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How multi-agent AI economics influence business automation

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Managing the economics of multi-agent AI now dictates the financial viability of modern business automation workflows. Organisations progressing past standard chat interfaces into multi-agent applications face two primary constraints. The first issue is the thinking tax; complex autonomous agents need to reason at each stage, making the reliance on massive architectures for every subtask too […]

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Upgrading agentic AI for finance workflows

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Improving trust in agentic AI for finance workflows remains a major priority for technology leaders today. Over the past two years, enterprises have rushed to put automated agents into real workflows, spanning customer support and back-office operations. These tools excel at retrieving information, yet they often struggle to provide consistent and explainable reasoning during multi-step

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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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Chinese hyperscalers and industry-specific agentic AI

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Major Chinese technology companies Alibaba, Tencent, and Huawei are pursuing agentic AI (systems that can execute multi-step tasks autonomously and interact with software, data, and services without human instruction), and orienting the technology toward discrete industries and workflows. Alibaba’s open-source strategy for agentic AI Alibaba’s strategy centres on its Qwen AI model family, a set

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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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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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Masumi Network: How AI-blockchain fusion adds trust to burgeoning agent economy

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2026 will see forward-thinking organisations building out their squads of AI agents across roles and functions. But amid the rush, there is another aspect to consider. One of IDC’s enterprise technology predictions for the coming five years, published in October, was fascinating. “By 2030, up to 20% of [global 1000] organisations will have faced lawsuits,

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How people really use AI: The surprising truth from analysing billions of interactions

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For the past year, we’ve been told that artificial intelligence is revolutionising productivity—helping us write emails, generate code, and summarise documents. But what if the reality of how people actually use AI is completely different from what we’ve been led to believe? A data-driven study by OpenRouter has just pulled back the curtain on real-world AI usage by analysing over 100

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