IBM’s stalled ambitions with Watson show AI isn’t elementary, but can work when focused 

Contextual variability can be a roadblock to successful use of artificial intelligence, say Carlos Cordon and Amin Kaboli

When IBM’s Watson supercomputer won US TV show “Jeopardy!” in 2011, it was heralded as a sign of how artificial intelligence would revolutionize industries from healthcare to finance and agriculture and retail. 

In 2015, the company founded Watson Health with the goal of using its artificial intelligence platform to help solve healthcare problems, including improving the way doctors prescribe treatments for cancer and diabetes. But a series of setbacks dashed those expectations and culminated in the sale this week of part of the Watson Health business to private equity firm Francisco Partners. 

While some people might see IBM’s scaling back of its lofty ambitions as a failure, we believe this shows how artificial intelligence succeeds best in business when it is deployed in a very focused context-dependent way. 

Instead of closing Watson Health, IBM…