State and local governments are embracing data modeling and governance strategies to advance efficiency, sharpen decision-making, and elevate their service delivery. In so doing, they’re helping ...

Published in AI & Society, the study titled “Data-centric AI governance for responsible organizational value: evidence from a ...

Today, AI relies on data, and many organizations are treating AI systems like traditional applications. From my experience ...

Organizations need to be less trustful of data given how much of it is AI-generated, according to new research from Gartner. As more enterprises jump on board the generative AI train — a recent ...

More than any other factor, the hyperabundance of accessible data has powered today’s surge in AI adoption and generative AI capability. Collecting, cleaning, organizing, and securing that data for AI ...

Responsible AI is an investment in long-term sustainability. The absence of governance can lead to model drift, eroding customer trust and increasing risk.

Enterprises no longer need to "lift and shift data" to get the answers they need Traditional eDiscovery and governance ...

Abstract: The increasing reliance on artificial intelligence (AI) and advanced analytics to gain competitive advantages has elevated the importance of robust data governance frameworks. This article ...

Achieving business success today increasingly depends on getting the right information at the right time — so people can make ...

Artificial intelligence (AI) is transforming industries by automating processes, enabling smarter decisions, and unlocking new avenues for innovation. According to recent Semarchy research, 74% of ...

Data fabric is a powerful architectural approach for integrating and managing data across diverse sources and platforms. As enterprises navigate increasingly complex data environments, the need for ...