AI in social media: use cases,
top tools & adoption challenges

AI in social media: use cases, top tools & adoption challenges

February 13, 2024

AI use cases in social media

In recent years, AI's influence on social media and social networks has become so pervasive that it majorly defines the way we interact, enjoy content, and do business in virtual communities.

Recommendation systems

Any major social media platform currently integrates ML-based recommendation systems to segment users based on their profile data and behavioral patterns (shares, likes, comments, purchase and browsing history, etc.) and target them with personalized content suggestions. Such systems help users navigate an unlimited offer of digital resources, products, and services by offering them content they’re most likely to engage with.

Benefits
Provide a tailored user experience and boost engagement

Reinvent your social media strategy with Itransition’s AI solutions

Contact us

Examples of AI adoption in social media platforms

LinkedIn’s recommendation engine

LinkedIn uses an ML-based recommender system to provide job recommendations, suggest potential connections, show the most relevant posts at the top of each user's newsfeed, and offer online courses on its eLearning platform. It can also rank suitable candidates for an open position based on their expertise and location.
Profile dataActivity dataCourse metadataRecommendation
engineLearner course recommendationsOfflineOnline
recommendationsrequestrecommendationsRestli
end pointModel
treatment
(A/B testing)BlendingKey-value storeOnline

Scheme title: LinkedIn Learning's course recommendation system
Data source: engineering.linkedin.com — A closer look at the AI behind course recommendations on LinkedIn Learning

Top AI-based tools for social media management

Nowadays, social media managers and marketing specialists can choose from an extensive offering of AI-powered software. Here are some well-known solutions available on the market, selected by popularity and user feedback on peer-to-peer review sites.

Canva is one of the most popular graphic design platforms for the social media sphere. What’s more, its scope has progressively expanded with a set of AI-based tools for visual and textual content creation.

Key AI features
  • Design generation tool to turn simple images into social media graphics with the required headline and font
  • OpenAI-powered content generation to create or edit copy, social bios, and captions tailored to your brand's voice
  • Presentations feature to generate slides based on simple prompts
  • Video editing system that can combine images and clips into short videos and recommend suitable soundtracks
  • Content planner to create and schedule social media posts
Pricing
  • Free basic plan
  • Pro plan: $119.99 per person per year
  • Teams plan starting from $300 per year for groups of five
  • 30-day free trial
Limitations
  • Not suitable for professional graphic designers requiring a more advanced and comprehensive tool
G2 rating
  • 4.7 out of 5 (4,400+ reviews)

Our AI services

Itransition provides comprehensive AI services and solutions to help businesses across industries optimize their social media strategies and marketing initiatives.

Our AI services

We offer expert guidance in implementing AI-based solutions and overcoming potential project challenges.

  • Evaluate your corporate goals, business processes, and current tech ecosystem
  • Define the solution’s functional and non-functional requirements
  • Assist with data requirements definition, data mapping, and data quality assessment
  • Design the architecture of your software
  • Identify the tech stack, including algorithms and AI/ML services
  • Set up a development roadmap covering key stages like PoC, MVP, and full-fledged product releases
  • Establish an AI deployment strategy and select a suitable hosting environment
  • Create a maintenance plan and continuous improvement strategy

We build solutions powered by AI algorithms and trained on large and reliable data sets to ensure their optimal performance.

  • Prepare ETL pipelines to gather data from multiple sources and consolidate it in a centralized repository
  • Execute data pre-processing, including data cleansing, annotation, and transformation
  • Train one or more AI models and integrate the one producing the desired output into the solution
  • Equip the AI solution with a variety of security features to protect your data assets
  • Integrate the solution with third-party software and corporate systems
  • Perform end-to-end testing combining test automation tools and manual reviews
  • After deployment, enhance the solution over time via model retraining and additional features

Partner with Itransition for your AI project

Get in touch

Challenges & tips for adopting AI in social media

Concerns

Recommendations

AI reliability & bias

Concerns

AI algorithms and their models are far from 100% accurate and can feature biases. In the social media sphere, this can result in unfair content moderation, such as incorrect YouTube video takedowns. 

When prioritizing certain parameters over others, biases can also lead to prejudicial content recommendations. For instance, according to the WSJ’s Facebook Files, Facebook’s algorithm has been promoting controversial content to boost engagement, spreading misinformation and creating a toxic virtual environment.

The well-known “black-box” nature of AI (no one fully understands how algorithms reach a certain conclusion) raises questions about the transparency and explainability of the decision-making process.

Concerns

Recommendations

AI systems’ performance depends on the quality of training data. Careful data mapping, integration, preparation, and feature selection can help create reliable, diversified training sets that represent social media’s user base. Fairness-aware machine learning techniques can mitigate algorithmic bias. These include, for instance, reweighing, a pre-processing technique that assigns different weights to each data set point, altering the relevance of protected attributes. AI model performance typically degrades over time because of progressive changes in input variables and their relationships. You can address this phenomenon, called model drift, through integration of special metrics and multiple retraining iterations with new data. Some of the best-performing algorithms, including deep neural networks, are also the least explainable due to their sprawling architectures. Their usage should be approached with due care and limited to specific tasks. AI systems work best in combination with human supervision. For instance, AI-based content moderation should be complemented by effective reporting and appeal mechanisms to provide human feedback.

Privacy, security & ethics

Concerns

Social media’s intrusive access to vast amounts of user information, together with AI’s notorious hunger for data, is raising concerns about data privacy and security among policymakers and the public. Numerous institutions have questioned social media's ethical standards in terms of data usage. The infamous Facebook-Cambridge Analytica scandal, for example, proved how personal data could be weaponized by insidious powers.

Concerns

Recommendations

Any social media platform or social media management and marketing software should operate in strict compliance with major data management standards and applicable legislation. They should also implement solid security features, including multi-factor authentication, to mitigate cyber risk exposure. Social media service providers should be transparent about how personal data is handled, allowing users to control their data privacy settings or even opt out of data collection via consent management features. Data masking and anonymization techniques can obscure or remove sensitive and confidential details from user data, offering a reasonable compromise between privacy and the need to train AI models for analytical purposes.

AI & social media data: a perfect match?

The combination of AI's data-driven nature and social media's boundless pool of personal information has proven to be highly beneficial for both users and platforms. We can say that most of social media's success in connecting people, digital content, and brands comes from this union. At the same time, such a symbiosis has generated several controversial issues, showing how AI technology is prone to be abused when implemented improperly. To maximize the benefits of AI for your business and customers while overcoming potential adoption challenges, you can turn to Itransition's developers and consultants.