AI is having an impact in business, government and healthcare. But nowhere is it having more impact than for the biggest companies with the most resources. Advantages big companies have include access to lots of data and funds to buy smaller companies with the expertise to do something innovative and profitable with the data. Each company has had to decide on the best way to leverage AI for their business. "The question is how do you use AI right or use it wisely," stated Ed McLaughlin, Chief Emerging Payments Officer for Mastercard, at the recent EmTech Digital event on AI and big data, as reported in MIT Sloan Review.

As artificial intelligence continues to move into the mainstream, companies are combining AI and big data to build and design better products, react faster to changing market conditions, and protect consumers from fraud. According to experts at EmTech Digital, MIT Technology Review's annual event on artificial intelligence, big data plus AI creates a foundation for more intelligent products and services -- ones that initiate maintenance procedures before something breaks, perform more precise operations, or automatically recalibrate resources to meet changing demand and usage patterns. While AI and big data pave the way for such evolutionary use cases, the pair do not constitute a business strategy on their own accord. "The question is how do you use AI right or use it wisely," said panelist Ed McLaughlin, president of operations and technology for Mastercard. "The biggest lesson learned is how to take these powerful tools and start backward from the problem," McLaughlin said.

As artificial intelligence continues to move into the mainstream, companies are combining AI and big data to build and design better products, react faster to changing market conditions, and protect consumers from fraud. According to experts at EmTech Digital, MIT Technology Review's annual event on artificial intelligence, big data plus AI creates a foundation for more intelligent products and services -- ones that initiate maintenance procedures before something breaks, perform more precise operations, or automatically recalibrate resources to meet changing demand and usage patterns. While AI and big data pave the way for such evolutionary use cases, the pair do not constitute a business strategy on their own accord. "The question is how do you use AI right or use it wisely," said panelist Ed McLaughlin, president of operations and technology for Mastercard. "The biggest lesson learned is how to take these powerful tools and start backwards from the problem," McLaughlin said.

Consider, for example, automated driving systems. Although autonomous vehicles promise to significantly improve mobility, engineers must test these frameworks for critical factors such as safety and potential system failures. Toyota is one of the automakers working to make driverless systems safe. In 2016, Toyota president and CEO Akio Toyoda said more testing would be needed to complete its mission--some 8.8 billion miles of it. Fortunately, says Stefan Jockusch, vice president of strategy at Siemens Digital Industries Software, simulation can help.

Stefan Jockusch is not one of them. Vice president of strategy at Siemens Digital Industries Software, Jockusch says trusting an algorithm that powers an AI application is a matter of statistics. This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not produced by MIT Technology Review's editorial staff. "If it works right, and if you have enough compute power, then the AI application will give you the right answer in an overwhelming percentage of cases," says Jockusch, whose business is building "digital twin" software of physical products. He gives the example of Apple's iPhones and its facial recognition software--technology that has been tested "millions and millions of times" and produced just a few failures. "That's where the trust comes from," says Jockusch. In this episode of Business Lab, Jockusch discusses how AI can be used in manufacturing to build better products: by doing the tedious work engineers have traditionally done themselves.

Ask Stefan Jockusch what a factory might look like in 10 or 20 years, and the answer might leave you at a crossroads between fascination and bewilderment. Jockusch is vice president for strategy at Siemens Digital Industries Software, which develops applications that simulate the conception, design, and manufacture of products like cell phones or smart watches. His vision of a smart factory is abuzz with "independent, moving" robots. This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not produced by MIT Technology Review's editorial staff. "Depending on what product I throw at this factory, it will completely reshuffle itself and work differently when I come in with a very different product," Jockusch says. "It will self-organize itself to do something different." Behind this factory of the future is artificial intelligence (AI), Jockusch says in this episode of Business Lab. But AI starts much, much smaller, with the chip.

Ask Stefan Jockusch what a factory might look like in 10 or 20 years, and the answer might leave you at a crossroads between fascination and bewilderment. Jockusch is vice president for strategy at Siemens Digital Industries Software, which develops applications that simulate the conception, design, and manufacture of products like cell phones or smart watches. His vision of a smart factory is abuzz with "independent, moving" robots. This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not produced by MIT Technology Review's editorial staff. "Depending on what product I throw at this factory, it will completely reshuffle itself and work differently when I come in with a very different product," Jockusch says. "It will self-organize itself to do something different." Behind this factory of future is artificial intelligence (AI), Jockusch says in this episode of Business Lab. But AI starts much, much smaller, with the chip.