5 Ways AI Will Be Useful to Managers

By Jamiel Sheikh

Effective management is an evolving art. Since scientific management was introduce by Frederick Winslow Taylor, there have been dozens of iterations of what it means to be a good manager. Perhaps none, however, have ever had the influence that artificial intelligence (AI) promises. AI systems are going to revolutionize business practices throughout corporations, and managers stand to gain just as much as anyone else. The following are five areas in which managers are likely to find AI useful to their everyday work life.

Outsourcing Mundane Work to Algorithms

Harvard Business Review conducted a survey of project managers and the results were surprising: managers claimed that more than 50% of their time was spent on administrative matters. That number may be unusually high; however, even if it’s only 20% for most managers, that still means that one-fifth of their working time is spent on paperwork and admin. Artificial intelligence is going to change that.

AI systems are becoming increasingly adept at filling out paperwork, creating agendas and even drafting reports. As AI’s ability to reason and think like a human grows, the number of tasks AI will be able to perform will grow as well, freeing up more time for managers to focus on what matters.

Decision Making

Asymmetric information plagues decision making at all levels of management. Google is great, but AI is going to be even better. AI systems trained to search the web will scour millions of webpages to find the desired information and provide higher quality inputs into a decision-making process.

Managing People

Artificial intelligence is all about data and in its quest to learn, AI systems will devour incredible amounts of information from a number of fields. In doing so they will make countless connections, discovering correlations that no human could ever imagine. One such correlation is likely to be the odds that two people, based on their personality type and past performance, will work well together in a team.

Even if AI proves less than outstanding at predicting who will work together well, it may prove useful in raising red flags before a project is ever started. Assessing personality and preferences, artificial intelligence systems might soon be able to predict, to a high degree of success, that two people will not be good together. By acting on that information managers may be able to save themselves a great deal of trouble down the road.

Mastering the Art of the Negotiation

Progress is rapidly being made on artificial intelligence systems that can read human emotions not only through facial analysis but also by analyzing voice patterns. As this technology improves, managers will be able to use it in negotiations to get a more thorough read of the person sitting across from them. This could prove invaluable information as crucial decisions are made.

The same AI systems could also be used in focus groups or in customer interactions to get a clear picture of how someone perceives an item or service. The best part? Emotion-reading AI will detect signals that are almost impossible to fake, making them a high-quality source of information.

Hiring

Hiring personnel can be a time-consuming process but artificial intelligence is going to make it easier. There will be AI systems that can be programmed to sort through hundreds or even thousands of applicants in order to find the best potential fit. While it’s possible to sort applications now based on somewhat rigid parameters, future AI systems will achieve a depth of search that is currently impossible.

For instance, an AI might find that a potential applicant studied under the same professor as another employee in the company. It could alert the manager to ask that employee about the potential hire’s work ethic. Or it may sort candidates based on personality traits to find someone who will work well in a given team.

A word of caution, however. AI’s do not have an ingrained moral sense and unless they are carefully programmed, they may display certain biases. For instance, an AI scrutinizing the hiring record of a manager may find that he predominantly favors candidates from a certain ethnic group. Using that information, the AI may display a marked preference for applicants from that group and discard all others, no matter how qualified. To an AI this appears logical based on that manager’s past actions.

To combat this, it is important to pay close attention to how artificial intelligence programs screen applicants and what, if any, biases they display. Warnings aside, if done right AI has the chance to dramatically improve the hiring process, reducing the workload of busy managers.

About the Author

Jamiel Sheikh is CEO of Chainhaus, an advisory, software development, application studio and education company focused on blockchain, artificial intelligence and machine learning. Jamiel has more than 15 years of experience in technology, capital markets, real estate and management working for organizations like Lehman Brothers, JPMorgan, Bank of America, Sun Microsystems, SONY and Citigroup. Jamiel is an adjunct professor at Columbia Business School, NYU and CUNY, teaching graduate-level blockchain, AI and data science subjects. He runs one of the largest blockchain, AI and data science Meetups in NYC.