When it comes to adoption of cognitive technology, some of the leading companies are progressing rapidly from the pilot project phase to the production application phase. Those in the sidelines would do well to move from interest to adoption of this impressive group of technologies.
While cognitive computing, often referred to as artificial intelligence (AI), is hardly new, the recent level of interest in it is astounding. The combination of vendor marketing, concerns about job losses, and even discussion of “robot overlords” have prompted massive interest in the media. There is also plenty of substance behind the hype. Cognitive technologies offer the possibility of increased productivity, better knowledge-based interactions with customers, and the ability to solve problems that are too complex for human brains.
While there have been several “AI winters” and “AI springs” over the past 50 years, there is reason to be confident that the flowering this AI spring is changing the garden permanently. However, in order to get value from this impressive set of technologies, organizations should move rapidly from interest to adoption. In many cases, the technology is ready for immediate use, and many large, established companies are moving ahead with production applications.
The current term for AI is “cognitive technology,” suggesting an ability to perceive and learn that approaches—and sometimes exceeds—that of humans. On both the vendor and user sides of information technology, cognitive is likely the most exciting technology of our time. It is on track to become the most influential technology since the rapid growth of the Internet around the turn of the last century.
There are still some obstacles to cognitive technologies assuming their place at the head of the technology table, but determined organizations can overcome them. It’s not clear when or if cognitive technologies will ever reach the level of “artificial general intelligence” at which they are better than humans at every kind of thinking we do (also known as “The Singularity”). But it is already having dramatic and, generally, beneficial impacts on businesses and organizations.
Why has this rapid growth in visibility and interest for cognitive technologies taken place, and what are the implications of it? There are both demand and supply factors underlying this trend. On the demand side, there are strategic, tactical, and operational aspects. From a strategic standpoint, companies always want profitable growth, and increased productivity is a common way to achieve it. But there hasn’t been much productivity improvement in advanced economies over the past several years (only 1.3 percent average annual growth from 2007 to 2015, and decreasing productivity in the first two quarters of 2016), and companies are anxious to learn whether cognitive technologies can finally spur productivity growth.
Also, on the demand side, there are many situations today in which a traditional human approach to analytics and decision-making is simply impossible. These decisions need to be made with too much data and in too short a time for humans to employ their own brains in the process. Digital advertising, medical diagnosis, predictive maintenance of industrial equipment, and many other realms of business today are impossible to execute well without some form of cognitive technologies.
Finally, in terms of the simple operational aspects of demand, while human labor has many strengths, it remains expensive (even when outsourced) and difficult to manage relative to machines. Of course, in many cases smart machines will work alongside smart humans, and that is the best combination in many work settings. But there’s no doubt that the siren call of automation is propelling cognitive technology forward.
On the supply side, we now have both software and hardware that is well suited to performing cognitive tasks.
