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Building AI builders: Playbook for closing the AI knowledge-capability gap | Amazon Web Services
The biggest barrier to AI adoption isn’t awareness. It’s the gap between talking about AI and building with it. Professionals whose primary role isn’t writing code, but whose daily work increasingly depends on AI solutions, don’t need engineering backgrounds to start building AI capability. They need
Automate remediation post AWS DevOps Agent investigation | Amazon Web Services
Reducing the time between incident detection, investigation, and remediation is a critical priority for organizations running production workloads on AWS. When an issue arises, on-call engineers often need to quickly diagnose the problem across application components, identify the root cause, and apply the fix, often in the middle of the
How Qlik built grounded, enterprise-scale AI with Amazon Bedrock | Amazon Web Services
Building grounded AI on Amazon Bedrock, Qlik Answers tackles a common enterprise problem: employees aren’t short on data. They are short on a fast way to ask a real question of it and get an answer they can trust. Analysts spend hours searching through documents, dashboards, and institutional memory
Beyond hours saved: Building the business case for agentic automation | Amazon Web Services
Agentic automation, software that reasons and adapts to complete tasks, is showing up on AI center of excellence (AI CoE) roadmaps. But the standard way companies justify automation investments, hours saved times labor cost minus build cost, was designed for rule-based tools like robotic process automation (RPA). That model misses