A.I. has the potential to add $16 trillion globally to the GDP, but only has an adoption rate of about 4% so far.
In addition to the learning curve, there are plenty of steps that need to be taken before A.I. can even become usable in a business. A company would need to have the rights to accessible data, as well as infrastructure to access it reliably 24/7, Solmaz Shahalizadeh, vice president of data science and engineering at Shopify, said during a discussion at Fortune‘s Most Powerful Women International Summit in Montreal Tuesday.
Ellyn Shook, chief leadership and human resources officer at Accenture, notes that it’s easier than some think to train a workforce to utilize A.I. In fact, Accenture offered its employees a deal: If your work becomes automated, we’ll train you in something else. However, in some areas, employers are finding their problems are two-fold—workers aren’t interested in changing their skill set and their strengths are no longer as useful as they once were.
“We think that there’s really only two essential ingredients to be able to train people to use these technologies. The first is aspiration, and from our research we know that about two-thirds do have a high aspiration to use the technology. The second is learning agility. If you have those two things you can really invest in people to train them how to use the information and the data. Even if they’re people you wouldn’t normally think are digital native,” Shook said.
This could tie in with the lack of adoption by companies at large. And there’s worry that the problem won’t be solved any time soon as a shortage of A.I. educators is reported. Canada is investing in the effort, but it could be years before A.I. needs are met.
