A new conversational AI interface brings speed, clarity, and intelligence to investment research on the Bloomberg Terminal
Bloomberg introduced ASKB, a powerful new conversational AI interface, now in beta, that reshapes how investors discover, analyze, and act on information using the Bloomberg Terminal®. Built on Bloomberg’s long-standing leadership in artificial intelligence and its application in finance, ASKB is designed to help clients unlock even more value from their Bloomberg Anywhere (BBA) subscriptions — by dramatically accelerating research and insight generation.
With ASKB, financial professionals focused on company and equity market analysis can use everyday language to quickly tap into Bloomberg’s vast universe of structured data and unstructured documents, news, research, and analytics, which they already trust for their decision-making. By reducing friction and delivering clear, transparent source attribution, ASKB helps users move faster from questions to conviction – supporting smarter, more confident investment decisions.
“ASKB is a revolutionary new mode of interaction with the Bloomberg Terminal that will enable our customers to tap into the full power and context of Bloomberg’s trusted data and analytics,” said Shawn Edwards, Bloomberg’s Chief Technology Officer. “This agentic AI system enables users to ask detailed questions in conversational language and receive comprehensive answers synthesized from our extensive data, documents, news, research, and analytics. Early feedback from beta clients shows ASKB is driving efficiency, improving discovery, and helping users surface actionable insights at speed.”
Agentic AI, Built for the Speed of the Markets
ASKB brings agentic AI directly into the Bloomberg Terminal through a coordinated network of AI agents working in parallel. These agents dynamically access Bloomberg’s data, news, research, and analytics to deliver rich, contextual answers to complex questions about markets, companies, and investment ideas.
Built using multiple commercial and open weight LLMs in alignment with Bloomberg’s Responsible AI principles, ASKB grounds every response in high-quality, trusted data and includes transparent attribution to original research documents and news sources. When responses include data analysis, ASKB provides the underlying Bloomberg Query Language (BQL) code — so users can immediately extend their analysis in Microsoft® Excel®, BQuant Desktop, or BQuant Enterprise.
One Interface. Maximum Depth. Global Coverage.
ASKB delivers broad coverage across all asset classes and supports a wide range of analytical and research queries. Its AI agents simultaneously draw from Bloomberg’s premium content library, including:
A Smarter Way to Work
Today’s investment research is often fragmented and manual — requiring professionals to jump between screens, assemble information, and spend hours synthesizing results.
ASKB changes that.
Instead of navigating screen-to-screen, users can ask questions in natural language and let ASKB’s AI agents perform discovery across Bloomberg’s entire content universe. ASKB then analyzes and synthesizes the findings into a clear, contextual foundation for decision-making — helping investors keep pace with the speed, scale, and complexity of modern markets.
ASKB Workflows: From Hours to Minutes
ASKB goes beyond conversational Q&A to speed up repetitive research tasks. With ASKB Workflows, users can describe multi-step activities such as pre-earnings preparation, post-earnings analysis, or meeting prep – and ASKB will assemble a structured output in minutes.
Users can:
ASKB Workflows help scale research processes without sacrificing flexibility or rigor.
“Investment research is on the cusp of a significant transformation, with AI poised to revolutionize the way researchers work in 2026”, says David Easthope, Crisil Coalition Greenwich Senior Analyst in Market Structure & Technology and co-author of a new report, Top Trends in Financial Market Structure for 2026. “As adoption accelerates, we expect AI to unlock new insights, automate complex analyses, and drive efficiency, with its full potential only just beginning to be realized. We see these tools becoming more mainstream and they are increasingly embedded in major desktop solutions.”
