Keystone logo

Why Business Students Should Care About Deep Learning

Deep learning has near-endless applications in the business world, but fully realizing its potential relies on finding the right humans to lead the way. Here’s a closer look at deep learning, along with why all business students should know about this amazing form of artificial intelligence.

Feb 18, 2019
  • Education
  • International News
Why Business Students Should Care About Deep Learning

Machines can do many exciting and surprising things. However, they have also been inherently limited when it came to the ability to think -- and learn -- for themselves. Until now, that is. With deep learning, a groundbreaking machine learning technique, computers have gained the ability to mimic the complex neural structure of the human brain in order to solve abstract problems on their own -- even without all of the directly relevant information. This technology has near-endless applications, including in the business world. Here’s a closer look at deep learning, along with why all business students should know about this amazing AI.

The 411 on Deep Learning

“The term ‘deep learning’ refers to the use of artificial neural networks to carry out a form of advanced pattern recognition. Algorithms are trained on large amounts of data, then applied to fresh data that is to be analyzed,” explains the Financial Times.

Consider the following example: If you showed a five-year-old child a short sequence of handwritten digits, she would immediately recognize those digits and be able to make sense of them. While this may seem effortless, its simplicity is deceptive: there are many things happening in her brain to support the translation of these numbers on a page into something meaningful.

“We carry in our heads a supercomputer, tuned by evolution over hundreds of millions of years, and superbly adapted to understand the visual world. Recognizing handwritten digits isn't easy. Rather, we humans are stupendously, astoundingly good at making sense of what our eyes show us. But nearly all that work is done unconsciously. And so we don't usually appreciate how tough a problem our visual systems solve,” asserts Michael A. Nielsen in the book, Neural Networks and Deep Learning.

For computers, however, this task is much harder. For example, Nielsen adds, “Simple intuitions about how we recognize shapes - ‘a 9 has a loop at the top, and a vertical stroke in the bottom right’ - turn out to be not so simple to express algorithmically. When you try to make such rules precise, you quickly get lost in a morass of exceptions and caveats and special cases. It seems hopeless.”

Enter neural networking. This approach uses a large number of handwritten digits, or 'training examples', to 'teach' computers to infer rules which allow them to more accurately recognize handwritten digits. As the number of training examples increases, so does accuracy. The result? Commercial neural networks that replicate how the human brain works in order to do everything from help post offices recognize addresses to helping banks process checks.

Forbes says of the capabilities of deep learning as compared to machine learning, “In machine learning, algorithms created by human programmers are responsible for parsing and learning from the data. They make decisions based on what they learn from the data. Deep learning learns through an artificial neural network that acts very much like a human brain and allows the machine to analyze data in a structure very much as humans do.”

The Benefits to Business

The potential applications of deep learning in a MBA are profound. A 2008 McKinsey Global Institute paper, 'Notes from the AI Frontier: Modeling the Impact of AI on the World Economy', explains, “The research found that three deep learning techniques -- feed forward neural networks, recurrent neural networks, and convolutional neural networks -- together could enable the creation of between $3.5 trillion and $5.8 trillion in value each year in nine business functions in 19 countries. This is the equivalent of 1 to 9 percent of 2016 sector revenue.”

Looking to more specifically visualize the potential of deep learning in practice? Forbes recently highlighted ten ways it is positioned to transform the business landscape, with improving the customer experience as a major opportunity. “Just a couple of examples include online self-service solutions and to create reliable workflows. There are already deep-learning models being used for chatbots, and as deep learning continues to mature, we can expect this to be an area deep learning will be used for many businesses,” asserts Forbes.

In its round up of deep learning business leaders should understand, meanwhile, VentureBeat highlights image understanding (think Google Image Search), sequence prediction, language translation, and generative models as breakthrough areas for businesses.

However, the McKinsey discussion paper also points out that most companies face significant challenges when it comes to leveraging the full power of AI and deep learning. So while it is applicable to real business problems across areas including marketing and sales, supply chain management, and manufacturing, we are not quite there yet.

According to experts, the key to overcoming these limitations and harnessing the full power of deep learning is managers with both technical skills and business acumen. McKinsey partner Michael Chui told the Financial Times, “The technologies are levers of value creation. [...] Digital means you can do more, faster. If you can successfully scale something across an organization or a customer base, you have that much more impact.”

It follows that business schools across the globe are expanding their offerings in AI and deep learning in order to prepare future leaders to be confident in this new frontier. If you are thinking of a MBA in Artificial Intelligence determining the quality of a prospective business school’s AI curriculum is important.

According to U.S. News & World Report, five key considerations can help guide you to a suitable program, including: assessing how realistic the courses are; whether the curriculum puts AI in a historical context; whether it addresses ethical dilemmas related to AI; if coursework is available in managing companies with disruptive technology; and if coursework is available in the basic elements of AI.

On the latter point, one professor advises, “If schools do not offer you the fundamentals, the methodological foundations of AI, you probably are not going to get access to the state of the art -- and if you want to make a difference in your career, you probably want to know about the fundamentals.”

The overarching takeaway for students? Given the vast potential of deep learning and its relatively low adoption among businesses at present, organizations are increasingly looking for footholds to help them navigate this challenging terrain. Acquiring knowledge and skills in this red-hot area can lay the groundwork for this successful and exciting career for aspiring business leaders.

Joanna Hughes


Joanna worked in higher education administration for many years at a leading research institution before becoming a full-time freelance writer. She lives in the beautiful White Mountains region of New Hampshire with her family.