Meta Builds Arena Prediction App for 100 Million Users as It Sidesteps Real-Money Bets
Updated
Updated · Built In · Jul 8
Meta Builds Arena Prediction App for 100 Million Users as It Sidesteps Real-Money Bets
2 articles · Updated · Built In · Jul 8
Summary
Arena, now in internal testing, would let users wager virtual “play money” on politics, sports, finance and entertainment, with Meta targeting 100 million monthly “predictors” aged 18 to 34.
Meta is using its Llama AI to generate markets from trending topics, personalize recommendations and resolve outcomes in near real time, making the app a more social alternative to Kalshi and Polymarket.
The company is keeping Arena separate from Facebook and Instagram at first, but plans could later weave betting into Messenger, WhatsApp, Stories and Reels through chats, sharing tools and leaderboards.
Play-money betting helps Meta pursue engagement while avoiding immediate regulatory risk in a sector facing dozens of legal challenges, even as Kalshi and Polymarket processed a combined $50 billion in 2025 trades.
The push shows Meta chasing one of the internet’s fastest-growing formats, though the project remains unannounced, may never launch publicly, and is already drawing ethical criticism from employees and Senator Richard Blumenthal.
Besieged by lawsuits, can Meta's controversial new prediction market app save the company from its AI struggles?
As AI's energy demand explodes, are big tech's climate pledges now simply impossible to achieve?
Is nuclear power the unavoidable answer to AI's insatiable appetite for electricity?
Meta's $145 Billion AI Reorientation: 2026 Layoffs, Cloud Computing Entry, and Prediction Market Disruption
Overview
In May 2026, Meta launched major layoffs as part of a deliberate restructuring, signaling a strong shift toward artificial intelligence. This move reflects broader tech industry trends, with companies reallocating resources to focus on AI development. Meta is now investing heavily in building its own AI models, moving away from reliance on external providers like Google’s Gemini and instead using its proprietary Muse Spark model. These changes have affected employee morale and sparked internal discussions, highlighting the challenges of rapid transformation as Meta aims to strengthen its internal AI capabilities and adapt to a fast-evolving digital landscape.