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Meta says its AI is making you spend more time on Instagram
Time on the app grew by double digits last quarter, Meta says, driven by more personalised recommendations, even as the company faces lawsuits over exactly that design. Meta says people are spending more time on Instagram, and it credits its artificial intelligence for the increase. Global time spent on the app grew by double digits year on year in the second quarter, the company told investors, driven by AI-tuned recommendations in the main feed and in Reels. The gains are specific enough to be measured. Meta said a reworked Reels system lifted sessions by 15 basis points, a small-sounding figure that, across billions of users, translates into a meaningful amount of extra attention captured. The pattern holds across Meta's apps. Video time has surged on both Instagram and Facebook, the company said, as short-form recommendations pull users from the feeds they follow toward an endless stream the algorithm assembles for them. Mark Zuckerberg described the change as more personal, not just more. "Our recommendations are also becoming more personalized, surfacing more fresh content while giving people more direct control over what they see," he said, pairing the engagement gains with a nod to user choice. The technical shift underneath is notable. Zuckerberg said Reels now combines faster inference with a new architecture that draws on a deeper history of what each user has done, letting the system predict more accurately what will keep them watching. Meta has also turned large language models loose on its own feed. The company now runs every public Reel and post through an LLM to analyse its topic and tone, which Zuckerberg called "a key building block toward greater personalization," with plans to extend it to Facebook. The purpose is plain enough. Understanding content more deeply lets Meta match it more precisely to each viewer, and more precise matching means more time spent, the metric on which its advertising business ultimately rests. That is where the achievement becomes uncomfortable. The same design Meta celebrates as personalisation is the one that regulators and litigants describe as engineered compulsion, especially where younger users are concerned. The lawsuits are not abstract. Meta booked a $2.4 billion legal charge in the quarter, and a group of US states is pressing claims that its products are built to keep young people hooked, litigation that turns "time spent" from a boast into evidence. Meta's answer is that control comes with the engagement. Executives point to settings that let users tune their own algorithms and to teen-specific protections rolled out across its apps, arguing that more personalisation need not mean less agency. Critics see the two claims as hard to hold together. A system optimised to maximise time spent, they argue, is not neutral about what a user "chooses," and the controls sit on top of an engine designed to keep people scrolling. For the business, though, the direction is unambiguous. Engagement is the raw material of Meta's ad machine, and anything that reliably lifts it, especially AI that does so at scale, is exactly what the company has been spending tens of billions to build. More time also means more inventory. Every extra minute of scrolling is another slot Meta can sell to advertisers, which is why engagement gains translate so directly into the revenue that funds everything else. It also helps explain the spending. Meta's enormous AI capex is often framed around future agents and superintelligence, but the clearest near-term payoff is this, a recommendation system that already measurably increases how long people stay. The tension will follow Meta into court and onto the balance sheet. The AI that lifts engagement is both its best answer to investors asking where the returns are and its worst evidence in cases asking whether those returns come at users' expense. For now, the number is going up. People are spending more time on Instagram, Meta knows exactly why, and the same fact that reassures Wall Street is the one its opponents intend to use against it.
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Meta used AI to make your Instagram feed harder to quit
Meta says its latest AI recommendation sytems are keeping people on Instagram longer by serving up more relevant Reels and Feed posts. Caught yourself scrolling on Instagram a lot longer lately? You're not imagining it. Meta just told investors what's driving that trend, and AI is at the center of it. During its second-quarter earnings call, Meta said time spent on Instagram grew by double digits year over year after rolling out new AI-powered recommendation systems. According to the company, the biggest gains came from improvements to how it recommends Reels and other public content, making it easier to surface videos people are more likely to watch. Every public post gets an AI read first Meta's recommendation systems now do more than track likes or watch time. According to Chief Financial Officer Susan Li, Meta has trained large language models to read what a Reel or Feed post is actually about, down to its topic and tone, and pair that understanding with a deeper read on each user's viewing history to predict what they'll watch next. Li said Meta hit a milestone earlier this year, when every public Reel and Feed post on Instagram started getting automatically processed through an LLM. The company is extending the same process to more parts of Facebook, and it has also started using a separate model family, called Muse, to analyze videos for automatic topic classification and summarization. Recommended Videos This implementation appears to have worked in Meta's favor. Li said Meta's largest single Reels ranking update to date drove a 15 basis point increase in sessions, with the biggest gains in reshares and time spent. Meta is now rolling the same approach out to the main Feed. Better recommendations mean stickier feeds For Meta, this AI-based approach makes sense. Better recommendations keep people on the app for longer, help creators reach bigger audiences, and create more room for ads. For Instagram users, the implications are harder to ignore. The better the platform gets at predicting what you'll watch next, the harder it becomes to stop scrolling.
