More tech layoffs in 20​26 than in 2025?

Prediction market odds on Kalshi currently reflect 88.5% probability of more tech layoffs in 2026 versus 2025. This contrasts with traditional analyst forecasts, which often rely on survey data and historical hiring trends. Prediction markets aggregate real-money bets from traders with direct exposure to tech employment, potentially capturing forward-looking sentiment faster than consensus analyst views. Comparing market odds to published tech sector employment reports and investment bank guidance can reveal whether traders expect conditions to deteriorate beyond mainstream expectations.

On Kalshi, this outcome is priced at 88.5%, meaning traders collectively assess a 88.5% likelihood that 2026 will see more tech layoffs than 2025. On Kalshi, prices reflect that venue's order book, liquidity, and how traders price the outcome right now. The price reflects continuous order-book matching and reflects real-time updates as new labor data, earnings calls, and macroeconomic indicators emerge. Traders can buy or sell shares representing this outcome, with the price fluctuating based on supply and demand. Higher prices indicate stronger conviction that layoffs will increase year-over-year.

The market resolves on Mar 1, 2027. Resolution depends on comparing the total number or scale of tech sector layoffs announced or executed in calendar year 2026 against those in calendar year 2025. Traders should monitor official labor statistics, company announcements, and industry reports as the resolution date approaches. The specific criteria for what counts as a tech layoff and how comparisons are measured will be defined by the market's resolution rules, which traders should review before placing positions.

Key catalysts include macroeconomic data such as GDP growth, inflation, and interest rate decisions that influence corporate hiring freezes and restructuring plans. Tech earnings reports and management commentary on headcount plans directly signal layoff intentions. Regulatory changes affecting tech sectors like AI, data privacy, or antitrust could trigger workforce reductions. Geopolitical tensions or supply-chain disruptions may accelerate cost-cutting. Historical layoff announcements and workforce reduction guidance from major tech firms will shape trader expectations. Labor market strength or weakness in adjacent sectors may also influence tech employment decisions heading into 2026.