How Social Media is Changing in the Face of AI 

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Artificial intelligence (AI) has been used in social media for years.

But recent AI advances and technology shifts are leading to new uses and challenges that are changing social media platforms, how brands use AI with social media, and users’ experience with social media.

In this post, here are some current trends and challenges revealing how social media is changing.

More personalized content

Social media thrives on providing a user-friendly and enjoyable experience. This is increasingly done by AI-driven personalized content recommendations. 

Since the algorithm can process large amounts of data in real time, it analyzes a user’s data, like their interactions and browsing history, preferences, and online behavior to help provide and recommend more personalized content. 

The personalization is designed to help users save time and effort, so they don’t have to search manually for what they’re interested in. It also improves their experience, keeps them engaged on the platform, and can help conversion rates.

For instance, let’s use the example of  TikTok’s For You page. TikTok FYP determines what’s featured based on various weighted signals, such as hashtags, songs, whether the video was watched completely, and more. 

So, if you watched and commented on a few DIY air fryer cooking videos, you’ll start seeing more information on air fryers, air fryer recipes, and other related topics being suggested on your social media platforms and feeds. Alternatively, if you watch videos by a particular music group, you’ll start seeing more of that content showing up in your feed as well as related or similar content.  

AI for moderation 

Social media networks depend on user-generated content. But moderating content can be challenging as you need a way to protect your users from harmful content, like hate speech, misinformation, or cyberbullying. 

You also want to ensure you follow all laws and regulations and maintain your reputation. 

AI content moderation tools can be used to help detect inappropriate content through algorithms and rules you establish. It can automatically monitor and filter content, including images, text, and videos, and remove offensive, inappropriate, or other content that doesn’t abide by your terms.

When using AI content moderation, you will want to be transparent with your users, so they’re clear on the acceptable and unacceptable terms, like privacy, access to information, and terms of speech.

AI algorithms to identify potential influencers

Influencer marketing is a big business, with it expanding into a $16.4 billion industry in 2022. It’s an effective marketing tool, helping many brands generate sales and conversions.

Yet it also comes with some concerns and challenges. Brands need to find influencers that are the right fit for them and their audience. Additionally, there’s also concern about influencer fraud, which can result in wasted marketing budget. 

Influencer fraud can occur when an influencer buys fake followers or falsifies engagement rates. This can leave the brand with a poor return on investment and content that may not align with the brand.

However, AI algorithms can address these issues, so you can find the right influencers for your brand and weed out fake influencers.

For instance, it can analyze campaign metrics and performance, like traffic, brand mentions, and conversions, to provide brands insights on what content is working and ways to further optimize campaigns moving forward. 

AI tools can also provide predictive abilities to help brands evaluate which influencers may be better to work with — eliminating some of the trial and error and searching involved in finding influencers. 

AI can also assist with identifying fraudulent influencers. For instance, AI can gather an analysis of the influencer, including engagement rate, audience demographics, and more. Additionally, AI can help you assess an influencer’s growth over time, so you can evaluate whether the growth looks natural or not. 

The rise of deepfakes

As AI technology has advanced, it’s becoming more widespread and easier to use. It also can mimic reality better. 

These AI-generated realistic but fake videos and memes are often called deepfakes. While they’ve been around for a while, it’s getting harder for even experts to spot the fakes. 

This is problematic because it can lead to misinformation, where people see a video that’s AI-generated but believe it’s real. 

And deepfakes can have a significant negative influence, especially those that are popular and get passed around. Many users will believe the information, share it, and not realize it’s false. 

For instance, two videos supposedly of news anchors for a news outlet called Wolf News don’t actually show real people. According to an article in the New York Times, these AI-created videos were distributed by pro-China bot accounts on Facebook and Twitter to influence users.

Additionally, there’s concern about how false, AI-generated videos may be used to spread misinformation in the upcoming 2024 US presidential election. 

Sentiment analysis

AI-driven sentiment analysis can help brands discover and assess how people and customers feel about their brand by tracking online conversations in real-time.

Sentiment analysis tools collect and analyze information on how people are discussing your brand on social media. Instead of counting comments or mentions, these tools focus on understanding the emotions and opinions (also called opinion mining). AI advances, especially predictive analytics, make this process easier.

For example, AI tools can analyze comments to assess for a positive or negative sentiment. Tools may also track emotions over time, helping brands assess ongoing trends or see sudden changes. 

Then, if you have a spike in mentions due to a flurry of negative posts, the AI tools can alert you. So you can investigate the reason for the change and address the situation as needed.

Monitoring sentiment analysis can also help you:

  • Address and resolve posts about customer support issues, ideally so the customer is happy and other visitors can see the positive outcome
  • Gain insights into what your ideal audience wants, which can help you improve your brand messaging and content on social media
  • Identify your niche and ideal audience so you are providing the right content

For instance, the company, Underknown, changed the focus of a YouTube channel they had launched after analyzing their data. They discovered that videos focusing on survival received more positive responses. Using this information, they switched their strategy, content, and relaunched the channel — resulting in a successful channel with more followers.   

Rise of augmented reality filters

Augmented reality (AR) is technology that superimposes AI-generated images and graphics on what you see in the real world. 

One popular example of this technology in action was the Pokemon Go craze in 2016. The app allowed people to look for Pokemon in your area, neighborhood, and other real-world locations. This app incorporated AR technology by overlaying digital images of Pokemon on what your smartphone camera sees.

A popular use of AR on social media is through filters. These filters and the effects you can use continue to advance and become more sophisticated, allowing users more options and capabilities. For instance, AR filters allow you to change your appearance, age your face, apply beauty filters, add virtual makeup, and other effects.

People enjoy using the filters to create lighthearted, fun, and funny images. Incorporating AR filters can:

  • Create a positive user experience
  • Increase user engagement
  • Provide an interactive experience

Algorithmic bias and transparency

While AI can be useful, it’s also important for brands to understand the potential for algorithmic bias.

Essentially algorithmic or AI bias occurs when the decisions the AI makes are systematically unfair to certain groups of people. These biases may occur around gender, race, ethnicity, sexual orientation, or other groups.

For instance, a 2023 article by The Guardian highlighted how AI algorithms rated photos of women as more sexually explicit than those of men.

This is important for brands to consider because these types of algorithmic biases can suppress groups of people, negatively impact campaigns focusing on systemic injustices, and hurt certain brands, such as those that serve underrepresented groups. 

You also could find your content being shadowbanned or suppressed based on an image that AI deems inappropriate, even if it’s not. 

At present, there is no one way to perfectly combat bias in AI algorithms. However, continuing to push for and provide transparency and insight into the algorithms used in social media can help. Having companies be accountable for the impact the algorithm has on society and requiring regulations and standards may also help.

Improving auto-captioning and translation

Advances in AI technology have also helped social media provide a more accessible experience for individuals who speak different languages or have a disability.

For instance, AI can help automatically create captions and subtitles due to advances in its ability to analyze language in video content. This can make watching videos more enjoyable and easier for people, even those who want to watch a video with the sound off.

On some social media sites like YouTube, you can even have the automatic captions translated into a different language — in real-time. These types of advances can eliminate language barriers and allow a greater audience reach that’s not impacted by language.


In conclusion, recent AI advancements are reshaping the social media landscape. These changes are revolutionizing how brands utilize AI, altering social media platforms, and transforming users’ experiences.

The fusion of AI and social media presents new opportunities and challenges that demand careful consideration to ensure ethical practices and meaningful connections in this evolving digital realm.


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