There is a widening gap between the sophistication of manufacturing data models and the reality of the production line.

Google's Agentic Data Cloud rewires BigQuery, its data catalog and pipeline tooling around autonomous AI agents — not the human-scale queries enterprise data stacks were built for.

Failed NEET 3 times? No JEE rank? No coding background? Read how Sanjay B. became a Data Scientist at Syngenta without a ...

Compare Data Scientist vs Machine Learning Engineer roles in India 2026. Explore salary, skills, career paths, and find which ...

Google Cloud is turning the traditional enterprise data platform on its head, unveiling the Agentic Data Cloud infrastructure ...

Every secure API draws a line between code and data. HTTP separates headers from bodies. SQL has prepared statements. Even email distinguishes the envelope from the message. The Model Context Protocol ...

Oracle Corp. is extending its partnership with Google LLC’s Cloud to simplify how enterprise users interact with data, ...

AI is uncovering decades-old software bugs at scale, forcing a race to patch vulnerabilities before attackers gain access to ...

Anthropic is investigating reports that unauthorized users accessed its Mythos AI tool via a vendor, raising cybersecurity ...

Google launches AI agent suite at Cloud Next 2026 with Workspace Studio, A2A protocol at 150 orgs, and Project Mariner. The pitch: only Google owns the full stack.

TL;DR AI risk doesn’t live in the model. It lives in the APIs behind it. Every AI interaction triggers a chain of API calls across your environment. Many of those APIs aren’t documented or tracked.

Enterprises are struggling to scale agentic AI. Here’s what’s holding them back and what it takes to move from pilots to production. The post Agentic AI: Scaling from pilots to production appeared ...