Meta Is Doubling The Amount Of AI Recommendations In Your Feed

May 4, 2023

Meta (formerly known as Facebook) has recently announced that they’re on track to double the number of AI recommendations in user feeds by July 2023.

Currently, over 20% of the content in Facebook feeds and 40% in Instagram feeds are recommended by AI systems. This shift towards AI recommendations reflects the changing landscape of social media, with platforms like TikTok focusing on individual post content rather than social connections.

In the same report that noted the rise of more AI-recommended content being shown to users, it was also disclosed that while Facebook users are viewing more content, they’re also posting fewer updates themselves, and personal sharing has increasingly shifted into DMs.

This means the shift to AI could provide some level of advantage to brands by allowing the best content to reach greater audiences in the app. The challenge is that you should no longer maximize social engagement or interactive value, but instead focus on entertainment.

The report also suggests that brands should be far more focused on creating quality Reels for a higher chance to take advantage of the more frequently served AI-recommended content. Meta says that Reels has seen a 24% increase in total time spent on Instagram.

This means creating good, entertaining content, especially in Reels, which means you stand a good chance to get more reach in either app, with its algorithm now looking to showcase more content to people outside your direct audience.

Reels that are aligned with your target audience’s interest are a key tactic to not only be recommended in other feeds by AI but also get shared by other users, with Meta also noting that users are now resharing Reels more than 2 billion times every day, a 100% increase over the last six months.

While it can seem frustrating at times that Meta is leaning towards not showing your followers your content, there are always opportunities to reach a broader audience than you have already established by working towards Meta recommendations and following how the algorithm works.

About the author 

Sam King

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