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Microsoft open-source toolkit secures AI agents at runtime

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A new open-source toolkit from Microsoft focuses on runtime security to force strict governance onto enterprise AI agents. The release tackles a growing anxiety: autonomous language models are now executing code and hitting corporate networks way faster than traditional policy controls can keep up. AI integration used to mean conversational interfaces and advisory copilots. Those […]

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As AI agents take on more tasks, governance becomes a priority

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AI systems are starting to move beyond simple responses. In many organisations, AI agents are now being tested to plan tasks, make decisions, and carry out actions with limited human input. It is no longer just about whether a model gives the right answer. It is about what happens when that model is allowed to

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KiloClaw targets shadow AI with autonomous agent governance

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With the launch of KiloClaw, enterprises now have a tool to enforce governance over autonomous agents and manage shadow AI. While businesses spent the last year securing large language models and formalising vendor agreements, developers and knowledge workers started moving on their own. Employees are bypassing official procurement, deploying autonomous agents on personal infrastructure to

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KPMG: Inside the AI agent playbook driving enterprise margin gains

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Global AI investment is accelerating, yet KPMG data shows the gap between enterprise AI spend and measurable business value is widening fast. The headline figure from KPMG’s first quarterly Global AI Pulse survey is blunt: despite global organisations planning to spend a weighted average of $186 million on AI over the next 12 months, only

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SAP and ANYbotics drive industrial adoption of physical AI

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Heavy industry relies on people to inspect hazardous, dirty facilities. It’s expensive, and putting humans in these zones carries obvious safety risks. Swiss robot maker ANYbotics and software company SAP are trying to change that. ANYbotics’ four-legged autonomous robots will be connected straight into SAP’s backend enterprise resource planning software. Instead of treating a robot

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Secure governance accelerates financial AI revenue growth

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Financial institutions are learning to deploy compliant AI solutions for greater revenue growth and market advantage. For the better part of ten years, financial institutions viewed AI primarily as a mechanism for pure efficiency gains. During that era, quantitative teams programmed systems designed to discover ledger discrepancies or eliminate milliseconds from automated trading execution times.

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JPMorgan begins tracking how employees use AI at work

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Banking house JPMorgan Chase is asking its roughly 65,000 engineers and technologists to use AI tools as part of their regular workflow. Business Insider reported that managers are tracking how often staff use these tools. That use may also influence performance reviews. The report states employees are encouraged to use tools like ChatGPT and Claude

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Ocorian: Family offices turn to AI for financial data insights

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To gain financial data insights, the majority of family offices now turn to AI, according to new research from Ocorian. The global study reveals 86 percent of these private wealth groups are utilising AI to improve their daily operations and data analysis. Representing a combined wealth of $119.37 billion, these organisations want machine learning to

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AI agents enter banking roles at Bank of America

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AI agents are starting to take on a more direct role in how financial advice is delivered, as large banks move beyond internal tools and into systems that support real client interactions. Bank of America is now deploying an internal AI-powered advisory platform to a subset of financial advisors, rolled out to around 1,000 financial

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Automating complex finance workflows with multimodal AI

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Finance leaders are automating their complex workflows by actively adopting powerful new multimodal AI frameworks. Extracting text from unstructured documents presents a frequent headache for developers. Historically, standard optical character recognition systems failed to accurately digitise complex layouts, frequently converting multi-column files, pictures, and layered datasets into an unreadable mess of plain text. The varied

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