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Reversing enterprise security costs with AI vulnerability discovery

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Automated AI vulnerability discovery is reversing the enterprise security costs that traditionally favour attackers. Bringing exploits to zero was once viewed as an unrealistic goal. The prevailing operational doctrine aimed to make attacks so expensive that only adversaries with functionally unlimited budgets could afford them, thereby disincentivising casual use. However, the recent evaluation by the […]

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Accountability in Automated Decisions: The Next Frontier of Tech Law

ai, AI (Artificial Intelligence), Artificial Intelligence, governance, Legal tech

As automated decision-making becomes embedded in business-as-usual processes‚ the need for accountability changes from a theoretical debate to a practical governance challenge. New regulations such as the EU AI Act and the General Data Protection Regulation reflect a growing consensus that businesses should explain, audit, and enable individuals to contest automated decisions that significantly affect

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OpenAI Agents SDK improves governance with sandbox execution

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OpenAI is introducing sandbox execution that allows enterprise governance teams to deploy automated workflows with controlled risk. Teams taking systems from prototype to production have faced difficult architectural compromises regarding where their operations occurred. Using model-agnostic frameworks offered initial flexibility but failed to fully utilise the capabilities of frontier models. Model-provider SDKs remained closer to

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Commvault launches a ‘Ctrl-Z’ for cloud AI workloads

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Enterprise cloud environments now have access to an undo feature for AI agents following the deployment of Commvault AI Protect. Autonomous software now roams across infrastructure, potentially deleting files, reading databases, spinning up server clusters, and even rewriting access policies. Commvault identified this governance issue and the data protection vendor has launched AI Protect, a

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SAP brings agentic AI to human capital management

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According to SAP, integrating agentic AI into core human capital management (HCM) modules helps target operational bloat and reduce costs. SAP’s SuccessFactors 1H 2026 release aims to anticipate administrative bottlenecks before they stall daily operations by embedding a network of AI agents across recruiting, payroll, workforce administration, and talent development. Behind the user interface, these

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Strengthening enterprise governance for rising edge AI workloads

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Models like Google Gemma 4 are increasing enterprise AI governance challenges for CISOs as they scramble to secure edge workloads. Security chiefs have built massive digital walls around the cloud; deploying advanced cloud access security brokers and routing every piece of traffic heading to external large language models through monitored corporate gateways. The logic was

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Companies expand AI adoption while keeping control

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Many companies are taking a slower, more controlled approach to autonomous systems as AI adoption grows. Rather than deploying systems that act on their own, they are focusing on tools that assist human decision-making while keeping tight control over outputs. This approach is especially clear in sectors where errors carry real financial or legal risk.

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IBM: How robust AI governance protects enterprise margins

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To protect enterprise margins, business leaders must invest in robust AI governance to securely manage AI infrastructure. When evaluating enterprise software adoption, a recurring pattern dictates how technology matures across industries. As Rob Thomas, SVP and CCO at IBM, recently outlined, software typically graduates from a standalone product to a platform, and then from a

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Why companies like Apple are building AI agents with limits

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Next-generation AI assistants being developed in the Apple ecosystem and by chipmakers like Qualcomm, but early reports suggest they are being designed with limits in place. Tom’s Guide has described early versions of these assistants as capable of navigating apps, carrying out bookings, and managing tasks in services. For instance a private beta agentic system

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Agentic AI’s governance challenges under the EU AI Act in 2026

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AI agents hold the promise of automatically moving data between systems and triggering decisions, but in some cases, they can act without a clear record of what, when, and why they undertook their tasks. That has the potential to create a governance problem, for which IT leaders are ultimately responsible. If an organisation can’t trace

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