Meta Platforms (META) Morgan Stanley Technology, Media & Telecom Conference 2026 summary

Strategic review and business performance

• Over the past year, the core business has remained robust, with continuous improvements in both organic content and ad monetization, driven by a measurement-focused investment process.

• AI initiatives have accelerated, with significant talent acquisition and the formation of a leading AI research and product team, aiming to push the frontier of foundation models and product experiences through 2025 and beyond.

• Infrastructure capacity planning has evolved, with ongoing expansion of data centers and cloud capacity to meet growing AI training and inference needs, with some projects not coming online until 2027 or later.

• The company is leveraging scenario analyses to forecast capacity and ROI, balancing science-driven budgeting for core needs with more artful predictions for emerging AI-driven products and experiences.

• Custom silicon is being deployed at scale for ranking and recommendation workloads, with plans to expand its use to AI model training for greater cost efficiency.

AI, LLMs, and product innovation

• AI and LLMs are being used to enhance content understanding and recommendations, with Threads leading in LLM integration due to its text-based nature.

• Recent product launches, such as improved ranking on Facebook, have driven a 7% lift in organic content views, and Instagram saw a 3% conversion lift from compute-efficient ad improvements.

• The company is merging research efforts across ads and discovery to build unified foundation models, with LLMs being fine-tuned using engagement data for future gains.

• There is a strong focus on making existing products better with AI, viewing this as a massive opportunity, while also preparing for new AI-native experiences like business agents.

• Meta AI, despite not being on a state-of-the-art model, already serves over 1 billion users, and future innovation is expected to leverage the company’s distribution and personalization strengths.

Monetization, open source, and future outlook

• Open source remains a nuanced strategy, with decisions made model by model; monetization is expected to come primarily from enhanced consumer experiences across the family of apps.

• The evolution of content—from text to short-form video and toward interactive, AI-assisted experiences—is seen as a key driver of future engagement and revenue.

• Individualized ads and streamlined advertiser experiences are priorities, with AI enabling more relevant and adaptive ad delivery.

• The company anticipates that AI-powered business agents will become commonplace, and is investing in scaling promising acquisitions like Manus.

• Internal adoption of AI tools has led to significant productivity gains, with an 80% increase in coding productivity, and ongoing efforts to ensure the company remains competitive with AI-native startups.