Digital Today, Cognitive Tomorrow

Digital is not the destination. Rather, it is laying the foundation for a more profound transformation to come.

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An MIT SMR initiative exploring how technology is reshaping the practice of management.
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Editor’s Note: This article is one of a special series of 14 commissioned essays MIT Sloan Management Review is publishing to celebrate the launch of our new Frontiers initiative. Each essay gives the author’s response to this question:

“Within the next five years, how will technology change the practice of management in a way we have not yet witnessed?”

In today’s economy, we are seeing companies, business models, products, and processes undergoing major transformation. Enterprises and governments are rapidly “becoming digital” as they seek to capture the cost savings, agility, and collaboration enabled by cloud, analytics, mobile, and social technologies.

However, digital is not the destination. Rather, it is laying the foundation for a much more profound transformation to come. Within five years, I believe all major business decisions will be enhanced by cognitive technologies.

I sensed the magnitude of the transition for the first time in 2011, when I watched IBM’s Watson system win on “Jeopardy!” At the time, I felt that I was watching history in the making: The technology known as artificial intelligence (AI) was finally moving from the lab into the world.

Why are we seeing this now?

First, the technologies required for cognitive systems — not just AI, but a broad spectrum of capabilities that include natural language processing, human-computer interaction, deep learning, neural nets, and more — have made exponential advances in recent years.

Second, the abundance of data being generated throughout the world today requires cognitive technology. Much of this data is “unstructured”: video, audio, sensor outputs, and everything we encode in language, from medical journals to tweets. However, such unstructured data are “dark” to traditional computer systems. Computers can capture, move, and store the data, but they cannot understand what the data mean (which is why cognitive systems are so vital).

Finally, and most important, we will see systems that learn. We need systems that learn. Think of the challenges and issues we face today: predicting risk in financial markets, anticipating consumer behavior, ensuring public safety, managing traffic, optimizing global supply chains, personalizing medicine, treating chronic diseases, and preventing pandemics.

The challenges today go beyond information overload. In many ways, we live in an era of cognitive overload, characterized by an exponential increase in the complexity of decision making.



An MIT SMR initiative exploring how technology is reshaping the practice of management.
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Comments (2)
Phani Sekhar
Nice Article,

Really very informative.Hope we should have a stage from Today digital,Tommorow Cognitive and after Cognitive with solution provider for the end customers should be at highly helpful for the customers.

For example : I have a one month sweet daughter.I have gone for shopping and the sales person has suggested for Digitized thermometer where we can access the temparature of  my one month daughter.We should have a solution at the same time in the digitized machine for the fever  along with the identification of temparature where we can avoid the doctor in certain circumstances.

Hope we should have the cognitive services to the end customers either in Healthcare,Education,Banking etc where ever it is applicable.
Manu Sharma
Customers demand for NEW (services, products and consumption models) is putting pressure on businesses to innovate. Innovation is best delivered when idea generation and development is crowd sourced, which is being enabled by seamless data integration collected from various sources. API integration solutions creating which connects island solutions is the backbone of an effective analytics solutions.

Agree with the points Ginni has made in the above article...innovation avalanche is coming soon and high end data solutions will drive its speed and accuracy