Exploring the artificial intelligence journey for the Data-Driven Enterprise
Summary
In the next few decades, Artificial Intelligence (AI) will be the biggest commercial opportunity in the world—and with good reason. The ability to harness large amounts of data from many sources and effectively manage and leverage that data can lay the foundation for not only successful digital transformation, but also help establish a significant business competitive advantage as well.
But while that potential for competitive advantage, the benefits of process automation, and the ability to deliver more personalized interactions are all undeniably attractive, many companies struggle with the ability to properly implement AI, to move beyond initial pilots, as well as harnessing the power that AI can deliver. The primary reason for this is simple: There is a tremendous learning curve between the launch of an AI/data analytics system, and the successful integration, adoption, and active security and management of it. Successful AI requires clean data—and lots of it. It requires high-performing compute and storage both on-premise and/or in the cloud that can support sophisticated algorithms, often in real-time. It requires clear processes, scaled throughout an enterprise. And it requires an enterprise-wide commitment to use the insights AI provides to make decisions—and act on them.
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