For decades analysts have predicted the eventual development of artificial general intelligence (i.e., sentient machines). Nevertheless, that achievement continues to elude the scientific community. In the meantime, the world has discovered the usefulness of narrow artificial intelligence (i.e., AI designed to perform specific functions). A couple of years ago David Cearley, a Vice President and Gartner Fellow in Gartner Research, wrote, “Artificial Intelligence and machine learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing or application. Creating intelligent systems that learn, adapt and potentially act autonomously rather than simply execute predefined instructions is primarily battleground for technology vendors through at least 2020.”[1] Analysts from Gartner now insist artificial intelligence is approaching the peak of the hype cycle. Lynsey Barber (@lynseybarber) reports, “Deep learning and machine learning are at what [Gartner] calls the ‘peak of inflated expectation’, but are just two to five years away from mainstream adoption. Cognitive computing is also at peak hype, but up to 10 years away, while general artificial intelligence remains more than a decade away and is still at the stage of early innovation.”[2]

Artificial Intelligence and Business

As President and CEO of a cognitive computing firm, I’m a bit surprised Gartner analysts predict cognitive computing is a decade away from mainstream adoption. Many commercial fields are already using cognitive computing to advance their interests, improve their decision making, and make their processes more efficient. Part of the reason Gartner analysts may be pushing the mainstreaming of cognitive computing out a decade is the fact that some analysts believe IBM oversold the capabilities of its Watson offering following Watson’s impressive victory on Jeopardy! Jennings Brown (@tjenningsbrown) explains, “The splashy vision of Watson has been integral to IBM’s branding since the groundbreaking question-answering system made its debut in 2011 on Jeopardy! Now, thanks to billions of dollars of investment and years of aggressive marketing, Watson has come to represent AI in the popular imagination. Siri and Alexa may get more attention these days, but when it comes to big-data computing, Watson was the first to offer up its name, and it has remained a cocksure mascot.”[3] He adds, “To be fair, it is challenging to market AI and machine learning to a mainstream audience. It was especially challenging back when Watson was born in 2011 and AI was the stuff of sci-fi. That’s why IBM came up with their own description: ‘cognitive computing.’” According to Brown, here’s the rub, “As other companies have started investing heavily in AI in a time when it’s safer to do so, IBM has stayed on the same course, and Watson is trapped in the same black box.” With competition so keen, I predict you will see cognitive computing go mainstream in less than 10 years.

Although he didn’t put a timeline on his prediction, Kevin Kelly (@kevin2kelly), founding Executive Editor of Wired magazine, tweeted, “In the very near future you will cognify everything in your life that is already electrified.” Satya Nadella, CEO of Microsoft, also believes artificial intelligence is one of the most important technologies of the future. Alex Hickey reports “Nadella … outlined three technologies at the GeekWire summit … which he believes are paving his company’s path into the future: mixed reality, artificial intelligence and quantum computing. … He has been the key driver integrating AI throughout Microsoft’s products and services, and hopes these efforts will keep Microsoft on the forefront of computing.”[4]

Even though implementing AI is essential in the digital transformation process, Boris Evelson (@bevelson), Vice President & Principal Analyst at Forrester Research, and Michele Goetz (@Mgoetz_FORR), an enterprise data expert at Forrester, insist the going could be rough. They explain, “Forrester predicts that 2018 will be the year when a majority of enterprises start dealing with the hard facts: AI and all other new technologies like big data and cloud computing still require hard work.”[5] They suggest four ways “AI will shape enterprises in 2018”:

• AI will reshape analytic and business innovation: A quarter of firms will supplement point-and-click analytics with conversational user interfaces, and AI will make decisions and provide real-time instructions at 20% of firms.
• Big Data environments will evolve or suffer the same fate as yesterday’s data management: One-third of enterprises will take their data lakes off life support in 2018, and half of firms will adopt a cloud-first strategy for big data analytics.
• Firms will remake traditional data and analytic roles to activate insights: Two-thirds of firms will create customer insight centers of excellence, and data engineers will become the new hot job title in 2018.
• The insights market landscape will become as complex as three-dimensional chess: The IaaS (Insights-as-a-Service) market will double, with 80% of firms relying on insights service providers for some portion of insights capabilities in 2018.

Artificial Intelligence and Jobs

One of the ongoing concerns about the emergence of AI is the number of human jobs it will eliminate. David Weldon (@DWeldon646) reports Gartner is optimistic this won’t happen. He writes, “In 2020, AI will become a positive net job motivator, creating 2.3 million jobs while eliminating only 1.8 million jobs. ‘AI will eliminate more jobs than it creates through 2019, however, Gartner believes that the number of jobs created due to AI in 2020 is sufficient to overcome the deficit,’ the research firm says. ‘Net job creation or elimination will vary greatly by industry; some industries will experience overall job loss, some industries will experience net job loss for only a few years; and some industries, such as healthcare and education, will never experience net job loss. AI will improve the productivity of many jobs, and, used creatively, it has the potential to enrich people’s careers, reimagine old tasks and create new industries.’”[6]

Lee Rainie (@lrainie), Director of Internet and Technology research at Pew Research Center, isn’t quite as sanguine. “There is no consensus,” he writes, “about whether the forces unleashed by technology destroy more jobs than they create or whether the historic pattern of human upskilling prevails as new, more valuable jobs replace those supplanted by technology. The next advancements in machines are clear, but the human response is not. How the ecosystem of education and skills training will adapt is extremely relevant.” Jobs sustainability will be a growing topic of interest in the years ahead.

Summary

There seems to be a consensus that artificial intelligence will continue to touch more corners of our lives whether we are at work, at home, or at play. How quickly they will mainstream and how pervasive they will be remain open questions. For more AI predictions, see “51 Artificial Intelligence (AI) Predictions for 2018” by Gil Press (@GilPress).

Footnotes
[1] David Cearley, “Gartner’s Top 10 Strategic Technology Trends For 2017,” Forbes, 26 October 2016.
[2] Lynsey Barber, “Gartner Hype Cycle 2017: Artificial intelligence at peak hype, blockchain heads for disillusionment, but say hello to 5G,” City A.M., 17 August 2017.
[3] Jennings Brown, “Why Everyone Is Hating on IBM Watson—Including the People Who Helped Make It,” Gizmodo, 10 August 2017.
[4] Alex Hickey, “3 technologies Microsoft’s CEO says are the future,” CIO Dive, 12 October 2017.
[5] Boris Evelson and Michele Goetz, “Predictions 2018: AI is tough stuff and many organizations will fail at it,” Information Management, 20 November 2017.
[6] David Weldon, “Top 10 predictions for IT in 2018 and beyond,” Information Management, 10 October 2017.
[7] Lee Rainie, “Life in 2030: 4 Things Experts Can’t Predict,” Longitudes, 21 November 2017.