Manufacturing insights
58 results found
Who Should Own OT Security? The Answer Is More Nuanced Than You'd Think
As IT and OT environments converge, the old model of siloed security teams is breaking down. Manufacturers are best served by a new approach, one that balances executive ownership with the realities of the plant floor.
Matching the 'Clock Speed of AI' with Softchoice CEO Andrew Caprara
Softchoice CEO Andrew Caprara explains why AI transformation must be CEO-led, and strips the hype away from AI agents, describing them as simply data, a set of rules and connections into existing systems. He argues small and mid-market companies are often better positioned than large enterprises to move quickly, since they carry less legacy technical debt and fewer layers of decision-making, but only if they start with one workflow rather than attempting an enterprise-wide transformation.
From $100,000 to $2 Million a Month: What AI at Scale Really Costs
WWT CFO and Chief Data Officer Tom Strunk and CIO Kevin Dana explain how organizational leaders can create AI cost visibility, govern variable consumption and connect rapidly growing token usage to measurable business outcomes.
Apple on the Frontline: What It Takes to Deploy iPhone and iPad at Shift Scale
Legacy MDM update management ends in iOS 27, iPadOS 27 and macOS 27. Why these programs fail on operations, not hardware, and the four decisions ahead.
Eli Lilly & Company Chief AI Officer on Why Lilly Bet Big on On-Prem AI
Eli Lilly & Company Chief AI Officer Thomas Fuchs explains why the pharma giant built its own on-prem AI supercomputer, LillyPod, instead of solely relying on the cloud. Fuchs, who has built machine learning infrastructure since long before AI was mainstream, argues that owning compute at scale changes what's possible for medicine discovery, development, and delivery.
Partner POV | Edge Computing for Smart Manufacturing
Edge computing revolutionizes manufacturing by enabling real-time AI-driven decisions, reducing latency, and enhancing operational resilience. As factories become more autonomous, integrating edge with cloud and on-premises systems is crucial. Manufacturers must prioritize latency-sensitive tasks, streamline data flow, and standardize architectures to scale efficiently and maintain competitive advantage.
Agentic AI in Life Sciences Manufacturing
Every life sciences application is quietly shipping AI agents inside routine upgrades; no strategy meeting required. This replays the ERP sprawl mistake, only faster and quieter, and this time touching GxP decisions regulators expect to trace. We predict that by 2027, it will be everywhere. The fix is deciding, now, who owns the architecture and who owns the agent.
Getting Our Hands on Physical AI: What We're Learning in the Field
Inside our work with a humanoid robot on a real manufacturing floor
AI Inferencing Without the Infrastructure Overhaul
How the NetApp AIPod Mini with Intel lets organizations put proprietary data to work in existing data centers, at department scale, without GPU complexity. AI inferencing doesn't have to mean GPU procurement, liquid cooling, or a rearchitected data center. The NetApp AIPod Mini with Intel was built for the organizations that already have the data — and need a production path that fits where they are today.
WWT Industry Solution Experience (WISE)
WWT's Demonstration lab for industrial IT/OT collaboration
OT Security Roundtable: Navigating the IT-OT-IoT Alignment Challenge
OT Security experts at World Wide Technology sit down for a conversation about the growing challenges of IT-OT-IoT alignment. They share practitioner perspectives on securing operational technology environments, bridging the technical and cultural gap between IT and OT teams, and what organizations need to consider as industrial systems become increasingly connected.
The Data Flywheel: How Kiewit Built a Foundation That Makes AI Actually Work
Kiewit's Chief Data and Analytics Officer, Matt Pappas, has spent 15 years building machine learning into one of the world's largest construction companies — long before "AI-ready" was a buzzword. In this episode of teh AI Proving Ground Podcast, he shares what he's learned about data culture, decision science, and the discipline most enterprises are skipping when it comes to driving AI strategy at scale.