“We doubled the length of user interaction sequences we use for training on Instagram in Q1 and increased the richness of how each user interaction is described,” Susan Li, Meta’s Chief Financial Officer (CFO), said during Meta’s Q1FY26 earnings call. The change means Meta’s systems are now trained on longer user histories and more detailed interaction signals, enabling a clearer understanding of user interests.
Li said this has already been translated into gains, with ranking improvements driving a “10% lift in Reels time spent” on Instagram and an increase of “more than 8%” in Facebook’s global video time, marking the largest gain in four years.
Recommendation systems are getting more exact: Same-day posts now account for “more than 30% of recommended Reels” on Instagram and Facebook, more than double the level a year ago. Li said the company is “making several investments we expect will deliver more valuable recommendations,” including scaling model size and complexity and “incorporating LLMs to deepen content understanding across our platform.” Over half a billion users on Facebook and Instagram now watch AI-generated videos each week.
Mark Zuckerberg, Meta’s Chief Executive Officer (CEO), said, “For the first time in Meta’s history, we’re going to be able to develop a first-principles understanding of what you care about and what each piece of content in our system is about.” Li added that Meta is redesigning its content retrieval system to “show more content that matches the full range of a user’s interests” and refining “LLM-based tune-your-algorithm features” that allow users to give natural-language feedback on what they want to see more or less of.
Meta experimenting with LLM-based recommender systems: The CFO further said, “This includes building foundation models that power organic content and ads recommendations, as well as developing LLM-based recommender systems. Our focus this year is validating the model architectures and techniques in these domains before we scale them out in future years.”
Muse Spark rollout: Zuckerberg said, “Our biggest milestone so far this year has been the release of our Muse family of models and our first model, Muse Spark.” He added that this was “the first release from Meta Superintelligence Labs” and that the company is “already training even more advanced models.”
Muse Spark now powers Meta AI “in direct chat threads across our Family of Apps, as well as the standalone Meta AI app and website.” Meta said testing showed “meaningful engagement gains” that “accelerated week-over-week,” and the rollout has led to “double-digit percent increases in Meta AI sessions per user.”
Personal and business agents: Zuckerberg stated that “our goal is not just to deliver Meta AI as an assistant, but to deliver agents that can understand your goals and then work day and night to help you achieve them.” He added, “We are building a personal agent” and “we are also building a business agent focused on helping entrepreneurs and businesses across the world use our tools.”
Meta said weekly conversations with business AIs have grown from 1 million at the start of the year to more than 10 million. Li said these tools are “currently free for most businesses,” and that Meta expects to “work towards establishing a longer-term monetization model.” Zuckerberg added that “people are going to also be willing to pay a lot of money to have premium or high compute versions of it.”
AI in advertising: Li said Meta is “introducing Meta ads AI connectors in open beta,” allowing advertisers to connect their ad accounts directly to AI agents. The Meta AI business assistant has been “fully rolled out to all eligible advertisers,” resolving account issues at a “20% higher rate.”
More than 8 million advertisers are using at least one generative AI ad tool, and advertisers using video generation are seeing “more than 3% higher conversion rates.” Meta’s Adaptive Ranking Model, described as an LLM-scale system with “a trillion parameters,” routes requests to more compute-intensive models when the probability of conversion is higher. This drove a 1.6% increase in conversion rates across Facebook and Instagram.
Layoffs planned despite gains: Li pointed out, “We ended Q1 with over 77,900 employees, down 1% from Q4 as the impact of headcount optimization efforts in certain functions was partially offset by hiring in priority areas of monetization and infrastructure.” She also noted internal plans to “reduce the size of our employee base in May,” as the company shifts “substantial investments” towards AI and infrastructure.
Manus deal and legal scrutiny: Responding to a question on Manus, Li said, “We’re still working through the details. So we don’t have an update right now.” This is after the Chinese government blocked the Meta-Manus deal in April.
Furthermore, Meta acknowledged legal and regulatory scrutiny on youth-related issues. Li said, “We continue to see scrutiny on youth-related issues and have additional trials scheduled for this year in the US, which may ultimately result in a material loss.” Notably, Meta lost a significant case in March this year, where a jury held it liable for intentionally designing features that led to social media addiction in teens.
Operational metrics: Meta reported that Family daily active people (DAP) averaged 3.56 billion in March 2026, up 4% year-on-year, with a slight quarter-on-quarter decline due to “internet disruptions in Iran” and “a restriction on access to WhatsApp in Russia.”Ad impressions across its Family of Apps increased 19% year-on-year, while the average price per ad rose 12%.
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