Get data literate

To get there, however, every company urgently needs a management and workforce with a good understanding of machine learning, as well as the skills needed to implement AI-based solutions. And savvy CEOs know that it is essential to get these employees in place now, so that they are ahead of the game when the AI revolution starts growing exponentially.

Data literacy remains the top barrier to successfully implementing AI, followed closely by a lack of AI and data science expertise among employees. However, retraining a workforce and hiring new data literate employees will represent a major outgoing for most companies. This is a sensible expense for major tech brands and listed companies, but what about smaller start-ups?

“Partnering AI with high-performing individuals is the best recipe for success for any company no matter what their size,” says Tom Davenport, an American academic and author specialising in analytics, business process innovation and knowledge management. “Artificial intelligence is one of the most powerful technologies for reshaping business in decades. In my view AI will become a permanent aspect of the business landscape.” 

The implication being that companies that are too small to upgrade to wide-reaching AI-based systems will be at a major disadvantage, which means finding the money and training time to incorporate machine learning into current practices may soon become a non-negotiable.

“No business can avoid the AI reality,” says Davenport, “Remember those diehards who swore they weren't going to use the Internet? Now they're running ads on Google or Facebook. To run a business, you need information and insight. The Internet gives you information but not insight. AI gives you both.”

If companies accept that they need people who can coordinate, integrate, and put the right datasets and solutions in place, does this come from training or new hires? Studies have shown that both technical and non-technical employees want to learn and develop in these areas. How easy are these skills to learn?

Invest in employee training

“At Fave, we believe AI and machine learning is going to disrupt the way consumers transact and merchants operate,” says Joel Neoh, the CEO and founder of Malaysian-based discount site Fave. “With the advancement in algorithms and processing power, building AI systems is becoming more convenient and easier to run. AI relies heavily on good data, so our plan is to revamp the whole data infrastructure that can handle AI complexities. As AI grows, it is going to be difficult to attract AI talents. But when the need arises, we have decided to provide existing employees with the support, training and tools they need to work alongside AI rather than employ from outside.”

As Neoh illustrates, knowing the business challenges you want AI to solve will be essential when designing a future tech team. Because every company will have very different needs from AI employees, much like they currently do with non-tech staff. Ask yourself: can the problem be fixed by someone with any level of experience in machine learning, or is it so complex that it can only be handled by someone with years of experience in the field?

For Steven Kim, the CEO of Indonesia-based food app Qraved, AI is currently a secondary focus. “We are implementing AI into various parts in the organisation, including image recognition and recommendations based on context and personal preference, but we see that AI in the near future will be an upgrade from automation but not a breakthrough when it comes to influence or content,” says Kim. “The human touch is important, and AI is a more supporting role so that our workforce can focus more on the creative aspects.”

Advances in AI promise social and economic change on a par only with the industrial revolution of the 19th and 20th centuries. But what differentiates our era is that the transformation of humanity’s approach to labour will be squeezed into a single generation, rather than spread out over several decades. Right now, we are teetering on the edge of rapid global change—and the best way to be prepared is with the brightest people on board, while looking the future square in the eye.