New & Notable
Manage
AI inference cost optimization: An enterprise guide
Inference is the largest long-term expense in enterprise AI deployments. Businesses can keep AI inference costs in check with these seven optimization strategies.
Evaluate
Why AI writing can't be great
In today's rapidly changing writing landscape -- just kidding. Most readers are savvy enough to recognize specific phrases as AI tells. Why does AI write like that, and why does it matter?
Manage
Businesses have AI tools. Why aren't employees using them?
As enterprise AI deployments accelerate, businesses find workflow redesign, change management and employee trust, not just the tools, determine adoption success.
Evaluate
To make policy, policymakers should use AI
Too often, policymakers base their organization's policies for AI usage on what they read in the news instead of first-hand experience working with the latest AI features.
Trending Topics
-
AI Infrastructure Manage
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.
-
AI Technologies Manage
How to ensure interpretability in machine learning models
When building ML models, developers can use several techniques to make models easier for humans to interpret, leading to improved transparency, troubleshooting and user acceptance.
-
AI Platforms Evaluate
The best AI chatbots for 2026: Compare features and costs
AI chatbots are smarter, faster and more versatile than ever. See how top platforms like OpenAI's ChatGPT, Anthropic's Claude and Microsoft's Copilot stack up in this hands-on comparison.
-
ML Platforms Manage
7 machine learning challenges facing businesses
Machine learning challenges cover everything from ethical issues to data quality and user acceptance concerns. Learn about seven common obstacles.
-
AI Business Strategies News
When orbital AI data centers become business reality
Shrinking launch costs, hyperscaler validation, serviceable hardware, manageable insurance risks and earthly energy constraints will thrust data centers into orbit and beyond.
-
Applications of AI Evaluate
To make policy, policymakers should use AI
Too often, policymakers base their organization's policies for AI usage on what they read in the news instead of first-hand experience working with the latest AI features.
Sponsored Sites
-
Security
One Identity | Integrated Cybersecurity for all Your Identities
Learn how One Identity provides integrated cybersecurity solutions, delivering a truly unified identity platform and streamlining management across on-premises and cloud resources.
-
Artificial Intelligence
HPE & Intel: Harness AI
Learn how HPE & Intel are pioneering advancements in artificial intelligence (AI) and machine learning (ML) technologies. As a global leader in semiconductor innovation, Intel continues to drive the evolution of AI across diverse industries, from healthcare and finance to autonomous vehicles and edge computing. Explore the latest developments and strategies shaping the future of AI-driven technologies.
-
Accelerating Application Transformation with Amazon Q Developer
Amazon Q Developer transformation capabilities accelerate large-scale transformation of enterprise workloads with domain-expert generative AI agents to simplify .NET porting, VMware modernization, mainframe application modernization, and Java upgrades. Put experience of AWS and the power of generative AI to work to simplify your application migration and modernization journey and transform your business.
Featured Authors
Find Solutions For Your Project
-
Evaluate
When orbital AI data centers become business reality
Shrinking launch costs, hyperscaler validation, serviceable hardware, manageable insurance risks and earthly energy constraints will thrust data centers into orbit and beyond.
-
Why AI writing can't be great
-
To make policy, policymakers should use AI
-
AI and robotics yield bumper crops down on the farm
-
-
Problem Solve
AI scaling is where most companies stall. Here's why
Expanding AI use requires new operating models, talent and mindsets -- not just more resources. Companies fail because they try to scale experiments instead of redesigning systems.
-
Controlling AI models is harder than building them
-
AI is supposed to cut lots of jobs? Not so fast
-
How to keep data silos from damaging your AI projects
-
-
Manage
AI inference cost optimization: An enterprise guide
Inference is the largest long-term expense in enterprise AI deployments. Businesses can keep AI inference costs in check with these seven optimization strategies.
-
Businesses have AI tools. Why aren't employees using them?
-
How to ensure interpretability in machine learning models
-
AI turns data center power into an enterprise challenge
-
Enterprise Artificial Intelligence Basics
-
Get Started
When orbital AI data centers become business reality
Shrinking launch costs, hyperscaler validation, serviceable hardware, manageable insurance risks and earthly energy constraints will thrust data centers into orbit and beyond.
-
Get Started
AI and robotics yield bumper crops down on the farm
Autonomous tractors roam the fields 24/7, while AI, computer vision and machine learning harvest fruits, increase milk production, limit pesticides and boost crop yields.
-
Get Started
AI in law offices: How it's being used and the risks
Document discovery, court motions, patent protection, focus groups and client calls are tasks where AI saves law firms significant time and costs, while keeping humans in the loop.
Multimedia
Vendor Resources
-
News
View All -
Enterprise applications of AI
MIT study warns of major AI risk. Is governance keeping up?
AI experts warn of catastrophic AI risks, but governance lags, with security concerns driving policy while broader risks aren't being fully addressed.
-
AI technologies
SpaceX IPO aims for AI and orbital data centers
The record-setting debut asks investors to buy into an integrated hardware and software infrastructure play that spans space, energy and data resources.
-
AI technologies
Trump AI order targets frontier model prerelease review
The White House's voluntary AI executive order creates a prerelease review process for frontier models, raising questions about release timelines, vendor trust and enterprise procurement.
Search Enterprise AI Definitions
- What is automated machine learning (AutoML)?
- What is a data scientist? What do they do?
- What are AI agents? Types and examples
- What is an intelligent agent? Definition, use cases and benefits
- What is natural language processing (NLP)?
- Agentic AI explained: Key concepts and enterprise use cases
- What is a neural network?
- What is a robot? Definition, purpose, uses