Prediction markets are not just for betting. They are becoming a valuable source of predictive data for enterprises, as shown by new partnerships with media giants like CNN and CNBC. This dual-purpose model, functioning as both a consumer product and a B2B data service, creates two distinct revenue streams.

The primary value for the vast majority of prediction market users isn't trading but consuming the market's data as a form of real-time, aggregated news. This reframes the user base as a media audience of 'lurkers' rather than a community of active traders.

There is emerging evidence of a "pay-to-play" dynamic in AI search. Platforms like ChatGPT seem to disproportionately cite content from sources with which they have commercial deals, such as the Financial Times and Reddit. This suggests paid partnerships can heavily influence visibility in AI-generated results.

Prediction markets like Polymarket operate in a regulatory gray area where traditional insider trading laws don't apply. This creates a loophole for employees to monetize confidential information (e.g., product release dates) through bets, effectively leaking corporate secrets and creating a new espionage risk for companies.

Foreign adversaries, particularly from the Middle East and China, are weaponizing political prediction markets. By funding ads that display skewed betting odds, they aim to create a false sense of momentum or inevitability for a candidate, representing a novel and subtle form of election interference designed to sow division.

The true value of prediction markets lies beyond speculation. By requiring "skin in the game," they aggregate the wisdom of crowds into a reliable forecasting tool, creating a source of truth that is more accurate than traditional polling. The trading is the work that produces the information.

Satirical examples of using prediction markets to replace DoorDash or Tinder reveal a core flaw in their utopian vision. Applying these financial models to everyday life can create bizarre and perverse incentives, highlighting the absurdity of a one-size-fits-all solution.

Prediction markets are accelerating their normalization by integrating directly into established ecosystems. Partnerships with Google, Robinhood, and the NYSE's owner embed gambling-like activities into everyday financial and informational tools, lowering barriers to entry and lending them legitimacy.

Terry Duffy distinguishes between large-scale political events like a presidential election and smaller, local races. He argues that a prediction market on a local mayoral race with only a few hundred voters could be easily manipulated, as an actor could potentially buy the election to ensure their market prediction pays off.