AI isn’t short of features. What we’re short of… are better blueprints. Without strong foundations - data, integration, governance, AI initiatives quickly turn into experiments without impact. The question isn’t “What can AI do?” It’s “What can we architect so AI delivers real value?” Curious to hear: what’s the single biggest “blueprint gap” you see in organisations right now? #BetterBlueprints #AIArchitecture #FutureOfCRM #SalesforceArchitect #EnterpriseArchitecture #TechLeadership #InnovationInAction

materialsIN leverages a proprietary AI/data-driven methodology to streamline, and improve, companies' production processes and materials usage. And, we are flexible in our data science approach--we work with all forms of customer data, and data sizes can be minimal to large. #AIformanufacturing #processoptimization #datadrivensolutions

💡 The three-layer stack that truly unlocks Enterprise AI. 💥 To get AI that's a genuine partner in delivering value, these elements are important: 0️⃣ Ontology: To define the business's Concepts, Rules, and Governance. 1️⃣ Knowledge Graph: To link data and context across domains. 2️⃣ Context Window: To surface what matters, in real time. 🍒 Without this structure, AI remains a predictive tool that predicts with incomplete, disconnected data. With it, you build durable trust. 👉 The future of Enterprise AI starts with capturing your business flows. #AIArchitecture #KnowledgeGraphs #DigitalTransformation #LLMs

The new MIT State of AI in Business 2025 report reveals a stark truth: despite $30–40B invested, 95% of enterprise AI initiatives show no measurable ROI. The problem isn’t the models. It’s that most enterprise AI systems don’t learn, don’t adapt, don’t integrate into workflows, and don’t retain context. At K2view, we see this every day: without trusted, real-time, entity-centric data, that acts as a foundation to any agentic AI initiative, AI can’t move from pilots to production. That’s the real GenAI Divide — and it’s why data integration is the missing link between AI hype and AI impact. https://lnkd.in/eEiXCteC

Gen AI initiatives often fail not because of the tech, but because of how it's applied. From overhyped spending to poor data governance and DIY builds gone wrong, these common mistakes can stall your AI journey and prevent it from delivering real impact. This post breaks down 5 common Gen AI mistakes and how to avoid them. If you're exploring Gen AI for your operations, this is a must-read before your next move. Take a deep dive into the full post: https://lnkd.in/d45USYUe Connect with our experts to get it right: https://lnkd.in/dbzNfKAK #GenAI #DigitalTransformation #AIImplementation #EnterpriseAI

⚖️ The mandate for AI maturity is pushing IT teams to deliver a balance between agility with governance. Are enterprise leaders prepared to scale AI securely? Grab your copy of the latest Beyond Big Data report to find out: https://hubs.la/Q03LZNP40

MCP (Model Context Protocol) the new open standard connecting AI models, tools, and data. Think of it as the USB for AI. Plug-and-play access to databases, APIs, and workflows. 👉 The challenge? Organizations still struggle to connect their AI initiatives with existing systems. That’s where we come in. At TransData we help enterprises integrate MCP into their AI stack, making their agents smarter, more reliable, and future-ready. If you’re exploring AI adoption but hitting integration roadblocks, let’s talk. #AI #MCP #AIAgents #Interoperability #FutureOfWork #TechTrends #digitalworkforce

What impact do AI agents have on the development of data products? In today’s data-driven landscape, leveraging AI agents is becoming essential for transforming how we gain insights and make decisions. This article explores the evolution of data products, detailing how AI agents enhance data utility and user experience. By incorporating advanced machine learning techniques, businesses can streamline processes, unlock new perspectives, and deliver tailored solutions that resonate with stakeholder needs. Let’s discuss how AI agents are shaping the future of data strategies and the critical role they play in refining our decision-making capabilities. What are your thoughts on integrating AI into your data products? Share your insights below and let’s engage in a meaningful conversation about innovation in our community. #DataScience #MachineLearning #AIAgents #CloudTechnology #DataProducts #Innovation #SnowflakeDevelopers https://lnkd.in/gRRR7Fxh

Excited to share that Dataiku has launched Agent Hub, a new collaborative workspace for building, governing, and scaling AI agents across the enterprise. This launch comes as our “Global AI Confessions Report: Data Leaders Edition” reveals: *72% of data leaders would let AI make critical business decisions without explanation. *Only 5% say AI outputs are traceable 100% of the time. Agent Hub gives enterprises a way forward, with ROI they can measure and systems they can trust. Full press release:  https://lnkd.in/gzMJp6-Q Survey report:  https://lnkd.in/g9majRJX #EnterpriseAI #AIAgents

Quick fixes won’t scale companies' generative AI ambitions. Successful gen AI-enabled organizations are designing flexible, open systems with reusable components and the freedom to choose best-in-class partners. In this article by McKinsey & Company's Curt Jacobsen, Erik Witte, Mike Kazmier, and Oscar Villarreal, the authors explain how this approach is helping business leaders accelerate their orgs now while preparing for what’s next: https://lnkd.in/dxqjGk6S McKinsey Digital #GenerativeAI #GenAI