opinions, and emotions expressed across millions of social media posts. This surfaces powerful insights into how customers and audiences really perceive brands, products, campaigns, and trends. This way, brands are now more closer to their audience, helping them to make the right decision, at the right time.

Trendsmap Trend Prediction For Knowing The Future

Trendsmap leverages the live firehose of Twitter (now X) data in realtime and uses AI to detect emerging topics, hashtags, and shared URLs that are rapidly gaining traction. This surfaces potential viral trends and insights days or weeks earlier than manual trend detection methods. It’s like predicting the future, via AI.

Sephora’s Chatbot For Understanding Your Needs & Desires

Sephora’s AI chatbot integrates natural language processing to understand beauty-related queries and requests. It then uses machine learning models and Sephora’s product database to provide personalized shade matches, outfit suggestions, and purchase recommendations via conversational AI.

AI Driving Engagement For Instagram Reels 

Instagram’s AI generates personalized “Reels” by analyzing each user’s interests and creating unique 15-second videos spliced together from curated photos and video clips. Using deep learning models like generative adversarial networks (GANs), AI production rivals human video editing, and inspires users to spend more time on their app, translating to more revenues and more profits. 

IZEA Influencer Matching Powered By AI

IZEA uses machine learning to analyze data on over 30 million influencers’ audience demographics, interests, past campaigns, and engagement rates. This AI model matches brands with their statistically ideal influencers to maximize reach and impact. This way, the brand can choose the right influencer, to deliver stunning results, because now, their audience can resonate more deeply with the brand.

IZEA Influencer Matching Powered By AI

AI Powered Social Listening

Hootsuite Social Listening For Decoding Users

Hootsuite’s AI-powered listening tool monitors over 100 million sources in real time, surfacing relevant social media mentions, conversations, and trends around specified keywords, brands, or topics. Natural language processing models provide sentiment analysis and data visualizations. One of the most popular AI tools for social media marketers, HootSuite empowers brands because now, they can decode their users in real time.

Sprout Social Predictive Analytics For Unleashing Max ROI

Sprout Social uses AI and machine learning techniques like gradient boosting to predict customer churn likelihood and identify high-value audience segments. This allows targeted retention campaigns at an individual level to maximize engagement and revenue impact. If a brand knows and understands what its audience wants and needs, then magic is bound to happen.

AI-Powered Social Media App Development: 10 Interesting Use Cases

AI-Powered Social Media App Development- 10 Interesting Use Cases

We have observed how AI-integration in social media apps is actually a reality, and how the world’s most popular social media platforms and social media management firms are deploying AI for maximum impact.

Now, let’s find out how we at TechAhead can help you with AI-integration in social media, and how our AI expertise can help you to launch powerful, creative, and user-focussed social media apps:

Personalized Content Curation For Higher Engagement

We can deploy AI algorithms to analyze highly personalized user data such as browsing history, interests, demographics, and engagement patterns to build personalized user profiles. Using machine learning techniques like collaborative filtering and content-based recommendation engines, the AI can curate a unique content feed tailored to each user’s preferences, increasing relevance and engagement. 

ROI-focussed, Intelligent Advertising

We can use AI to power ad platforms such as Google Adwords and Facebook Ads with machine learning models that optimize ad targeting, bidding, and creative elements in real time. Techniques like lookalike modeling identify high-value audience segments, while reinforcement learning algorithms continuously test and optimize ad delivery strategies based on performance data to maximize ROI on every dollar spent. 

AI Powered Content Moderation Within Social Media Apps

Discover How TechAhead Can Enhance Your Social Media Presence with AI Integration and Create User-centric Social Media Apps – 1

We can train and empower social media platforms to deploy AI models trained on large datasets of text, images, and videos to automatically detect policy-violating content within the social media app. Via Natural language processing and computer vision techniques, we can identify hate speech, nudity, violence, and other harmful content that human moderators can review and remove if necessary.

AI-Sentiment Analysis For Unleashing Innovation 

Our developers at TechAhead can leverage AI-enabled sentiment analysis tools and use natural language processing and machine learning to analyze the emotional tone and opinions expressed in social media posts, comments, and messages. This can provide your brand with invaluable insights into customer sentiment, identifying potential issues and opportunities for customer engagement: Make the right decision, at the right time, in real-time. 

