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ARTIFICIAL INTELLIGENCE & MANAGEMENT SCIENCE

We may be approaching a seminal moment in management, where technology and management trends converge to accelerate business transformation. Here, we’ll highlight how two current trends are going to transform management during the next decade.

Both trends have been around for several decades but have distinctly different histories. Interest in Artificial Intelligence (AI) has recently skyrocketed due to its recent, spectacular achievements. Management science, which applies mathematical methods and computing to difficult business and management problems, has had a quieter but no less impactful history.

During World War II, Management Science became identified as a well-defined body of knowledge as it helped in optimizing difficult logistics tasks by achieving an optimum allocation of limited resources among competing activities, under a set of constraints. It’s hard to overstate how much this has fundamentally changed business culture, from a culture of “gut instinct” and personal intuition, to one where structured, informed decision-making is preferred – when it is possible.

“AI now allows us make valuable usage of the huge amount of data generated every day – social media chatter, traffic patterns, weather, a plethora of open data sets, and many others. And importantly, it can now tackle three types of decisions that are key to management science.”

Mathematical models are simplified representations of the real world — but interestingly, they are also the basis of modern AI. These models are required to help us move from data gathering, to understanding (useful information), to making relevant actions. That is, to a tee, the definition of AI: it is giving computers the ability to learn, to interpret information, and then generate decisions as a result of the scenarios it has identified.

The obstacles to success of AI in the past have been the inability to digest and interpret the available information – and with increasing amounts of data generated by technology, the obstacle was not going away. The recent resurgence of interest in AI has been driven by the technical success of Artificial Neural Networks; these neural networks have been able to handle these vast amounts of information.

AI now allows us make valuable usage of the huge amount of data generated every day – social media chatter, traffic patterns, weather, a plethora of open data sets, and many others. And importantly, it can now tackle three types of decisions that are key to management science.

AI can support strategic decisions; those can be major capital investments in production capacity, mergers and acquisition, distribution networks, and even financing decisions.

AI can support planning decisions; these effectively allocate assets and human resources to satisfy demand and optimise revenues, taking into account operating constraints.

AI can support operational decisions; manufacturers assigning and sequencing production orders, managing inventory, scheduling transportation, and even granting credit to customers.

These three types of decisions interact with one another, and the resulting web of constraints and choices is exceedingly complex – that creates computational challenges, even for modern systems.

We’re working on new innovations, such as quantum computing, that help break down these barriers, and contribute to finding optimal solutions to complex decision problems that are impossible to solve today.

While both management science and AI have had separate, winding histories, combining these techniques has the potential to fundamentally change how companies make decisions, from product development all the way through to manufacturing, strategy, marketing and operations.

As a decision maker, you must keep in mind that there is still an insufficient supply of skills to tackle these issues. It is therefore imperative for businesses to develop their own skills and knowledge base in AI and the technologies that will accelerate its growth. Better to skill up now; if you do not, you may end up near the bottom the corporate leagues table.

IBM

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