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Meta revealed during its Q2 earnings call that Instagram users are spending significantly more time on the platform, driven entirely by AI-powered recommendation systems. Global time spent on Instagram grew by double digits year over year in the second quarter, with Meta crediting AI-tuned recommendations in the main feed and Reels. The company now processes every public post through large language models to analyze content and match it to users, though this success arrives amid lawsuits alleging the platform is engineered to keep young users hooked.
Meta has confirmed that Instagram users are spending significantly more time on the platform, and the company attributes this increase directly to its artificial intelligence systems. During its Q2 earnings call, Meta disclosed that global time spent on Instagram grew by double digits year over year in the second quarter, driven primarily by AI recommendations in the main feed and Reels
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. The gains are measurable and substantial. Meta reported that a reworked Reels system delivered a 15 basis point increase in sessions, a figure that translates into millions of additional hours of attention captured across billions of users1
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Source: The Next Web
The technical architecture behind this shift is sophisticated. Mark Zuckerberg explained that Reels now combines faster inference with a new architecture that draws on a deeper history of what each user has done, allowing the system to predict more accurately what will keep them watching
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. This represents Meta's most significant Reels ranking update to date, with the biggest gains observed in reshares and time spent2
.Meta has deployed large language models across its platforms in a way that fundamentally changes how content reaches users. According to Chief Financial Officer Susan Li, Meta hit a milestone earlier this year when every public Reel and Feed post on Instagram started getting automatically processed through an LLM
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. These models analyze each post's topic and tone, then pair that understanding with a deeper read on each user's viewing history to predict what they'll watch next2
.Zuckerberg described this LLM integration as "a key building block toward greater personalization," with plans to extend the same approach to Facebook
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. Meta has also started using a separate model family called Muse to analyze videos for automatic topic classification and summarization2
. The purpose is clear: understanding content more deeply lets Meta match it more precisely to each user, and more precise matching means more time spent, the metric on which its advertising business ultimately rests1
.For Meta's business model, increased user engagement translates directly into ad revenue opportunities. Every extra minute of scrolling represents another slot Meta can sell to advertisers, which explains why engagement gains matter so much to the company's bottom line
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. The AI-powered recommendation systems are delivering the clearest near-term payoff for Meta's enormous AI capital expenditure, which is often framed around future agents and superintelligence but shows measurable returns today1
.Video analysis has become central to this strategy. Video time has surged on both Instagram and Facebook as short-form recommendations pull users from the feeds they follow toward an endless stream the algorithm assembles for them
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. This shift from chronological, follower-based feeds to algorithmically curated content represents a fundamental change in how people experience Meta's platforms.Related Stories
The same design Meta celebrates as personalization faces intense regulatory scrutiny. Meta booked a $2.4 billion legal charge in the quarter, and a group of US states is pressing claims that its products are built to keep young people hooked
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. The lawsuits turn "time spent" from a business achievement into potential evidence of engineered compulsion, especially concerning younger users1
.Meta's response emphasizes user controls. Executives point to settings that let users tune their own algorithms and to teen-specific protections rolled out across its apps, arguing that more personalization need not mean less agency
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. However, critics argue these two claims are difficult to reconcile, noting that user controls sit on top of an engine fundamentally designed to maximize scrolling1
. The AI that lifts engagement serves as both Meta's best answer to investors asking where returns are and its most problematic evidence in cases questioning whether those returns come at users' expense1
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