Trust, Bias & Fairness

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Upgrading agentic AI for finance workflows

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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Deploying agentic finance AI for immediate business ROI

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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Mastercard’s AI payment demo points to agent-led commerce

A recent demonstration from Mastercard suggests that payment systems may be heading toward a future where software agents, not people, complete purchases. During the India AI Impact Summit 2026, Mastercard showed what it described as its first fully authenticated “agentic commerce” transaction. In the demo, as reported by Times of India, an AI agent searched

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DBS pilots system that lets AI agents make payments for customers

Artificial intelligence is moving closer to the point where it can act, not advise. A new pilot by DBS Bank shows how that change may soon affect everyday payments, as financial institutions begin testing systems that allow AI agents to complete purchases on behalf of customers. DBS is working with Visa to trial Visa Intelligent

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How financial institutions are embedding AI decision-making

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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Microsoft unveils method to detect sleeper agent backdoors

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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Franny Hsiao, Salesforce: Scaling enterprise AI

Scaling enterprise AI requires overcoming architectural oversights that often stall pilots before production, a challenge that goes far beyond model selection. While generative AI prototypes are easy to spin up, turning them into reliable business assets involves solving the difficult problems of data engineering and governance. Ahead of AI & Big Data Global 2026 in

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Inside Standard Chartered’s approach to running AI under privacy rules

For banks trying to put AI into real use, the hardest questions often come before any model is trained. Can the data be used at all? Where is it allowed to be stored? Who is responsible once the system goes live? At Standard Chartered, these privacy-driven questions now shape how AI systems are built, and

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McKinsey tests AI chatbot in early stages of graduate recruitment

Hiring at large firms has long relied on interviews, tests, and human judgment. That process is starting to shift. McKinsey has begun using an AI chatbot as part of its graduate recruitment process, signalling a shift in how professional services organisations evaluate early-career candidates. The chatbot is being used during the initial stages of recruitment,

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Allister Frost, a former Microsoft leader and expert on business transformation.

Allister Frost: Tackling workforce anxiety for AI integration success

Navigating workforce anxiety remains a primary challenge for leaders as AI integration defines modern enterprise success. For enterprise leaders, deploying AI is less a technical hurdle than a complex exercise in change management. The reality for many organisations is that, while algorithms offer efficiency, the human element dictates the speed of adoption. Data from the

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