Cognitive computing can be defined as a set of augmented intelligence abilities such as machine learning, reasoning and decision technology, language, speech and vision, human-interface tech, distributed and high-performance computing and the latest computing infrastructures and devices. When blended, the capabilities of these systems are intended to solve practical problems and harbor new discoveries.

To better understand the marketplace along with the opportunities created and the challenges faced by cognitive computing, it is important to consider the insights gained by early adopters. These organizations are already deriving business value from cognitive computing and are an excellent marker to promote others to do the same for their businesses.

A recent study by one of the biggest tech developers in the world, conducted into cognitive computing found that advanced users that are using two or more cognitive technologies for over a year, made up 22% of total respondents. Beginners, using the technology for under a year or simply using one technology for more than a year formed the majority at 54%. While planners, those that want to implement cognitive technology in their business within the next two years formed the remaining 24%.

Typically, cognitive technology is excellent in scenarios where there is just too much data for humans to handle and sort, or where carrying out automated and quick decisions on a vast amount of data is critical for the business, and where there are well-defined rules in processes. Machine learning, for example, is being leveraged to identify and handle fraud in a more proactive manner, reduce customer churn or boost sales using personalization. Cognitive technology is vital to IoT networks as well and can be applied in manufacturing optimization and predictive maintenance as well. It is also being experimented with in formulating medical diagnostics. 

Every business wants to highlight its key differentiators, and early adopters of the technology claim that their customers are already responding strongly. More than half claim that cognitive abilities are a ‘must have’ in order to remain competitive within the next couple of years.

A large number of businesses are leveraging cognitive computing due to developer and business experimentation, not just C-suite mandates. Additionally, almost half of respondents claim that their competitors adopting cognitive technology have spurred their own investments.

Although cognitive technology can create dreams of executing big ideas on a large scale, it comes with its share of challenges such as high cost and difficulties in implementing its infrastructure. Difficulties in the technology’s adoption strategy have slowed down just over 40% of respondents and many early adopters find themselves struggling to manage their data.

But the most difficult hurdle to overcome is the skill gap. With 63% of respondents needing more computer scientists and experts in machine learning, natural language processing etc. Software developers are required as well to help develop the system that enables employees to engage with the technology.

That being said, there is a lot more ground that needs to be covered before most companies will be able to position themselves to take advantage of these technologies and the myriad benefits they offer. Between locating the people with the correct amount of expertise and the correct platform to launch it on as well as paying for the whole thing, cognitive computing can be the differentiating factor for future-thinking companies.

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