Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. I am a proud late adopter of new technology. I had a StarTAC well into the 21st century, fearing the limitless access to digital information and services that smartphones would bring and the way they would rob us of our time and attention and humanity. Though this realization offers little solace as I stare into my phone hundreds of hours a day.) I traveled with my books of CDs and my Discman well into the era when Transportation Security Administration agents would look at them with curiosity and suspicion.

With research suggesting artificial intelligence in manufacturing could become mainstream within 24 months, what can manufacturers gain from taking an early adopter approach? With AI and advanced analytics to identify patterns and trends in the wealth of data generated by the IoT, the barriers between operational technology and information technology are breaking down. Manufacturers can become data-driven in all aspects of business, enabling the companies to transform operations, restructure supply chains, improve efficiency, address skills shortages and create entirely new revenue streams and business models. Despite the many benefits, the Manufacturing Leadership Council's'Factories of the Future' survey revealed that less than one in 10 (8%) of manufacturers are currently using AI – though a further 50% expect to deploy it within two years. AI is still nascent in manufacturing today, yet these results suggest it could become mainstream in under 24 months.

Instead they are waiting for the technology to mature and for expertise in AI to become more widely available. They are planning to be "fast followers" -- a strategy that has worked with most information technologies. We think this is a bad idea. It's true that some technologies need further development, but some (like traditional machine learning) are quite mature and have been available in some form for decades. Even more recent technologies like deep learning are based on research that took place in the 1980s.

Early adopters of AI will share a global profit pool valued at $1 trillion. Will your company be among them? From the dexterity of Amazon's Kiva robots to the facial recognition in Apple's iPhone X, artificial intelligence is increasingly sophisticated and accessible. It also promises to be a rich source of profit uplift -- up to 10% of revenue, depending on your industry. Nevertheless, more than 95% of companies have not embraced AI technology to reinvent how they do business.1 Even though there are many unknowns regarding AI's capabilities and uses, our research at the McKinsey Global Institute suggests that following a wait-and-see strategy for too much longer could be a costly mistake.

Opportunity and crisis: A report from McKinsey has warned that late adopters of AI might be left playing catch-up indefinitely. A professor who is shorty set to take over as the President of the British Science Association has said that AI is the biggest issue of our time, and that he is concerned we are not discussing it enough. According to a report by McKinsey, by 2030, around 70% of companies will have adopted one category of AI. But, says McKinsey, less than half will have adopted what it has described as the five categories of AI, by that date. The report also predicted that AI could be worth $13 trillion to the global economy between now and 2030.

Early adopters of AI will share a global profit pool valued at $1 trillion. Will your company be among them? From the dexterity of Amazon's Kiva robots to the facial recognition in Apple's iPhone X, artificial intelligence is increasingly sophisticated and accessible. It also promises to be a rich source of profit uplift -- up to 10% of revenue, depending on your industry. Nevertheless, more than 95% of companies have not embraced AI technology to reinvent how they do business.1

Smart machines and artificial intelligence (AI) are taking off in a big way. Our relationships to technology continue to evolve. Soon machines will be able to learn and adapt to their environments. AI has long been considered the realm of science fiction, but as technology improves, AI becomes a reality. While advanced learning machines may replace low-skill jobs, AIs will be able to work collaboratively with human professionals to solve intensely complex problems.

This past week Uber announced the acquisition of an Artificial Intelligence company called Geometric Intelligence. With this acquisition Uber will officially be creating Uber AI Labs, a think tank within Uber that will be looking at all of the utilizations for Artificial Intelligence within the organization. Over the past few months, Uber has discussed its desire to be able to roll out an autonomous vehicle fleet. To accomplish this task, Uber is going to have to build a level of AI that can handle many unique situations. The Geometric Intelligence team is working on the types of deep learning and AI that could potentially help Uber to accomplish this in a shorter period of time.