Bloomberg has launched ASKB, a new conversational artificial intelligence interface for the Bloomberg Terminal, designed to help traders and investment professionals analyse markets, generate insights and act on information more quickly.
Shawn Edwards
Currently in beta, ASKB allows users to query companies, markets and investment themes using natural language, drawing simultaneously from Bloomberg’s structured datasets, news, research and analytics.
Specifically, ASKB will allow users to move away from traditional command-based navigation across multiple Terminal functions by allowing complex analytical queries to be completed through a single conversational interface.
Bloomberg said the system reduces friction in investment research by synthesising information from company filings, Bloomberg News coverage, sell-side research providers and proprietary analytics into consolidated responses with transparent source attribution.
Shawn Edwards, Bloomberg’s chief technology officer, said: “This agentic AI system enables users to ask detailed questions in conversational language and receive comprehensive answers synthesised 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.”
The platform uses a coordinated network of AI agents operating in parallel to retrieve and analyse information across Bloomberg’s content ecosystem. Built using a combination of commercial and open-weight large language models aligned with Bloomberg’s Responsible AI principles, ASKB grounds responses in Bloomberg’s proprietary datasets with transparent attribution to underlying research documents and news sources.
Where queries involve data analysis, the system generates the associated Bloomberg Query Language (BQL) code, allowing traders to extend outputs directly into Excel, BQuant Desktop or BQuant Enterprise for further modelling and workflow integration.
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The new ASKB offering is intended to address increasingly fragmented and manual research processes by performing discovery across Bloomberg’s full content universe and present structured insights designed to support faster investment conviction.
The system also introduces ASKB Workflows, allowing users to describe multi-step tasks such as earnings preparation, post-event analysis or meeting preparation. Outputs can be saved as reusable templates, rerun across securities or time periods and shared across teams, enabling trading desks to scale research processes while maintaining consistency.
David Easthope, senior analyst in market structure and technology at Crisil Coalition Greenwich, said: “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 realised. We see these tools becoming more mainstream, and they are increasingly embedded in major desktop solutions.”