Artificial intelligence is changing how investors access, interpret and use market data, creating new opportunities for retail traders to benefit from information and analytical capabilities traditionally available to large financial institutions, according to Brandon Tepper, Senior Vice President and Global Head of Data at Nasdaq.

“AI is really helping investors gather data in a more easy to use fashion to help tell stories from that data so that they can make informed investing decisions,” Tepper told Traders Magazine.

According to Tepper, Nasdaq is seeing new clients, applications and use cases emerge as financial institutions, technology providers and individual investors explore how AI can extract greater value from existing datasets.

The shift extends across retail investors, institutional traders and quantitative funds, with AI becoming increasingly important to how market information is delivered and consumed.

While AI is changing how investors interact with information, Tepper emphasized that the quality of the underlying data remains fundamental. “In order to have good AI, as you know, you really have to have clean, trusted, and accurate data,” he said.

Nasdaq operates 18 exchanges globally, according to Tepper, providing market data that can be combined with complementary and alternative datasets to support investment analysis. He described this as a layered approach, beginning with foundational exchange data before incorporating additional information.

Tepper acknowledged that AI systems are not always accurate and that their predictions depend heavily on the quality of the information they receive. “The value of the underlying data is the basis for good AI, and there are risks of using incorrect data,” he said.

He emphasized the importance of appropriate controls, security measures and understanding what AI applications can and cannot do.

Institutional intelligence reaches retail investors

The growing accessibility of institutional-grade market intelligence is another important development, with Tepper pointing to the narrowing gap between retail and professional investors. “I think the gap is getting very narrow,” he said.

Tepper noted that investors previously needed expensive financial terminals or proprietary datasets to obtain certain information, while technology platforms are now making that information easier to access.

One example is Nasdaq’s expanded partnership with Robinhood, which is bringing additional institutional-grade market intelligence into the brokerage’s AI-powered investment tools.

According to Tepper, the relationship began more than a decade ago and has expanded from equity market data to more sophisticated datasets, including Nasdaq TotalView.

More recently, Nasdaq began supplying alternative datasets through Robinhood’s new Agents ecosystem, allowing users to interact with AI agents that draw on market intelligence to answer investment-related questions. “We’re not just streaming live data, we’re helping investors utilize it in a more agentic way,” Tepper explained.

He said the development could eventually allow individual investors to establish algorithmic trading strategies based on predefined market conditions.

Tepper also pointed to the growing sophistication of retail traders, including investors described as “pro-tail,” who increasingly seek more advanced market information.

Despite the opportunities, he emphasized that AI-powered investing requires appropriate safeguards, particularly as applications become capable of supporting automated trading activity.

He cited Robinhood’s approach, which requires users to establish and separately fund an account for its agent-based functionality, with restrictions on access to information outside the platform. According to Tepper, the data is also not used to train the underlying AI models.

“If you have the right rails and the right security and risk profile, and understand what it can and can’t do, it’s going to just get better and easier to use,” he said.

Tepper said Nasdaq has been preparing its datasets for AI-driven applications for several years, including developing AI-ready data delivery capabilities and support for Model Context Protocol (MCP).

“AI is embedded in every single conversation we have with existing clients, new clients, startups, individual investors,” he said.

Market data moves toward an always-on environment

Beyond AI, Tepper identified expanding trading hours as another development shaping the market data industry. He said Nasdaq is diversifying geographically and across product categories, with more than 250 products available through Nasdaq Data Link.

The company is also preparing for growing demand for market information outside traditional trading hours as the industry moves toward 23-hour, five-day trading and potentially continuous markets.

According to Tepper, Nasdaq has been testing new data feeds in preparation for a December 6 launch of 23/5 trading.

Tepper linked the move toward extended trading hours to changing consumer expectations, noting that people have become accustomed to accessing services at almost any hour. “Why not have the ability to invest in your favorite company at all hours of the day?” he asked.

He sees opportunities for retail and institutional investors as trading hours expand, while emphasizing appropriate risk controls. “I see AI as sort of the next wave of investing,” Tepper said, predicting that improved access to information will support increasingly sophisticated agent-based investment applications.