Data Governance | News, how-tos, features, reviews, and videos
Organizations gain a strategic advantage with a life-cycle approach to AI cyber risk that acknowledges the rapid evolution of AI technologies, threats, and regulations. Here’s how.
The rush to the cloud was an expensive experiment for many. AI could be a repeat without careful evaluation and planning.
What metrics do business and tech leaders trust for measuring ROI on dataops, data governance, and data security? We asked the experts.
The governance journeys of SaaS and Web2 tell us that today’s ad hoc AI governance will give way to a continuous and automated approach.
The uncontrolled and ungoverned AI apps your employees are using are becoming a real threat to cloud deployments, but banning them won’t work. Here’s what to do.
With AI observability, we can guard against hallucinations, catch irrelevant and incomplete responses, and identify security lapses in generative AI applications — ensuring they meet the needs of the business.
AI red teaming offers an innovative, proactive method for strengthening AI while mitigating potential risks, helping organizations avoid costly AI incidents. Here’s how it works.
How can enterprises secure and manage the expanding ecosystem of AI applications that touch sensitive business data? Start with a governance framework.
This issue showcases practical AI deployments, implementation strategies, and real-world considerations such as for data management and AI governance that IT and business leaders alike should know before plunging into AI.
Creating a center of excellence to manage generative AI effectively will increase the chances of success throughout your organization. Here’s how to get it right.