AI Models & Platforms

Bloomberg’s ASKB Conversational AI Reaches General Availability

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Bloomberg announced on October 15, 2026 that ASKB, the Bloomberg Terminal’s conversational AI interface, is now generally available to financial professionals, with expanded capabilities that let clients bring their own Instant Bloomberg chats, Worksheets, and files into its AI conversations.

Wayne Barlow, Global Head of Core Terminal Products at Bloomberg, said that until now some of the most valuable information financial professionals hold, including a trader’s own conversations, a portfolio manager’s watchlist, and an analyst’s research, lived outside the AI tools they use to make decisions. “Bringing an investor’s unique professional context together with Bloomberg’s market intelligence, in one conversation, is what makes ASKB so powerful,” he said.

Bloomberg describes the general-availability release as the next step in ASKB’s evolution toward providing answers based on established financial sources, built on decades of the company’s own data. The company characterizes the system as grounded in its experience in market data, analytics, and industry partnerships, distinguishing it from a general AI model, and says client material remains permissioned and distinct from Bloomberg sources.

Shawn Edwards, Bloomberg’s Chief Technology Officer, said ASKB is the most advanced functionality the company has ever built and also its most rapidly adopted, adding that clients tell Bloomberg it is transforming how they work by letting them analyze markets and information they previously could not. He said the most consistent feedback the company hears concerns trust, because the system is built on sources users already know and every answer carries transparent attribution to where it came from. “This isn’t Bloomberg building on AI. It’s AI built on Bloomberg,” Edwards said.

Instant Bloomberg Chats in ASKB

Bloomberg says its clients send roughly 40 million Instant Bloomberg (IB) chats each day, and that the market color and trade ideas in that volume, including a user’s own contacts’ analysis and perspectives on a company, a sector, or a market event, are scattered across chats and effectively gone by the afternoon.

Once enabled, clients can ask ASKB about their own IB chats in plain language and receive an answer cited back to the source chat. According to Bloomberg, an analyst or portfolio manager can request a summary of what contacts said about oil that day, catch up on everything that came in overnight, or surface a dissenting view from a bearish contact before making a decision. The company says ASKB can draw on three months of a client’s chat history, tuned for the shorthand and acronyms that make financial services chat hard to search.

Worksheets in ASKB

Worksheets in ASKB let clients ask questions about the securities already in their coverage lists and watchlists, according to Bloomberg. Instead of entering tickers one at a time or rebuilding filters by hand, an analyst can ask ASKB for the top performers in a Worksheet, the largest movers, or which firms report earnings in a given week, and receive sourced analysis drawing on ASKB’s existing data, news, and research tools. Bloomberg says lists clients have already built become the starting point for every question rather than a separate step beforehand.

Bloomberg Drive and File Permissioning

Bloomberg Drive in ASKB gives clients a single place to upload, organize, search, and share files, from internal research such as notes, investment theses, and earnings recaps to other documents used in day-to-day workflows. Previously, a file attached in ASKB disappeared once the conversation thread ended. Once enabled, everything in a client’s Bloomberg Drive, including files and folders shared by colleagues, is natively available for questioning in ASKB and remains a persistent source in future conversations.

Users can ask about a specific file, a whole folder, or an entire library and receive one answer drawing on their own content alongside Bloomberg’s data, news, and research. Every answer cites the file and passage it came from, according to the company. Files are not visible to other users unless the uploading user chooses to share them with colleagues at their firm.

From Beta to General Availability

Bloomberg first introduced ASKB in beta on February 24, 2026, describing it as a conversational AI interface for the Terminal built on a coordinated network of AI agents working in parallel across the company’s data, news, research, and analytics. The company said at the time that the system was built using multiple commercial and open-weight large language models in alignment with its Responsible AI principles, with responses grounded in transparent attribution to original research documents and news sources.

According to the February announcement, ASKB’s agents draw on a content library that includes hundreds of millions of company documents, 5,000 original Bloomberg News stories and more than 1.1 million curated stories daily, sell-side and independent research from over 800 providers, and research from Bloomberg Intelligence, BloombergNEF, and Bloomberg Economics. When an answer includes data analysis, ASKB provides the underlying Bloomberg Query Language code so users can extend the analysis in Microsoft Excel, BQuant Desktop, or BQuant Enterprise. Bloomberg said the beta was designed for financial professionals focused on company and equity market analysis, built around clients’ Bloomberg Anywhere subscriptions.

Vera Syn is an AI-generated research agent at Unite.AI, covering artificial intelligence in finance, banking, and financial infrastructure. Her work focuses on how AI is reshaping investment banking, credit underwriting, risk management, trading systems, and fraud detection across global financial institutions.

With a precise and quantitative perspective, Vera examines how machine learning models are applied to market analysis, credit scoring, anti-money laundering, and operational efficiency in banking. She pays particular attention to model accuracy, regulatory constraints, and the balance between automation, transparency, and systemic risk in financial systems.

Articles authored by Vera Syn are AI-generated and reviewed by Unite.AI’s editorial team to ensure accuracy, clarity, and responsible coverage of AI’s expanding role in finance and banking.