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Even though most enterprise organizations use data and analytics to drive strategy, only 39% of executives believe their organizations manage data as an asset, and even fewer (24%) view their companies as being data-driven. For companies striving to capitalize on the promises of data and analytics, it can help to study successful leaders. Let’s look at how three companies benefit significantly from analytics.

Business leaders who understand the different types of AI are better able to harness its potential to drive innovation and efficiency. Let’s review the differences between traditional AI and generative AI and the types of uses for which each of them is best suited.

It seems like everyone these days is incorporating generative AI (GenAI) to improve efficiency, productivity, and costs. GenAI holds the promise to be a game changer, but many businesses aren’t sure whether or how it’s right for them. If you find yourself questioning whether AI is the right fit for your business, you’re not alone. Despite all the buzz, GenAI isn’t seeing universal adoption just yet. In fact, research by The Register finds that a whopping 81% of mid-market organizations are currently avoiding AI. They just don’t see the benefit. While caution is understandable before jumping on the GenAI bandwagon (see our blog post about this), the pressure is mounting to harness GenAI and reap its benefits. So, what’s the smart way forward? In a word: planning. GenAI is a journey, and like any trip, it requires a roadmap and thoughtfully planned steps. Here’s some guidance for charting your course in GenAI.

We believe that any data-centric organization can benefit from using hardware-based accelerators. But the tricky part is choosing the right one for the job. It can be challenging to navigate the sea of accelerator options available to you. Adding to the confusion, accelerator technologies are still rapidly evolving, which means the hardware manufacturers are far from standardizing on terminology or definitions. Use this article to get started with the basics.

We believe that any data-centric organization can benefit from using hardware-based accelerators. But the tricky part is choosing the right one for the job. It can be challenging to navigate the sea of accelerator options available to you. Adding to the confusion, accelerator technologies are still rapidly evolving, which means the hardware manufacturers are far from standardizing on terminology or definitions. Use this article to get started with the basics.

Microsoft released an email that introduced a major corporate restructuring. The biggest change? Artificial intelligence (AI) has surged to the top of priority list for the Redmond-based giant. “Cloud + AI Platform” is now one of the company’s three divisions (the others being “Experiences & Devices” and “Microsoft AI and Research”). This restructuring reflects the […]