AI Infrastructure: Page

Questions to ask when evaluating AI-ready data center providers

AI growth exposes data centers to power limits, cooling issues, water scarcity and regulatory pressure. Explore the key questions to raise with vendors.

By Kinza Yasar • July 30, 2026

The AI metrics trap: Measuring speed but missing value

Rising token counts and pull request throughput look impressive, but they miss where AI creates real value: preventing bad decisions and surfacing blockers before they cost time.

By Sireesha Pulipati • July 24, 2026

AI turns data center power into an enterprise challenge

AI workloads are straining data center power and grid capacity, forcing enterprises to rethink workload, cloud and infrastructure strategies beyond traditional approaches.

By Varun Raj • July 2, 2026

Controlling AI models is harder than building them

Before companies safely grant autonomy to AI agents deployed in their business processes, they must first establish an infrastructure of governance, accountability and control.

By Liz Hughes • June 30, 2026

When to run AI on-premises vs. in the cloud

AI deployment decisions don't exist in isolation. The best environment is the one that delivers the most value for each specific AI workload given cost and governance constraints.

By Abhishek Jadhav • June 23, 2026

Autonomous warehouse drones streamline inventory control

Autonomous indoor AI drones join the workforce, moving about factories and warehouses to track inventory, identify missing products and predict equipment maintenance.

By Chuck Martin • June 17, 2026

Beautiful insanity: AI buildouts lead to long lead times

As hyperscalers build out their AI infrastructure, enterprises are seeing the effects in long waits for equipment and a shift to distributed architecture.

By Jennifer English • May 22, 2026

Artificial general intelligence: So close yet so far?

Before signing off on their AI strategies, businesses should weigh the anticipated arrival and potential impact of artificial general and super intelligence on future operations.

By Stephen Bigelow • May 20, 2026

Communities call for transparency in AI data center deals

Your company might not be building an AI data center, but your AI workloads likely run in them. Here's what you need to know about the land-use war around data center development.

By Everett Bishop , Olivia Wisbey • May 6, 2026

How to use AI agents for infrastructure management

AI agents enable businesses to automate a variety of tasks, including infrastructure development. However, left unchecked, they can wreak havoc at the infrastructure layer.

By Wisdom Ekpotu • April 21, 2026

Infrastructure requirements for physical AI systems

Physical AI systems are becoming a priority for companies because of their strategic and operational advantages. But businesses must contend with their infrastructure needs.

By Kerry Doyle • April 17, 2026

Exploring the context layer for AI systems

To meet the needs of AI's increasing agency, context layers capture the missing reasoning, business rules and decision rationale that power truly aligned, autonomous AI systems.

By Abhishek Jadhav • April 16, 2026

AI agents are only as smart as the data that feeds them

Using business semantics is key to making AI agents deliver accurate insights. Aligning an organization's data with its business logic ensures trust and smarter decisions.

By Rashmi Choudhary • April 16, 2026

The business case for a multi-cloud AI strategy

Using a single cloud provider for AI infrastructure can have its limitations. Discover the benefits businesses can realize by opting for a multi-cloud AI strategy.

By Stephen Bigelow • April 9, 2026

How to choose a data center for AI workloads

Variables like power and network capacity affect the ability of data centers to support AI workloads. But not all AI workloads require the most powerful data center capabilities.

By Chris Tozzi • April 8, 2026

Open source AI: What it means for enterprise innovation

Open source AI is transforming enterprise innovation with greater flexibility and control, but organizations must address governance, security and operational challenges to scale effectively.

By Kinza Yasar • April 1, 2026

AI ethical red flags businesses must avoid

AI tools are everywhere in businesses, but are ethical best practices keeping pace? Here are the ethical AI red flags business leaders are seeing, and how to avoid them.

By George Lawton • March 31, 2026

Time to rethink cloud architecture for enterprise AI

Enterprise AI systems demand cloud architectures that emphasize persistent state, governance and adaptive infrastructure to ensure long-term reliability.

By Varun Raj • March 28, 2026

How to preprocess different types of data for AI workloads

Data preparation for AI differs by data type. However, common themes include improving data quality, ensuring consistency, reducing computing demands and enhancing model performance.

By Stephen Bigelow • March 24, 2026

Is GenAI villain and hero in data center power drama?

GenAI's infrastructure requirements drive up power demands for hyperscalers and other large data centers, but GenAI, and AI-based automation, could also help manage consumption.

By John Moore • March 13, 2026

Is neuromorphic computing the future of AI hardware?

AI hardware is hitting its limits. Is neuromorphic computing with its reduced energy use and latency a viable alternative? Hear one expert's take on this emerging technology.

By Abhishek Jadhav • Feb. 26, 2026

Optimizing hybrid cloud architecture for AI workloads

Hybrid cloud architecture can help with the unique scalability, hardware and governance needs of AI workloads. But is it the right choice for your business?

By Chris Tozzi • Jan. 13, 2026

The big AI misconception: Most AI apps run on CPUs, not GPUs

While the industry touts GPUs as the foundation for AI applications, CPUs can still provide the reliable and quick processing that's necessary for most daily AI use cases.

By Stephen Catanzano • Nov. 19, 2025

What is edge AI?

Edge artificial intelligence (edge AI) is a paradigm for crafting AI workflows.

By Nick Barney, George Lawton • Sept. 17, 2025

How Meta’s $10B cloud deal with Google helps it scale AI

The move favors both companies: It shows Google's leadership in cloud infrastructure and furthers the social media giant's goal of becoming the leader in AI superintelligence.

By Esther Shittu • Aug. 27, 2025