Expectations of AI are ‘sky-high’ but the reality doesn’t match

ARTIFICIAL intelligence is being used across almost every industry, from finance and healthcare to retail to travel. Yet many companies lack an understanding of how to fully utilize AI technology to grow revenue and create exceptional customer experience.

Expectations of how AI can improve business performance are “sky-high” according to a report released by MIT Sloan Management Review and The Boston Consulting Group. The survey polled 3,000 business executives, managers and analysts in 112 countries and 21 industries, with results finding 84 percent believe AI will allow their companies to gain or sustain a competitive advantage.

However, 36 percent of those polled admitted to having very little understanding of AI at all. The survey also revealed that fewer than 39 percent of all companies who intend to use AI to enhance business growth have an AI strategy in place.

The first thing AI adopters need to grasp is that the quality of data being put into the AI systems will determine the outcome. This can ultimately reduce the gap between expectation and conviction, as the better the data, the more thoroughly AI can be utilized in an enterprise.

“Businesses now have the data, they have the computing power and the algorithms are mature to the point that it doesn’t take a rocket scientist to understand what the algorithm is doing,” Kirk Borne, principal data scientist and executive advisor at global technology services firm Booz Allen Hamilton told Tech Wire Asia.

Not understanding AI can massively impact your business

The lack of understanding in how to fully utilize AI could see unattended algorithms go rogue, not in the sense of robots turning evil, but instead making actions which are harmful to business strategy.

One of these harmful actions came to light in the 2014 Sydney hostage crisis, when an algorithm used by ride-sharing app Uber learned the basics of supply and demand, and applied a minimum $100 charge to those trying to get out of the immediate vicinity of the crisis.

Exploiting those in need is a sure way to loosen customer retention and affect brand reputation. The cognitive awareness of AI is not yet advanced enough to be used in industry. However, using AI alongside the watchful eye of human employees can ensure infantile hiccups like these are learned from and not repeated.

As companies become au fait with AI, though, more advanced systems can be used – and eventually this type of AI will be able to learn from its own mistakes. “We get good judgment from experience, we get experience from bad judgment, so when we make mistakes as humans, we learn from those things and do better next time. So if a machine replicates what humans do then it will learn too,” said Borne. “The human in the loop of machine learning can provide that judgment, so the next time, the machine can have good judgment.”

Often organizations assume AI technology will work independently to improve business. However, humans using AI systems must be able to detect patterns in algorithms and adapt to work with or eliminate them.

Allowing humans to work with AI can result in astonishing customer experiences. “An employee of the airline (Transavia) recognized, through a simple algorithm, that this one very frequent passenger was traveling with her young daughter on a flight, and it was her birthday, so they arranged to have a little birthday cake given to her. Everyone sang happy birthday and their Twitter just lit up with all positive comments,” Borne said.

Closing the gap between expectation and reality

The demand for AI technology is high across all industries, but the adoption is still in its infancy. With AI comes a lot of caution – and rightfully so. The economic risks are high, and dangers of algorithms destroying a brand reputation are also a concern.

Ensuring the data input to the machine is not fragmented or weak is essential to seeing positive results from AI. Also, if AI adopters can gain an understanding of the technology behind machine learning, enterprises can better develop business strategies.

“I think a basic understanding that, through the use of analytics and by leveraging data, we do have techniques that will produce better and more accurate results and decisions than gut instinct is important,” J D Elliott, director of enterprise data management at TIAA, told MIT Sloan.

For years, AI was an ominous phrase, lurking in the laboratories of data scientists and in the minds of futurist action movie fans. It is now advancing and its adoption is one way to add value to any business. However, the disparities between ambition and execution have to be eliminated in order for every enterprise to run exceptionally well, and deliver birthday cake to each of their valued and unsuspecting customers.

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