There are plenty of organizations that are dabbling with AI, but relatively few have decided to go all in on the technology. One that is decidedly on that path is Mastercard. Employing a combination of acquisitions and internal capabilities, Mastercard has the clear objective of becoming an AI powerhouse. Just what does that term mean, and how is it being applied at the company?
What’s an AI Powerhouse?
Some refer to the idea of aggressive, pervasive adoption of AI as being “AI first.” Others use the term “AI fueled” or “all in on AI” (that’s Tom’s favorite, since it’s the title of his forthcoming book on the subject). Mastercard prefers “AI powerhouse.” Regardless of the descriptor, the concept refers to organizations that apply AI throughout their businesses, using it to either transform operations or develop new products, services, and business models, or both. These companies employ multiple AI technologies, develop many use cases, and put them all into production deployment.
As we’ve noted in previous columns, this level of engagement is unusual. In a 2019 MIT Sloan Management Review and Boston Consulting Group AI survey, 65% of respondents said they hadn’t seen value from their recent AI investments, in part because relatively few projects had been put into production. Survey respondents reported being skittish about the technology, with 45% saying they perceived some risk to their business from AI (up from 37% two years earlier).
To succeed in becoming an AI powerhouse, companies need to have a set of prerequisites in place. Senior leaders of the organization have to be on board and engaged with the effort because AI use cases must enable new ways of doing business and AI powerhouses inevitably invest at least a fair amount in AI. A lot of high-quality data is needed because that’s how machine learning models are trained. From a talent perspective, companies need smart individuals who can develop and apply AI systems. And it’s important that an organization have an ethical compass about how it uses AI and other information resources.
Continue reading: https://sloanreview.mit.edu/article/becoming-an-ai-powerhouse-means-going-all-in/
What’s an AI Powerhouse?
Some refer to the idea of aggressive, pervasive adoption of AI as being “AI first.” Others use the term “AI fueled” or “all in on AI” (that’s Tom’s favorite, since it’s the title of his forthcoming book on the subject). Mastercard prefers “AI powerhouse.” Regardless of the descriptor, the concept refers to organizations that apply AI throughout their businesses, using it to either transform operations or develop new products, services, and business models, or both. These companies employ multiple AI technologies, develop many use cases, and put them all into production deployment.
As we’ve noted in previous columns, this level of engagement is unusual. In a 2019 MIT Sloan Management Review and Boston Consulting Group AI survey, 65% of respondents said they hadn’t seen value from their recent AI investments, in part because relatively few projects had been put into production. Survey respondents reported being skittish about the technology, with 45% saying they perceived some risk to their business from AI (up from 37% two years earlier).
To succeed in becoming an AI powerhouse, companies need to have a set of prerequisites in place. Senior leaders of the organization have to be on board and engaged with the effort because AI use cases must enable new ways of doing business and AI powerhouses inevitably invest at least a fair amount in AI. A lot of high-quality data is needed because that’s how machine learning models are trained. From a talent perspective, companies need smart individuals who can develop and apply AI systems. And it’s important that an organization have an ethical compass about how it uses AI and other information resources.
Continue reading: https://sloanreview.mit.edu/article/becoming-an-ai-powerhouse-means-going-all-in/
