When companies say “AI,” they are often using it as a catch-all term for a broad selection of technologies from machine learning and predictive analytics to natural language processing, object recognition and more. It’s a bit like that family member who calls any tablet an ‘iPad’, regardless of the actual device they’re referring to. To the user, the capability of the device or solution is more important than the technology under the hood.
But the generic use of the term “AI” has left many IT and business professionals confused about what technology they actually need to procure in order to achieve a desired outcome. Most have explored technologies they think hold the promise of “AI,” and, in many cases, have been disappointed in pilots or even full use cases conducted in 2018.
It’s time for businesses to look at the wide range of solutions that are more precisely termed “Augmented Intelligence.” Redefining “AI” as augmented intelligence can help focus purchases and deployments, and return measurable value.
Here are three key learnings I believe companies will realize when implementing augmented intelligence in 2019.
Getting value from AI requires a reality check
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