Digital Today, Cognitive Tomorrow

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. It’s impossible to create protocols, algorithms, or software code to successfully anticipate all the potential permutations, trajectories, and interactions. But cognitive systems are not simply programmed. They actually improve with use, as they receive expert training, interact with clients and customers, and ingest data from their own experiences, successes, and failures.

Some people think of cognitive systems as supercomputers, and there is no question that the computational power behind systems like Watson is considerable. But thanks to the increasing prevalence of application program interfaces (APIs) — which can be encoded into digital services and easily accessed or combined in new ways in the cloud — it’s possible to build a kind of thinking into virtually every digital application, product, and system.

And because we can, we will. If it’s digital today, it will be cognitive tomorrow — and not a distant tomorrow. IDC Research Inc. has estimated that by 2018, more than half of the teams developing apps will embed some kind of cognitive services in them, up from 1% in 2015.

Cognitive systems are already transforming everything from the world-changing to the everyday. For example, cognitive oncology is a reality thanks to technology developed in partnership with Memorial Sloan Kettering Cancer Center in New York City that helps oncologists identify personalized, evidence-based treatment options based on massive volumes of data. This breakthrough technology is now helping scale access to knowledge at Bumrungrad International Hospital in Thailand, Manipal Hospitals in India, and more than 20 hospitals in China. Cognitive assistants are at work helping build more intimate, personalized relationships at the Brazilian bank Banco Bradesco, the insurance company GEICO, and the retailer The North Face. Dublin-based Medtronic plc, a global health care solutions company, is creating a cognitive app for people with diabetes to predict a hypoglycemic event hours in advance. These are just a few examples of organizations that are using cognitive systems today.

It’s important to note that we are not talking about the AI we see in movies. This isn’t about creating a synthetic brain or an artificial human. Rather, this is about augmenting human intelligence. Indeed, there is nothing in either cognitive science or its application that implies either sentience or autonomy.

Of course, anyone familiar with the history of technology knows that technological breakthroughs often have major effects on work and jobs. Some jobs are eliminated, while others are created. With cognitive systems, we are already beginning to see the emergence of new disciplines — from data curation to system training, as well as new fields of scientific knowledge and new kinds of work — quite possibly more than in any prior technology revolution.

Data can be seen as the world’s great new resource. What steam power, electricity, and fossil fuels did for earlier eras, data promises to do for the 21st century — if we can mine, refine, and apply it. Thanks to the new generation of cognitive technologies, we can. Intelligence augmentation — IA as opposed to AI — will change how humans work together, make decisions, and manage organizations.