Preface
A significant transformation is underway in the marketplace.
Mountains of data are being generated on a daily basis. Business operations, online transactions, vehicles and smart homes, our cell phone, and the increasing prevalence of the Internet of Things (IoT) means that data is continuously being generated and stored.
This growth in data vastly outstrips growth in the supply of technical analysts as demand for their services proliferates across industries. Companies, governments, and organizations are rightly asking how they can possibly provide value from these data volumes with their existing analytical capabilities and staff while determining where they need to invest to meet this growth.
When deployed effectively, Artificial Intelligence (AI) provides the necessary force multiplier, allowing organizations to generate insights not possible even a few years ago.1 AI provides organizations with the ability to process vast amounts of data by training algorithms to automate current processes, generate new insights, and then present these insights so that decision makers can act.
Rapid gains in computing power, inexpensive storage solutions for large volumes of data, and new research in algorithm development make AI increasingly more accessible. These three keys—processing power, data, and algorithms—bring us ...
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