Bloomberg’s First Generative AI Tool Hits the Terminal

All users now have access to earnings call summaries and analysis written by artificial intelligence.


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Bloomberg terminal users got a research boost on Monday just in time for earnings season: summaries and analysis of company performance written by artificial intelligence.

Some users were testing the beta version of Bloomberg’s first generative AI tool last quarter and others started getting access last week. Bloomberg is rolling it out to all users on Monday, the company told Institutional Investor.

The summaries are designed to help analysts save time absorbing earnings data and transcripts by highlighting key points. They will be available immediately for companies in the Russell 1000 and the top 1000 companies in Europe.

Beyond saving users time in general, Bloomberg says its AI summaries can help them uncover deeper insights and give them an edge. “Our clients need to be able to save time, but what they’re not looking for is a system just to give them an answer,” Andrew Skala, global head of research and listed core services product at Bloomberg, said. “What they want to be able to do is find more information so they can differentiate their own approach and do better research.”

Since late 2022, when the world became captivated with OpenAI’s ChatGPT — the most impressive generative AI chatbot yet available to the public — venture capitalists have shifted their focus to AI, analysts have called it a “mega force,” and managers began investing more in it. Bloomberg, which began developing AI tools internally more than a decade ago, also began ramping up its effort to get its customers AI-powered tools. Those included a ChatGPT-style upgrade to make searching the terminal easier and delivering faster bond prices.

Anyone can copy and paste a public company’s earnings report into a growing list of AI tools and ask them to summarize it. Bloomberg says it is offering something different.


“This technology that everyone’s talking about gives a lot out of the box and we think our clients need more than that,” Skala said.

The 400 Bloomberg Intelligence analysts that deliver independent data and research helped train the AI models so they better understand the nuances of financial language and anticipate what’s important to investors. Among other things they know investors are focused on, the summaries include context on a company’s guidance, capital allocation, hiring and labor plans, the macro environment, new products, supply chain issues, and consumer demand. “It’s been an iteration [process] to the point where we got comfortable that this makes a difference, this is unique, this is differentiated,” said Skala, who spent nearly 10 years as a sell-side researcher before joining Bloomberg.

The summaries also have hyperlinks embedded alongside original transcript documents, a level of transparency and sourcing that are often absent from other AI platforms.

The overviews prove especially useful when analysts need to quickly learn or could use an update on a company they aren’t covering but which suddenly become important, according to Skala. “It’s about knowing the ecosystem and knowing what their competitors are saying or their suppliers and how we model those relationships and start to bring some of those things to the surface. “That’s what we try to do here that I think is different, he said.

At least one hedge fund familiar with the summaries says they have already proven useful.

“Most of my team’s job is reading and synthesizing trends across companies, so the quality and accuracy of the summarization tool gives us a big edge. Bloomberg’s earnings summaries make for easier reading coverage across ancillary and adjacent companies and distills the contentious points so we know where in the material to look for insights on the important debates,” said Joyce Meng, managing director and partner at Fact Capital, a New York-based hedge fund.