IDC today released research that predicts that cognitive and artificial intelligence will generate $12.5 billion in revenue this year, an increase of 59.3 percent over 2016. Indeed, the growth shows no sign of slowing. The compound annual growth rate (CAGR) will be 54.4 percent through 2020, with revenue exceeding $46 billion.
A particularly interesting conclusion is that 51.1 percent of investment, based on this year’s market share, will made in the “other” category. All the identified use cases are clustered between 9 percent (fraud analysis and investigation) and 10.3 percent (quality management investigation). This seems promising. IDC is willing to say that growth will be strong despite the fact that it can’t definitively say from where more than half of that growth will come.
The other interesting element is the use of the word “cognitive” alongside artificial:
From a technology perspective, the largest area of spending in 2017 ($4.5 billion) will be cognitive applications, which includes cognitively-enabled process and industry applications that automatically learn, discover, and make recommendations or predictions. Cognitive/AI software platforms, which provide the tools and technologies to analyze, organize, access, and provide advisory services based on a range of structured and unstructured information, will see investments of nearly $2.5 billion this year.
That paragraph begs the question of what the difference is between AI and cognitive intelligence. It also implies that the broad category of using machines to “think” is comprised of many smaller technologies. It is important for those who will potentially use AI and related techniques to understand the differences. The terms include machine learning, deep learning, text mining, speech recognition, neural networks, cognitive technology and others, according to Analytics India.
The difference between AI and cognitive intelligence is a bit hard to understand. AI is the umbrella term for all technologies used to enable machines to do things “that normally require human intelligence,” the story says. Cognitive technologies provide the information, but allow the human to make the ultimate decision. The differentiation seems more in how technology is leveraged than a difference in the tools themselves:
[C]ognitive computing helps us make smarter decisions on our own leveraging the machines, while AI is rooted in the idea that machines can take better decisions on our behalf.
The Harvard Business Review takes a different approach. The writers suggest that cognitive the field “comprises a range of approaches in artificial intelligence (AI), machine learning, and deep learning.” In other words, the higher level classification is cognitive computing, with AI, machine learning and all the rest fitting underneath.
It is obviously complicated material. It is also in its infancy, with much work to be done in order to enable the IDC predictions to be fulfilled. Last week, IBM announced that it is opening its third IoT & AI Insiders Lab. A facility in Munich will join labs in Shenzhen, China and Redmond, Washington. The new facility will be a workshop and conduit between Internet of Things (IoT) and AI developers, entrepreneurs and companies in Europe and the Middle East, according to eWeek.
It’s not necessary for planners to deeply follow how the various pieces of the AI puzzle fit together. It is, however, important for them to understand that the field is not monolithic. A great deal of research and study is necessary before seriously talking to vendors, consultants, and others in the ecosystem.
Carl Weinschenk covers telecom for IT Business Edge. He writes about wireless technology, disaster recovery/business continuity, cellular services, the Internet of Things, machine-to-machine communications and other emerging technologies and platforms. He also covers net neutrality and related regulatory issues. Weinschenk has written about the phone companies, cable operators and related companies for decades and is senior editor of Broadband Technology Report. He can be reached at email@example.com and via twitter at @DailyMusicBrk.