Headlines are abuzz with the fact artificial intelligence (AI) is playing an ever-larger role in our daily lives. Princeton’s Kevin McElwee observes, “Artificial intelligence is already a part of everyday life. It helps us answer questions like ‘Is this email spam?’ It identifies friends in online photographs, selects news stories based on our politics and helps us deposit checks via our phones — if all somewhat imperfectly. But these applications are just the beginning. Through advances in computer science, researchers are creating new capabilities that have the potential to improve our lives in ways we have yet to imagine.”[1] Despite that kind of hype, Bob Violino (@BobViolino) reports, “Artificial intelligence … adoption is lagging even among key decision-makers championing change.”[2] At least, that’s the conclusion of a survey conducted by the RELX Group. Drawing from the survey, Violino writes, “While the value of the technologies is clear to executives, only 56 percent of organizations use machine learning or AI. In addition, only 18 percent of those surveyed plan to increase investment in these technologies.”
Unquestionable benefits of AI
Kumsal Bayazit, chairman of RELX Group’s Technology Forum, notes, “Organizations [that] can successfully use emerging technologies such as AI and machine learning to provide their customers with better products and advanced analytics can emerge as the leaders of the future.” What benefits are AI solutions providing companies? Violino reports, “69 percent of those surveyed say the technologies have had a positive impact on their industry. Machine learning and AI are helping solve challenges by automating decision processes (cited by 40 percent); improving customer retention (36 percent); and detecting fraud, waste and abuse (33 percent).” Nevertheless, Bayazit adds, “While awareness of these technologies and their benefits is higher than ever before, endorsement from key decision makers has not been enough to spark matching levels of adoption.”
What’s holding decision-makers back? According to Henrik Christensen (@hiskov), a computer science professor at UC San Diego, it’s fear of the unknown. He explains, “For some, investing in artificial intelligence feels like banking on the unknown. The concepts behind AI can range from sounding futuristic to downright fictional.”[3] He asserts decision-makers must get over their fears or they will miss out on exciting opportunities. “When you break down AI and explore the core technologies that drive it,” he writes, “look at what they are delivering today, and then consider what they are capable of delivering tomorrow, it’s suddenly quite easy to grasp how AI is changing the world around us. It is these facts that make investing in AI a not-to-be-missed investment opportunity.”
Ignore the hype and concentrate on the reality
John Leonard (@_JohnLeonard), a Research Director at Computing, believes too many decision-makers get distracted by the technology when they should be concentrating on what the technology can achieve. He writes, “A more practical viewpoint is to consider how machines that adapt their behavior might be useful. What do we want to use AI for? What information do we want it to give us and how do we want to act on it? What are we using our data for currently?”[4] Former IBM executive Irving Wladawsky-Berger reports the reality is that AI is going to add trillions of dollars worth of value to global economy over the next dozen years. He explains “Artificial intelligence has the potential to incrementally add 16 percent or around $13 trillion by 2030 to current global economic output — an annual average contribution to productivity growth of about 1.2 percent between now and 2030, according to a September 2018 report by the McKinsey Global Institute on the impact of AI on the world economy.”[5] He continues, “Taken together with a recent report by PwC, which found that AI technologies and applications will increase global GDP by up to 14% between now and 2030, the McKinsey report offers more evidence that AI is poised to deliver big economic opportunities for those companies and workers best positioned.”
According to Leonard, areas organizations are most interested in implementing AI solutions include: Business intelligence and analytics; process automation; customer experience; customer service; and cyber security. He explains:
“The main driver [of AI implementation] is making existing processes better and more efficient — exactly as you’d expect with any new technology. At the top we have business intelligence and analytics. Potentially AI can help businesses move from descriptive through predictive and ultimately prescriptive analytics, where machines take actions without first consulting their human masters. Then there are the various types of process automation. Typically this means handing over repetitive on-screen tasks to so-called soft bots that are able to quickly learn what is required of them. Much of the focus of that activity is on the customer, providing better customer experience — by learning what they like and giving them more of it — and better customer service, by improving the responsiveness of the organization using chat bots for example. Then there’s cyber security. Machine learning systems can be trained in what is normal and to recognize abnormal behavior on the network and either alert those in charge or, increasingly, act on the causes of the anomaly themselves.”
Many of the things organizations want to accomplish using AI will be achieved by leveraging cognitive computing capabilities. Christensen notes, “Today, cognitive computing is used to accelerate processes such as reasoning, natural language processing, speech recognition, object recognition, and dialog generation. According to research firm IDC, worldwide spending on cognitive and AI systems is expected to increase by more than 50% by 2021, taking total spending on cognitive computing from $12B in 2017 to $57.6B by 2021.”
Concluding thoughts
Although some people continue to view AI with wide-eyed wonder, clear-visioned leaders see only opportunities. Wladawsky-Berger concludes, “Over time, AI likely will become … a historical transformative technology. But other than a relatively small number of leading-edge firms, we’re still in the early stages of AI’s deployment. It’s only been in the last few years that complementary innovations like machine learning have taken AI from the lab to early adopters in the marketplace. Considerable innovations and investments are required for its wider deployment in robotics, self-driving cars, truly intelligent personal assistants, and advanced applications like smart health care.” Visionary leaders ignore hype and see real possibilities. Even though AI implementation remains in its early stages, laggards will find they don’t have much time to get started before they are left behind. Christensen concludes, “[Artificial intelligence is a] not-to-be-missed investment opportunity for decades to come.”
Footnotes
[1] Kevin McElwee, “From Math to Meaning. Artificial intelligence blends algorithms and applications,” Discovery, 2 December 2018.
[2] Bob Violino, “Artificial intelligence enthusiasm outpacing adoption, study finds,” Information Management, 26 December 2018.
[3] Henrik Christensen, “Why invest in AI? Core technologies hold the answer,” Robo Global, 20 November 2018.
[4] John Leonard, “Artificial Intelligence: The Potential And The Reality,” Computing, 19 November 2018.
[5] Irving Wladawsky-Berger, “The Impact of Artificial Intelligence on the World Economy,” The Wall Street Journal, 16 November 2018.