AI-Sentiment Analysis For Unleashing Innovation 

Trend Prediction For Unveiling The Future

We can deploy complex AI algorithms to analyze and study vast amounts of social media data, including post content, engagement metrics, and user interactions, to identify emerging topics, hashtags, and content formats that are gaining traction. Machine learning models can detect these early trends before they become mainstream, allowing your business to use this information to create a bigger impact. For example, if your brand is aware that football fans from New York will go berserk just 3 days before the UEFA European Football Championship, then you can plan the content and marketing campaigns accordingly, ensuring maximum results.

Conversational AI For Deeper Connections 

AI chatbots and virtual assistants use natural language processing to understand user queries and provide relevant information or actions. We can leverage machine learning techniques like sequence-to-sequence models, intent classification, and entity recognition to engage in human-like conversations and assist users on social platforms via intelligent chatbots.

Smart & Intelligent Content Generation

AI models like generative adversarial networks (GANs) and transformer-based language models can generate personalized social media content like captions, short videos, and images tailored to specific users or brand styles. This AI-powered content creation streamlines the process and ensures relevance for target audiences.

Selecting The Right Influencer At The Right Time

Machine learning algorithms can analyze data on influencer audiences, their engagement rates, content themes, and brand preferences to match brands with the most relevant influencers for their campaigns, at the right time. We can create this data-driven approach to improve campaign performance and ROI compared to manual influencer selection processes.

AI-Enabled Social Listening For Powerful Outcomes

AI-Enabled Social Listening For Powerful Outcomes

AI-powered social listening tools can scan and analyze vast amounts of social media data and use natural language processing to identify relevant mentions, conversations, and sentiments around specific brands, products, or topics. This provides valuable market and consumer insights for reputation management and product development.

Predictive Analytics For Decoding The Future

Our developers can create AI models to leverage machine learning techniques like logistic regression and gradient boosting to predict user behavior, engagement levels, and churn risks based on their historical data and activity patterns. These predictive insights can help social platforms to create better strategies to improve retention and engagement and create a loyal fanbase.

What are some examples of how leading social media platforms are using AI?

TikTok uses collaborative filtering AI to personalize the “For You” video feed for each user. Facebook leverages AI for intelligent ad targeting and delivery. Instagram uses AI for content moderation to detect policy violations. Brandwatch employs AI for social media sentiment analysis.

How can AI improve content curation on social media?

AI can analyze user data like interests, browsing history, and engagement patterns to build personalized user profiles. It then uses techniques like collaborative filtering to curate a tailored content feed that matches each individual’s preferences.

What role can AI play in social media advertising?

AI powers ad platforms with machine learning models that optimize targeting, bidding strategies, and creative elements in real time. Techniques like lookalike modeling identify high-value audience segments to maximize ad performance and ROI.

How is AI used for content moderation on social platforms?

Social platforms use AI models trained on large datasets to automatically detect hate speech, nudity, violence, and other policy violations in text, images, and videos. Flagged content is then reviewed by human moderators.

Can AI help brands understand consumer sentiment on social media?

Yes, AI sentiment analysis tools leverage natural language processing to analyze the emotions and opinions expressed in social posts/comments. This provides brands with valuable insights into how consumers perceive their products and campaigns.

AI algorithms analyze vast amounts of social data like post content, engagement metrics, and user interactions to identify emerging topics, hashtags, and viral content formats before they become mainstream trends.

How can AI power conversational experiences on social media? 

AI chatbots and virtual assistants use natural language processing to understand user queries and provide relevant responses. They use ML techniques like intent classification to engage in human-like conversations.

Can AI generate social media content like images and videos? 

Yes, AI models like generative adversarial networks (GANs) can generate personalized visuals like captions, short videos, and images tailored to specific users or brand styles using deep learning.

How does AI help with influencer marketing on social media? 

Machine learning analyzes data on influencer audiences, engagement rates, brand affinities, etc. to match brands with their statistically ideal influencers for maximum impact.

What is the role of AI in social media analytics and user retention? 

AI uses techniques like logistic regression to predict user behavior, engagement levels, and churn risks based on historical data. These predictive insights help optimize strategies to improve retention.

There are several AI tools catering to different aspects of app development. Here are a few examples:

For code generation and automation: TensorFlow Lite, PyTorch, and Spellbox AI

For design and prototyping: Uizard and Visily

For incorporating machine learning features: Core ML (Apple) and ML Kit (Google)

For chatbot development: Dialogflow (Google)

Looking forward to unleashing your unique idea via Social Media App Development? Wish to initiate AI-integration in Social Media? Connect with our AI experts and AI led mobile app development at TechAhead, and take the first step towards triggering a AI-powered revolution!