Over a Quarter of Wall Street Interns Use Prediction Markets
Morgan Stanley's equity research team conducted an annual survey of over 500 North American summer interns, most of whom are under 21 years old. More than a quarter of interns reported using betting or prediction market applications in the past year, with Kalshi and Polymarket being the most common choices. 55% of users utilize multiple betting applications simultaneously.
This survey included questions about betting habits for the first time, showing that the usage rate among interns is consistent with that of the national adult population. Another national survey indicated that 21% of adult respondents in the U.S. have used prediction market platforms, with the proportion rising to 37% among those aged 18 to 34.
Prediction markets are facing increased scrutiny in the U.S., with several states implementing legal or regulatory measures against related platforms. Morgan Stanley's employee conduct guidelines cover trading and investment matters, including prediction markets, but no further details were disclosed.
Regarding AI, 68% of interns use AI tools daily, up from 35% last year and 14% in 2024. About 70% pay for subscriptions to AI tools, an increase from 52% last summer. The main uses include learning new topics, drafting or editing text, and summarizing long documents.
At the same time, 61% of respondents are concerned about AI replacing jobs in finance, and 74% worry about job displacement in other industries. Over 60% are interested in using humanoid robots at home, with 10% indicating they might become early adopters.
In terms of market mechanisms, young professionals are directly participating in prediction markets through mobile applications, representing event-driven personal risk allocation. Funds are flowing to platforms like Kalshi and Polymarket, benefiting prediction market operators and AI tool subscription services, while traditional financial compliance frameworks and entry-level job stability are under pressure.
Supplementary data shows that interns' use of AI has become deeply embedded in their daily workflows, with entry-level tasks such as creating slides and Excel processing being automated at an accelerated pace.
Source: Public Information
ABAB AI Insight
Morgan Stanley's previous annual intern surveys focused on brand preferences, interest in cryptocurrencies, and attitudes towards humanoid robots. The 2025 version shows that only 18% own or use cryptocurrencies, while career priorities have risen to 89%. This year's survey includes questions about betting and prediction markets for the first time, reflecting the research team's inclusion of young professionals' risk behaviors in capital path observations.
On the capital path, the proportion of interns paying for AI tool subscriptions has risen from 52% to 70%, while over a quarter of funds are flowing into multiple platforms like Kalshi and Polymarket. The motivation is to use prediction markets as sources of information and trading tools, with AI serving as an efficiency lever, facilitating the transition from bank entry training to personal digital tool combinations.
Similar cases can be seen with Kalshi previously marketing data services to Wall Street firms, and several companies have already prohibited employees from trading in prediction markets. The industry is currently transitioning from prediction markets as marginal gambling to institutional data sources, while AI is accelerating from an auxiliary tool to replacing entry-level positions.
The structural judgment indicates a technological replacement: young professionals are embedding AI and prediction markets into their daily routines, with mechanisms that lower information and trading barriers, allowing personal risk allocation to bypass traditional compliance channels, leading to the compression of entry-level financial job values due to automation, while regulation lags behind usage habits.
ABAB News · Cognitive Laws
- The more widespread the tools, the younger the risks.
- Efficiency improvements and job anxiety accelerate in tandem.
- A generation where compliance lags behind usage habits.