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Dinanath Kholkar

Vice President & Global Head, Analytics


  • Large enterprises that take a Machine FirstTM approach to digital transformation are using Artificial Intelligence (AI) to automate both manual and knowledge work. While the technology will supplant some workers, we believe the most effective implementations will help people do their work better, whether that means a robot performing repetitive tasks in a factory, freeing up workers for more creative tasks, or an AI system illuminating traffic patterns in a retail store so that salespeople can better serve shoppers.
  • The benefits of using AI and machine learning are piling up fast. These intelligent systems can help companies react faster to fleeting revenue opportunities, such as identifying customer needs (at the moment when customers experience them) because AI-based machines are tracking those needs at a volume and pace that’s beyond the capability of humans. They can pinpoint organizational bottlenecks, such as suboptimal manufacturing processes and delivery routes to make them more efficient, reducing waste and costs. They can help organizations make better hiring decisions by logging the qualities of a firm’s most productive people and using them to screen potential employees. They can automate processes, from identifying suspicious financial transactions with greater accuracy (and in less time) than humans, to predicting when a machine might fail so it can be fixed before it brings a line to a grinding halt. Without human intervention, they can ensure that corporate purchases comply with an organization’s procurement policies.
  • With this wide array of opportunities, a clear challenge presents itself: to be effective, all these systems rely on data that must be continually refreshed and as complete as possible. Dated or incomplete data yields results that are meaningless, or worse, lead to errors.
  • The answer to this challenge is for enterprises to build unbiased and self-improving machines that continuously take in more data, from more sources.