It’s widely known that to succeed with AI, a company needs to have some distinctive information. Wolters Kluwer, the Netherlands-based professional information, software solutions and services company that does business in over 180 countries today, has never lacked for that resource. It was founded in 1836 as a schoolbook publishing company, and over the years merged with other publishers and eventually began developing and acquiring digital information capabilities.
Nancy McKinstry, the CEO and Chair of Wolters Kluwer, became its leader in 2003. She began to transform Wolters Kluwer into an expert solutions company, hiring and developing experts with deep expertise in areas like healthcare, tax, risk and compliance, and legal. The company also created a global Digital eXperience Group (DXG) to help speed time-to-market and innovation in digital products, as well as a Global Business Services (GBS) group to provide strategic execution services. Today, the company’s revenues from publishing are less than 5% of the total—down from over 80% when McKinstry became CEO.
By the time AI became more prevalent in the late 2010s, Wolters Kluwer was well into the business of providing “expert solutions” to its customers. At this point there were hundreds of experts in various fields providing expertise to customers, and fortunately Wolters Kluwer captured the data on the advice it provided and the outcomes for the customer. One might notice that this is a perfect situation to begin modeling and predicting those outcomes with machine learning. By 2016, the company had created its first AI-enabled product: CCH IQ used machine learning to help tax service providers identify which clients are affected by changes in tax legislation, assess the impact of the changes on client tax returns, and understand opportunities for additional tax services to clients.
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