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In 2017, MITSloan Management Review (MIT SMR) conducted a global survey of more than 3,000 executives, managers, and analysts on the current state of AI and its potential. The results reveal that there’s still a significant gap between “ambition and execution.”
Three out of four executives believe that AI will allow their companies to move into new business ventures, while 85 percent feel AI will give them a competitive advantage. Yet less than 20 percent of respondents had actually incorporated AI into their processes and/or product offerings at the time of the survey. Just 39 percent of companies have an AI strategy in place, and those that do tend to be the largest (100,000 employees or more).
“Our research reveals large gaps between today’s leaders — companies that already understand and have adopted AI — and laggards. One sizeable difference is their approach to data,” MIT SMR explains, referring to the fact that AI algorithms aren’t intuitive and “intelligent.” In order to get the most out of AI, businesses have to collect, organize, and feed data so that the AI can grow and become useful.
“Our research surfaced several misunderstandings about the resources needed to train AI,” MIT SMR continues. “The leaders not only have a much deeper appreciation about what’s required to produce AI than laggards, they are also more likely to have senior leadership support and have developed a business case for AI initiatives.”
The good news is that we’re making significant progress. As recently as 2015, studies showed that 34 percent of the marketplace feared AI, with those in business services scoring above the average in terms of apprehension. When asked about AI in relation to business, very few companies said they were actually using AI, and only seven percent planned on implementing it within the next year. While one in four businesses were evaluating how to apply AI, 49 percent had no plans to use AI in the future.
When you look at the current state of AI in business, it’s clear we’ve come a long way in a relatively short amount of time. But the more light we shed on misconceptions, the more positive development we can expect to see in this area.
Of businesses that are executing on their AI ambitions, most are focused on a couple of established paths:
Streamline customer service
In an ultra-connected marketplace where customers expect to be able to communicate with businesses whenever, wherever, and however they wish, customer service is becoming a huge challenge. Just ask the National Health Services (NHS) in the U.K.
The NHS is currently testing an AI-powered chatbot on its non-emergency helpline. People can opt to interact with the chatbot, as opposed to talking to a person, and enter their symptoms into the app. The app then consults a large medical database and provides responses based on the information provided. The goal is to reduce the pressure of call volume during the winter months.
While many patients have criticized the NHS chatbot, it’s easy to see how a system like this could work in other industries. By streamlining customer service and automating the first point of contact, companies can devote more human resources to the most important issues and concerns.
Cybersecurity can sometimes steal the spotlight, but business owners also know how important physical security is. As IP camera technology advances, we’re seeing how AI can transform this area.
AI researchers have been developing algorithms to look at an image and determine what it depicts. In the world of security, this comes in the form of surveillance-based facial recognition.
As Quartz Media explains, the U.S. government already uses this technology. At one point last year, the New York department of motor vehicles had already made more than 4,000 arrests with the assistance of facial recognition, which allowed law enforcement to access driver’s license photos. As the technology improves and AI algorithms get more sophisticated, businesses could actually identify individual people in security footage in real time.
Industrial businesses may be gaining the most from AI at the moment. Just look at BP, which is augmenting human skills with AI in an effort to improve operations in the field.
“We have something called the BP well advisor,” BP’s Ahmed Hashmi tells MIT SMR, “that takes all of the data that’s coming off of the drilling systems and creates advice for the engineers to adjust their drilling parameters to remain in the optimum zone and alerts them to potential operational upsets and risks down the road.”
Hashmi says BP is also hard at work automating root-cause failure analysis, so the system trains itself over time and quickly moves from description to prediction to prescription.
AI in the years to come
This year marks a pivotal point in the timeline of business-side AI adoption. The early indicators are that businesses are finally recognizing the value of AI, consumers are getting over their fears, and leading businesses are leveraging advanced technology.
Expect significant evolution on this topic throughout the calendar year and don’t be surprised if the business world looks a little different come December 2018.
Larry Alton is a contributing writer at VentureBeat covering artificial intelligence.
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