Responsible AI is an umbrella term encompassing fairness and equity, social and environmental impact, and privacy and safety. A more precise definition depicts responsible AI as systems that are consistent with a company's organizational values, while still delivering transformative business impact, according to Steven Mills, chief AI ethics officer, managing director and partner at Boston Consulting Group. "The end there is really important," said Mills, co-author of the report. "I can build it responsibly, considering my values and deliver business impact. Some people think you can do one or the other and I'd argue that's a false choice. You can absolutely do both and you should do both."

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Even though responsible artificial intelligence (AI) is considered a top management concern, a newly released report from Boston Consulting Group and MIT Sloan Management Review finds that few leaders are prioritizing initiatives to make it happen. Of the 84% of respondents who believe that responsible AI should be a top management priority, only 56% said that it is, in fact, a top priority -- with only 25% of those reporting their organizations has a fully mature program in place, according to the research. Further, only 52% of organizations reported they have a responsible AI program in place – and 79% of those programs are limited in scale and scope, the BCG/MIT Sloan report said.

Responsible usage of AI is growing extensively since 2017 and 2021 will see expansion fully into the operationalization of AI ethical principles, frameworks, and policies. Operationalization defined as taking principles into useful practice and thus requiring prioritization for businesses. The challenge is focusing on the top initiatives which I will identify in this article. In my pro bono contributions across 100 global programs with non-profits, I am seeing businesses are still challenged in moving from proof-of-concept responsible AI applications, within one business unit, to scaling across the enterprise. With more than 300 AI principles, frameworks, policy, and regulatory initiatives--businesses must keep current of the top contenders as AI usage grows.