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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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ABB: Physical AI simulation boosts ROI for factory automation

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A new ABB and NVIDIA partnership shows physical AI simulation is driving real ROI in factory automation and solving production hurdles. Manufacturers have often found it difficult to make intelligent robotics work reliably outside testing environments. The core issue is the gap between digital training models and actual factory floors, where lighting, material physics, and

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Agentic AI in finance speeds up operational automation

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In finance, achieving operational automation by integrating agentic AI requires a data-centric foundation to drive real value. Financial infrastructure provider SEI has engaged IBM to modernise its internal operations via AI and automation. The joint initiative focuses on process redesign and targeted system updates to deliver consistent client experiences, building a modern and data-enabled foundation

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Scaling intelligent automation without breaking live workflows

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Scaling intelligent automation without disruption demands a focus on architectural elasticity, not just deploying more bots. At the Intelligent Automation Conference, industry leaders gathered to dissect why many automation initiatives stall after pilot phases. Speaking alongside representatives from NatWest Group, Air Liquide, and AXA XL, Promise Akwaowo, Process Automation Analyst at Royal Mail, grounded the

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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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How disconnected clouds improve AI data governance

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Disconnected clouds aim to improve AI data governance as businesses rethink their infrastructure under tighter regulatory expectations. Ensuring operational continuity in isolated environments has become increasingly vital for businesses. Facilities lacking continuous internet access face unique constraints where external dependencies become unacceptable. Microsoft recently expanded its capabilities to allow regulated industries and public sectors to

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Deploying agentic finance AI for immediate business ROI

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Agentic finance AI improves business efficiency and ROI only when deployed with strict governance and clear return on investment targets. A recent FT Longitude survey of 200 finance leaders across the US, UK, France, and Germany showed 61 percent have deployed AI agents merely as experiments. Meanwhile, one in four executives admit they do not

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Exploring AI in the APAC retail sector

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AI in the APAC retail sector is transitioning from analytics and pilots into workflows and daily operations. Dense urban stores, high labour churn, and competitive quick-commerce ecosystems are driving the uptake. A Q4 2025 survey by GlobalData found that 45 percent of consumers in Asia and Australasia are very or quite likely to purchase a

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AI: Executives’ optimism about the future

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The most rigorous international study of firm-level AI impact to date has landed, and its headline finding is more constructive than many expected. Across nearly 6,000 verified executives in four countries, AI has delivered modest aggregate shifts in productivity or employment over the past three years. The measured impact reflects the early phases of deployment

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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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