How to build trust in AI with guardrails

In part two of our Leadership Perspective with Ben Schreiner of Amazon Web Services (AWS), we continue the conversation on AI business transformation essentials and look ahead to AI’s long-term impact and its role in the years to come. Read it here: https://lnkd.in/dWidjktw #EnterpriseAI #AgenticAI #AIFuture #AIInnovation #ModernDataStrategy #BenSchreiner #AWS #StayinFront #OnDeviceAI #RetailOptimization #ConsumerGoodsTech #AITransformation

🤖 AI that doesn’t just think - it acts. Welcome to Agentic AI on AWS Forget AI that only answers questions, this one actually plans, executes, and completes tasks safely inside AWS. Meet Amazon Bedrock AgentCore, the new way to let AI automate real cloud jobs, from log checks to reports and data workflows. It’s practical, powerful, and just the start of the Agentic era. 👉 Read more: https://lnkd.in/gzmwYXuX #AgenticAI #AWS #AmazonBedrock #AmazonWebServices #CloudComputing #AIAutomation #CloudAutomation #AIinCloud #DevOps #CloudEngineering #MachineLearning #ArtificialIntelligence #CloudOps #MLOps #FutureOfWork #TechInnovation #AIDriven #Serverless #AWSTools #CloudCareers

The demand for deploying AI Agents and LLM-powered applications on the cloud is skyrocketing. Every company is racing to set up the right infrastructure to build, deploy, and scale their intelligent systems efficiently. If you’re building on AWS, one of the most powerful ways to bring your AI ideas to life is through Amazon Bedrock — a fully managed service designed to help you build, scale, maintain, and deploy foundation models and AI agent applications seamlessly. In my latest post, I break down everything you need to know to get started with AWS Bedrock — from selecting the right foundation model to integrating it into your architecture and scaling it for production. Whether you’re just exploring LLM infrastructure or preparing to deploy your first AI agent, this guide will give you the clarity and confidence to move fast while staying scalable. View post at --> https://lnkd.in/egySAYjT #AI #AWS #Bedrock #LLM #CloudComputing #AIAgents #MachineLearning

The AI advantage isn’t custom code—it’s knowing what NOT to build. Your competitors aren’t failing at AI because of technology. They’re failing at strategy. 🎯 I just watched another company spend $500K building a custom AI model that AWS offers for $200/month. Here’s what nobody tells you about AI implementation: The expensive mistake: Building everything from scratch because it feels more “innovative” The smart play: → Use Azure’s pre-trained models for document processing → Leverage GCP’s AutoML for quick prototyping→ Deploy AWS SageMaker when you need scale The companies winning with AI aren’t the ones with the biggest budgets. They’re the ones who know which problems to solve vs. which solutions to buy. Last month, a client cut their data processing time from 3 days to 4 hours. Not with custom code. With the right cloud service configured correctly. Smart AI strategy isn’t about being cutting-edge. It’s about being strategic with what already exists. What’s the biggest AI misconception you’ve encountered? #ArtificialIntelligence #CloudStrategy #BusinessEfficiency #DigitalTransformation #TechLeadership #AWS #Azure #GoogleCloud #Innovation

Dynatrace, the AI-powered observability platform, announced today that it has achieved the «AWS Generative AI Competency». This recognition highlights the company’s role as an AWS Partner helping enterprises and the AWS Partner Network accelerate the adoption of generative AI technologies Details :👇 https://lnkd.in/esV2dHRS Amazon Web Services (AWS) Dynatrace #fintech_gate

🚀 Agentic AI meets AWS Cloud ☁️ Agentic AI systems are transforming the way intelligent applications act autonomously, plan workflows, and make real-time decisions — but behind this intelligence lies something even more powerful: AWS. 💡 🔹 With AWS services like: ✅ Amazon Bedrock – to access and build with foundation models (Claude, Titan, Llama 3, etc.) ✅ AWS Lambda – to automate agentic workflows ✅ S3 + DynamoDB – to store memory and retrieval data ✅ SageMaker – to train, fine-tune, and deploy AI agents ✅ Step Functions – to manage agent orchestration Developers can now build Agentic AI pipelines that are scalable, cost-efficient, and production-ready. 💬 Imagine combining LangChain or Hugging Face with AWS Bedrock — your AI agent can plan, reason, and act across data sources, all deployed on the cloud. This is the next era — Cloud + Cognition = Agentic Intelligence. ☁️🤖 #AWS #AgenticAI #GenerativeAI #LangChain #Bedrock #AIInnovation #CloudComputing #LLM #AIonAWS

🔓 Unlocking scalable AI doesn't have to be a maze! 💡🚀☁️ Discover practical strategies for selecting the right cloud platforms, leveraging containerization, and orchestrating secure, enterprise-ready AI deployments. In our newest article you will: ✅ Explore leading AI cloud platforms like AWS SageMaker, Azure ML, and Google Vertex AI ✅ Understand modular and hybrid architectures for flexibility and resilience ✅ Harness containerization with Docker and orchestration with Kubernetes for automated scaling ✅ Implement identity-first security and compliance frameworks to safeguard your AI workloads If your team is navigating the path to operationalize AI successfully, this article offers actionable insights and clear strategies for scalable, secure AI deployments leveraging cloud-native technologies. Read 👓 or listen🎧 to our newest article https://lnkd.in/eS8dPmtF Need a partner to guide you? The experts at Cloud Latitude can help you select the right cloud platforms and architectures, and implement identity-first security frameworks to safeguard your AI workloads and accelerate deployment. #AIDeployment #CloudArchitecture #CloudComputing #EnterpriseAI #MLOps #CloudLatitude

Todays keynote shares insight into what the Government Digital Service and Department for Science, Innovation and Technology is doing to increase the adoption of AI across wider government... #thinkai Amazon Web Services (AWS) Zaizi

AI training highlight for AWS Partners AWS AI FastTrack Program is Now Open: AWS has launched a global, hybrid learning program for AWS Partners • Get hands-on experience with latest AI services • Direct access to AWS experts • Structured learning paths (sales or technical audiences) • Industry certification vouchers and readiness training There are really helpful Generative AI and Agentic AI industry use cases and gamified labs. The program runs through October. #AWS #AI #CloudComputing #AWSPartner #GenerativeAI #AITraining https://lnkd.in/gNzKsXBq

After years of big data building the knowledge core for organizations, and RAG prototypes making that knowledge accessible through natural language, I think the next big wave is autonomous agents. RAG still relies on humans to do the heavy lifting. It’s a big efficiency gain, but autonomy takes things way further. My “wow” moment: I had to extract data from a 90s legacy system — normally a nightmare. By connecting Ghida (analysis tool) with Claude Desktop, I was able to understand complex bit-level data structures and reverse engineer the software in just 1–2 days. Research backs this up: agents boost non-experts disproportionately. I’m not a security researcher, but with these tools I could solve problems I’d never imagined tackling. The real potential isn’t just faster workflows for experts — it’s enabling people to work effectively outside their core domain.