The prediction markets are catching on with Wall Street interns

Morgan Stanley surveyed over 500 summer interns about their habits, including AI use and betting. While AI use has surged, more than 60% of interns expressed worry about job replacement. A quarter of interns said they had used a prediction market app in the past year, with Kalshi and Polymarket leading the pack. These intern surveys, conducted by Morgan Stanley's equity research team, included questions about AI use and betting habits for the first time this year.

In a national survey conducted by The Harris Poll, 21% of adults between 18 and 34 reported using a prediction market platform, which is consistent with the intern survey's findings. The use of prediction market apps is increasingly scrutinized, as some states have taken legal or regulatory action against them, and certain companies have restricted employee access.

Morgan Stanley's code of conduct does cover trading and investing topics, including prediction markets, but the specifics were not disclosed. Kalshi's head of institutional mentioned the company's efforts to attract Wall Street firms, highlighting the platform's appeal as a data source for investors. However, concerns over insider trading and limited regulation persist.

The survey also revealed that interns are excited and anxious about AI, with 68% saying they use an AI tool daily, up from 35% last year and 14% in 2024. AI is transforming entry-level roles on Wall Street, which have traditionally been filled with menial tasks that are ripe for automation. Around 70% of interns said they personally subscribe to paid versions of AI tools, up from 52% the previous year.

They primarily use AI for learning new topics, drafting or editing writing, and summarizing lengthy pieces of text. While many interns are optimistic about AI's potential, around 60% expressed at least some concern that it could replace finance jobs. The survey also delved into the interest in humanoid robots, with 60% of interns expressing at least some interest in having one at home, with 10% predicting they would be early adopters. This interest suggests that household demand for such technology may grow rapidly.