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How financial institutions are embedding AI decision-making

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For leaders in the financial sector, the experimental phase of generative AI has concluded and the focus for 2026 is operational integration. While early adoption centred on content generation and efficiency in isolated workflows, the current requirement is to industrialise these capabilities. The objective is to create systems where AI agents do not merely assist […]

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Alibaba Qwen is challenging proprietary AI model economics

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The release of Alibaba’s latest Qwen model challenges proprietary AI model economics with comparable performance on commodity hardware. While US-based labs have historically held the performance advantage, open-source alternatives like the Qwen 3.5 series are closing the gap with frontier models. This offers enterprises a potential reduction in inference costs and increased flexibility in deployment

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Debenhams pilots agentic AI commerce via PayPal integration

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Debenhams is piloting agentic AI commerce via PayPal integration to reduce mobile friction and help solve a familiar problem for retailers. Mobile checkout abandonment remains a persistent revenue leak for digital retailers. Debenhams Group is attempting to close this gap by deploying an agentic AI interface within the PayPal app. The pilot makes Debenhams the

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Agentic AI drives finance ROI in accounts payable automation

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Finance leaders are driving ROI using agentic AI for accounts payable automation, turning manual tasks into autonomous workflows. While general AI projects saw return on investment rise to 67 percent last year, autonomous agents delivered an average ROI of 80 percent by handling complex processes without human intervention. This performance gap demands a change in

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How insurance leaders use agentic AI to cut operational costs

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Agentic AI offers insurance leaders a path to scalable efficiency as the sector confronts a tough digital transformation. Insurers hold deep data reserves and employ a workforce skilled in analytic decision-making. Despite these advantages, the industry has largely failed to advance beyond pilot programmes. Research suggests only seven percent of insurers have scaled these initiatives

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Red Hat unifies AI and tactical edge deployment for UK MOD

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The UK Ministry of Defence (MOD) has selected Red Hat to architect a unified AI and hybrid cloud backbone across its entire estate. Announced today, the agreement is designed to break down data silos and accelerate the deployment of AI models from the data centre to the tactical edge. For CIOs, it’s part of a

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Exclusive: Why are Chinese AI models dominating open-source as Western labs step back?

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Because Western AI labs won’t—or can’t—anymore. As OpenAI, Anthropic, and Google face mounting pressure to restrict their most powerful models, Chinese developers have filled the open-source void with AI explicitly built for what operators need: powerful models that run on commodity hardware. A new security study reveals just how thoroughly Chinese AI has captured this space. Research published by SentinelOne

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How separating logic and search boosts AI agent scalability

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Separating logic from inference improves AI agent scalability by decoupling core workflows from execution strategies. The transition from generative AI prototypes to production-grade agents introduces a specific engineering hurdle: reliability. LLMs are stochastic by nature. A prompt that works once may fail on the second attempt. To mitigate this, development teams often wrap core business

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AI Expo 2026 Day 2: Moving experimental pilots to AI production

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The second day of the co-located AI & Big Data Expo and Digital Transformation Week in London showed a market in a clear transition. Early excitement over generative models is fading. Enterprise leaders now face the friction of fitting these tools into current stacks. Day two sessions focused less on large language models and more

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Microsoft unveils method to detect sleeper agent backdoors

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Researchers from Microsoft have unveiled a scanning method to identify poisoned models without knowing the trigger or intended outcome. Organisations integrating open-weight large language models (LLMs) face a specific supply chain vulnerability where distinct memory leaks and internal attention patterns expose hidden threats known as “sleeper agents”. These poisoned models contain backdoors that lie dormant

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