Gartner’s research predicts that by 2030, 80% of project management tasks will be run by AI.
, which provides instant status updates and helps users update time and task progress via text, voice or chat.
Advanced and automated system testing solutions for software projects will soon allow early detection of defects and self-correcting processes. This will significantly reduce time spent on cumbersome testing activities, reduce the number of reworks, and ultimately, deliver easy-to-use and bug-free solutions.For many project managers, automating a significant part of their current tasks may feel scary, but successful ones will learn to use these tools to their advantage.
Training AI algorithms to manage projects will require large amounts of project-related data. Your organization may retain troves of historical project data, but they are likely to be stored in thousands of documents in a variety of file formats scattered around different systems. The information could be out-of-date, might use different taxonomies, or contain outliers and gaps.
If you are seriously considering applying AI to your projects and project management practices, the following questions will help you assess your decision. Are you ready to let this technology make mistakes as it learns to perform better for your organization?
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