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137 articles
As AI becomes more embedded in enterprise operations, organizations are facing the challenge of systemic drift—subtle but significant changes in complex AI ecosystems that can undermine resilience. Leadership must now prioritize continuous monitoring and governance to maintain visibility into system dependencies.
OpenAI's second-in-command Fidji Simo is stepping down from her full-time role after an extended medical leave, creating a leadership vacuum at a critical time for the company's IPO preparations and competitive positioning.
Meta enters the AI coding battle with Muse Spark 1.1, targeting enterprise-scale automation and complex development workflows. The new tool aims to compete with established players like GitHub Copilot and ChatGPT-4 in the rapidly growing AI development space.
Oracle's Mark Hura argues that enterprise AI success hinges on data strategy, not model selection. At the RAISE Summit in Paris, he emphasized that companies leveraging their unique data assets will gain a competitive edge in the AI landscape.
n8n's founder Jan Oberhauser warns that over-reliance on specific AI models can be catastrophic for businesses, advocating instead for model-agnostic AI infrastructure.
Google expands Gemini API Managed Agents with background task execution and remote MCP support, enhancing AI automation capabilities for enterprise use.
OpenAI is hiring an investment banking expert to help train its AI in enterprise finance, signaling a move toward more specialized AI applications.
This article explains the 'AI gap' – the difference between having an AI strategy and actually implementing it in business operations. Learn why this gap exists and why it matters for companies investing in AI.
Mistral CEO Arthur Mensch warns that closed AI models give providers immense leverage over enterprise businesses, urging a shift toward open-source alternatives.
This article explains the technical aspects of Claude Code AI tool and Alibaba's decision to ban its use, examining enterprise AI governance and security concerns in the context of advanced AI development.
Microsoft has launched its own AI deployment company with a $2.5 billion commitment, entering the competitive AI infrastructure market alongside Amazon, OpenAI, and Anthropic.
Microsoft launches a $2.5 billion AI deployment business with 6,000 engineers to accelerate enterprise AI adoption.
