How to scale AI with connected, compliant data

Meet Claude AI — the model rewriting what “smart” means in 2025. Built by Anthropic, Claude isn’t just fast, it’s thoughtful. 💭 The latest update, Claude Haiku 4.5, now outpaces bigger models — running up to 5× faster than Sonnet 4.5 while costing a fraction as much. It codes, reasons, writes, and thinks like an AI built for real-world speed. Claude isn’t chasing size — it’s mastering efficiency. Say hello to the new frontier of intelligent AI assistants.

AI adoption is often rushed without the right foundation in place. The result? AI systems that fail or deliver inaccurate insights, causing resistance to future AI efforts. To succeed, manufacturers must understand the two data types: machine data and human-generated data. Combining both gives AI the context it needs to drive actionable insights. Build a strong data foundation first. Then AI can work its magic. Don’t rush into tools; focus on capturing clean, structured data. Only then can you unlock AI’s full potential. #Manufacturing #AI #OperationalExcellence https://ow.ly/qzAe50X6ktO

AI adoption is often rushed without the right foundation in place. The result? AI systems that fail or deliver inaccurate insights, causing resistance to future AI efforts. To succeed, manufacturers must understand the two data types: machine data and human-generated data. Combining both gives AI the context it needs to drive actionable insights. Build a strong data foundation first. Then AI can work its magic. Don’t rush into tools; focus on capturing clean, structured data. Only then can you unlock AI’s full potential. #Manufacturing #AI #OperationalExcellence https://ow.ly/ofHQ50X0AG3

High-stakes environments demand accuracy, but AI “hallucinations” can create risk and slow adoption. At the Summit of Things, Nitesh Singhal will provide a practical framework for building reliable, enterprise-grade Generative AI. He’ll cover strategies like Retrieval-Augmented Generation, fine-tuning, and automated verification to systematically reduce errors while maintaining high-value outputs. This session will also highlight the Four Pillars of Trustworthy AI: data integrity, purpose-driven model selection, validation with guardrails, and human-in-the-loop oversight. And it will offer actionable steps for organizations to build AI they can depend on. Walk away with a roadmap to make AI reliable and impactful in your business. Register now and join us virtually: https://lnkd.in/gkuhpFUD #AIFramework #EnterpriseAI #ReliableAI 

Most AI projects stall because the data isn’t ready. Leaders are fixing the foundation first. Structured, secure, governed data that turns AI into measurable value. Read the article: https://lnkd.in/e-NK2chE

Recent studies reveal that most enterprise AI projects still fail to reach production, and nearly half are paused or cancelled before delivering measurable value. The article highlights the five most common challenges that derail AI initiatives and how to overcome them with structure, clarity, and the right approach. Read the full article: https://hubs.la/Q03N3crh0 #AIProjects #DataDriven #Transformation #AIInsights

High-stakes environments demand accuracy, but AI “hallucinations” can create risk and slow adoption. At the Summit of Things, Nitesh Singhal will provide a practical framework for building reliable, enterprise-grade Generative AI. He’ll cover strategies like Retrieval-Augmented Generation, fine-tuning, and automated verification to systematically reduce errors while maintaining high-value outputs. This session will also highlight the Four Pillars of Trustworthy AI: data integrity, purpose-driven model selection, validation with guardrails, and human-in-the-loop oversight. And it will offer actionable steps for organizations to build AI they can depend on. Walk away with a roadmap to make AI reliable and impactful in your business. Register now and join us virtually: https://hubs.li/Q03P1B2Q0 #AIFramework #EnterpriseAI #ReliableAI

High-stakes environments demand accuracy, but AI “hallucinations” can create risk and slow adoption. At the Summit of Things, Nitesh Singhal will provide a practical framework for building reliable, enterprise-grade Generative AI. He’ll cover strategies like Retrieval-Augmented Generation, fine-tuning, and automated verification to systematically reduce errors while maintaining high-value outputs. This session will also highlight the Four Pillars of Trustworthy AI: data integrity, purpose-driven model selection, validation with guardrails, and human-in-the-loop oversight. And it will offer actionable steps for organizations to build AI they can depend on. Walk away with a roadmap to make AI reliable and impactful in your business. Register now and join us virtually: https://hubs.li/Q03P1DGb0 #AIFramework #EnterpriseAI #ReliableAI

Europe launched only 3 industrial AI models in 2024, compared to 40 in the US. Europe’s AI gap isn’t just about quantity; it’s about quality, reliability, and industrial fit. The path to closing this gap? A new report by Roland Berger outlines 4 main components of building truly sovereign AI: 🔹 Make AI safe and reliable from the start. 🔹 Fully own and manage your AI, data, and IP. 🔹 Tailor AI to your industry, its rules and regulations. 🔹 AI must integrate smoothly with your existing setup. Europe can leap forward, but only if industrial players own and govern their AI. What do you think is the future of European AI? 🔗 Explore this and other frameworks for sovereign AI directly in Roland Berger’s study: https://okt.to/2ZV7SR #RolandBerger #SovereignAI #AIinEurope