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Meta Business Agent drives AI-powered conversational commerce

Meta has launched Business Agent to automate conversational commerce workflows directly inside its messaging applications. The software allows global retail brands to execute transactions and field support tickets without human intervention. Deploying this architecture places agentic AI directly at the core of social commerce. Meta integrated these workflows natively into Instagram, Messenger, and soon WhatsApp. […]

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How E.ON uses SAP S/4HANA to modernise the grid with AI

Standardising grid data through SAP S/4HANA allows E.ON to modernise infrastructure and execute AI deployments. The utility giant manages infrastructure across three distinct domains: energy grids, customer solutions, and energy infrastructure solutions. Maintaining operations across this scope requires continuous capital expenditure on IT hardware and software maintenance. Leadership initially questioned the business case supporting large-scale

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Anthropic IPO filing marks AI maturing into enterprise utility

Anthropic’s IPO filing marks the maturation of generative AI from a research-heavy venture phase into a stabilised enterprise utility. Model developers operating in private markets have prioritised rapid iteration and maximum compute performance over predictable billing cycles. Taking a foundational provider public aligns those engineering goals with standard corporate procurement, introducing structured release schedules and

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SAP: How enterprise AI governance secures profit margins

According to SAP, enterprise AI governance secures profit margins by replacing statistical guesses with deterministic control. Ask a consumer-grade model to count the words in a document, and it will often miss the mark by ten percent. Manos Raptopoulos, Global President of Customer Success Europe, APAC, Middle East & Africa at SAP, observes that the

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

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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Strengthening enterprise governance for rising edge AI workloads

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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IBM: How robust AI governance protects enterprise margins

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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KiloClaw targets shadow AI with autonomous agent governance

With the launch of KiloClaw, enterprises now have a tool to enforce governance over autonomous agents and manage shadow AI. While businesses spent the last year securing large language models and formalising vendor agreements, developers and knowledge workers started moving on their own. Employees are bypassing official procurement, deploying autonomous agents on personal infrastructure to

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KPMG: Inside the AI agent playbook driving enterprise margin gains

Global AI investment is accelerating, yet KPMG data shows the gap between enterprise AI spend and measurable business value is widening fast. The headline figure from KPMG’s first quarterly Global AI Pulse survey is blunt: despite global organisations planning to spend a weighted average of $186 million on AI over the next 12 months, only

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Secure governance accelerates financial AI revenue growth

Financial institutions are learning to deploy compliant AI solutions for greater revenue growth and market advantage. For the better part of ten years, financial institutions viewed AI primarily as a mechanism for pure efficiency gains. During that era, quantitative teams programmed systems designed to discover ledger discrepancies or eliminate milliseconds from automated trading execution times.

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