He said, “The healthcare discussions were already underway (before the creation of the Watson business unit) ­­­—we didn’t know where in healthcare, but we knew healthcare was a good domain. One of the first things I had to do was figure out which market do we take Watson to. What became apparent to me after we did some work was that information intensive industries like healthcare, insurance, banking, telecoms where there is a tremendous amount of semi-structured and unstructured data – not just transactions like retail transactions or supply chain transactions but information like doctors’ notes, prospectuses on a stock purchase agreement or insurance policies—where there is a lot of human language that knowledge workers have to read and understand, are a great target for Watson, because until Watson, machines could not understand human language and unstructured information."

Watson is designed to question massive amounts of structured and unstructured data and produce useful answers. It is built on IBM’S parallel software architecture DeepQA, which works out what the question is asking, and then works out the answers for these questions, thereby creating a thread for each.

With moderate revenue generated, IBM still has high expectations from Watson and hopes to generate the expected revenue of $10 billion annually in 10 years. However, for the time being, IBM has not “figured out how to generate a reliable revenue stream,” states a report.

Will Watson be IBM’s dark horse, we need to watch and watch.