How Machine and Deep Learning Will Affect Project Managers

There is an unfair sentiment by some that artificial intelligence (AI) will replace the job force, rendering humans irrelevant. In reality, however, AI will live side-by-side with human employees, making their jobs easier. In the near future, project managers’ daily workload will become much simpler due to machine and deep learning algorithms that reside inside project management software. These AI capabilities are not a threat to the future employment of project managers; the job still requires a great deal of social skills that computers are incapable of providing such as motivation, encouragement and persuasion. Instead, machine learning algorithms will provide project managers with an incredible resource for creating task timelines, assigning tasks, tracking project progress and even predicting outside factors that could potentially cause delays.

Project management software provides a wealth of important data which project managers can attempt to manipulate into actionable improvements within their operations. Data is crucial in building effective machine learning algorithms: the more data that is accessible, the greater the ability of the AI. Specifically when predicting timelines, project managers rely on historical data to determine how long specific tasks or an overall project will take to complete. This can be a time-consuming and difficult process, but AI will be able to automate this procedure, saving the project manager valuable time and effort.

Additionally, the growth of cloud computing provides the opportunity for an even greater breadth of data that AI can utilize. Not only will project management AI be able to access a particular user’s or company’s historical data, but it can learn from the data of all companies that use that same project management software. The data from outside businesses would remain anonymous and a company would need to opt into such data sharing plans. Regardless, the ability for an AI to determine the length of a task not just based on one company’s data, but a variety of companies, would be invaluable.

Artificial Intelligence Benefits in Practice

For example, a construction company takes on a project to build a 12-story hotel. This company has only completed a similar project once before. A project manager is attempting to determine how long the HVAC installation will take, but historical data is scarce. The project manager can input an estimated timeline, based on the company’s data from the prior project, into a project management tool. Then, the AI within the tool can scan the timelines of other companies to see how long their standard HVAC installation took to complete. The AI may output a timeline that the project manager then deems unrealistic. While the project manager may have to reject the provided timeline, the manager now has a baseline to work off of that would not have been available otherwise.

That same AI could take into consideration outside factors, such as weather, that are often difficult to predict. Staying with the above construction example, let’s say that the crew is unable to work on days that it rains. For project managers, rain days are very challenging to predict. Machine learning algorithms could consider historical weather data from previous Octobers and estimate the number of days construction will need to be canceled due to rain. This is just one example of a number of outside factors that can cause headaches for project managers, which AI can preempt.

A balanced relationship between AI and project managers is going to become increasingly important. Project managers will need to know when to correct the AI and when to take the AI’s outputs into consideration. Machine learning software will give users an output based on the data available, but it may miss certain things that haven’t been factored into the AI’s programming. Ultimately, AI will improve the daily procedures of project managers by simply providing a baseline for strategic decision-making.

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