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Generative AI: 2 Ways Social Platforms Can Integrate it

Here are some ways AI could help social media users achieve more valuable goals


Enerative AI processes, such as image and word production, do not mesh well on social platforms, which are inherently defined by human, “social” experiences.

And they surely are trying:

Social Media Apps utilizing AI

  • Meta intends to integrate AI through celebrity-influenced chatbots, a new feature that allows users to create your own artificial intelligence friend in its apps, and picture generating options on both Facebook and Instagram.
  • LinkedIn has integrated AI post generation, as well as other job posting and advertising-related features. And, although artificial intelligence marketing tips make sense in light of engagement trends, post generation appears nearly anti-social and counterintuitive for social apps.
  • X has brought its Grok artificial intelligence chatbot to the main app UI and is working on a way to integrate Grok directly into the composer, allowing you to publish AI-generated text as updates.
    Snapchat has a chatbot called ‘My AI’ in user inboxes, and it is also experimenting with profile image generation and digital pets.
  • X has brought its Grok artificial intelligence chatbot to the main app UI and is working on a way to integrate Grok directly into the composer, allowing you to publish AI-generated text as updates.
  • Snapchat has a chatbot called ‘My AI’ in user inboxes, and it is also experimenting with profile image generation and digital pets.
  • TikTok also features generative AI profile photos, and it is experimenting with text-to-video, AI music generation, and chatbots for a variety of purposes.

All of them are intriguing choices, with varied degrees of value and functionality. However, few of them genuinely improve the social interaction experience, and so are not well aligned with the fundamental use case of social apps.

Of course, that definition is shifting as more individuals use social applications for amusement rather than communicating with friends. Even still, the relevance of the current wave of AI tools within social apps is disputed, and none of these capabilities appear to constitute key functionality of any of these apps.

Is it worth it?

They actually have to justify the cost of offering such services. Generative AI is expensive owing to the processing needs at scale, and while these new features allow social applications to ride the AI wave, they are unlikely to have a significant impact on their primary business.

Ads are an exception, and as previously stated, there is significant value in having AI ideas and platform-specific training to help optimize your promos.

But for everyday users, are these possibilities really going to make you utilizing any of these apps more often?

At the same time, generative artificial intelligence is the current trend, and every app is anxious that its competitors may develop a killer use case for it and outperform their product.

So, what can generative artificial intelligence be utilized for in social apps, and how might these technologies deliver value that is more aligned with their primary use case?

Here are some ways artificial intelligence could help social media users achieve more valuable goals.

Graph Search with AI


“Graph Search” was a natural language-based Facebook search engine that helped you learn more about people and trends in the app.

As demonstrated in this example, Graph Search was specifically built to make it easy to discover relevant information in the app without the need to comprehend Boolean search strings.

That’s pretty much how Facebook marketed it back in 2013.

“Graph Search and web search are very different. Web search is designed to take a set of keywords (for example: “hip hop”) and provide the best possible results that match those keywords. With Graph Search you combine phrases (for example: “my friends in New York who like Jay-Z”) to get that set of people, places, photos or other content that’s been shared on Facebook. We believe they have very different uses.”

Graph Search was quite useful for discovering interest correlations and insights, but it also revealed some data points that Facebook wasn’t entirely happy with.


Given the greater drive for data protection, particularly after the Cambridge Analytica affair, Facebook eventually eliminated the option. But, in reality, Graph Search sounds a lot like ChatGPT, in that it allows for more advanced discovery in a conversational setting, which could open up new avenues for similar insight.

TikTok is already exploring this with its Tako chatbot experiment and generative AI search in the Chinese version of the app.


This more advanced search function finds matches both within TikTok and beyond the web, delivering more detailed insights and matches for queries while keeping the user in-app.

Facebook might consider doing the same, using publicly displayed Facebook profile information to improve search functionality in the app.

For example, you can ask it questions like:

What is today’s top trending news story on Facebook?
What news stories are my friends most interested in on the app?
Which restaurants in [city] have received positive reviews from my friends?
Which of my previous classmates have I not yet connected with?

These are all quite typical Facebook use cases, but you have to look around a little to obtain this information. Graph Search addressed this to a considerable extent, and a customized AI chatbot might go even farther by providing natural language search, which would increase user engagement.

Source content references

One of the most pressing challenges with social media usage is the spread of disinformation, which may reach considerably more people through social post sharing.

Platforms have attempted to address this by including fact-checking tools and allowing users to raise issues about the legitimacy of statements. However, an AI fact-checking tool could be useful not only as a fact-checker, but also as an immediate reference tool for double-checking problematic statements.

The process would include a button on all posts that you could use to ask questions about any claims made in the post text.

Let’s imagine there’s a post that says “climate change is not real”. You may use the AI button to search for information on the internet to quickly determine whether that assertion is correct.

If a post declared that “[random celebrity] has died”, you would have an immediate chance to explain without having to open a new window, and you could even ask the bot follow-up questions to address any additional issues you may have.

It’s a less attractive application of AI, but it might be a useful tool for reducing the spread of disinformation through real-time fact-checking.

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