Explainable AI: Why It’s Important to You and Your Clients

Bernadette Wilson,

Explainable AI not only delivers a decision or prediction but also gives users confidence by explaining how the solution was determined.

What is Explainable AI?
AI algorithms are designed and trained (and retrained) to work accurately. However, it’s typically not clear to users how the algorithm works. McKinsey research from 2020 found this ambiguity led to lower-than-predicted adoption rates because users didn’t trust the system. It’s not difficult to understand. A manager responsible for customer service and satisfaction won’t want to put faith in a solution that doesn’t deliver results as well as a human agent would. Furthermore, if AI is controlling the starts and stops of heavy equipment that could cause serious injury to its operators, those employees will want to know it will come through in the clutch.

Michael Wu, Chief AI Strategist at PROS, sees explainable AI as “the last nudge to get executive buy-in.” “As more companies embrace a digital-first way of doing business, explainable AI will emerge as a major catalyst to get executive adoption of AI-based tools,” he says. “Initially, the fear factor will persist – companies will still be afraid to relinquish any control to decision-making AI. However, those who use XAI to overcome this fear will gain significant efficiency and competitive advantage in the market, leaving those formerly paralyzed by fear with no other choice but to adopt AI solutions themselves.”

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