How AI is revolutionizing project management

AI for project management

By Naveen Joshi  |  July 10, 2018
Naveen Joshi is founder and CEO of Allerin, which develops engineering and technology solutions focused on optimal customer experiences

AI in project management is expected to refine team performance and augment overall organizational productivity.

Implementation of AI in project management is transforming the way teams and resources in a workplace are planned, put into effect, and piloted to achieve strategic project goals within the specified time.

Project management requires the collation of various resources, planning, execution, and delivery of certain goals within the stipulated timelines. Working with a team demands a lot of collaboration and management. Until now, project managers and team members have been coordinating with each other in person to deliver a project on time. But, this approach has certain flaws:

  • Ineffective risk analysis
  • Improper resource management
  • Inaccurate detection of problems

However, AI in project management is bringing in a fresh wave of technology to automate these tasks and revolutionize other aspects of project management.

AI in project management

AI in project management

Project management with AI is the use of software that can manage various projects fed into it simultaneously, without any manual interference. It employs artificial cognition and predictive analysis on a large scale to aggregate and segregate data in a format that is easy for the end users to read and work with.

While offering solutions to the problems mentioned above, AI has revolutionized project management in the following ways:

Probabilistic risk analysis

No matter how comprehensive your plan is, the risks involved while executing it are probabilistic. Computers are, undoubtedly, better at probabilistic assessment, especially when multiple factors need to be considered. Applications are now being developed to work with both structured and unstructured data for revising the existing management strategies. These applications:

  • Study project data to predict the outcomes at every stage
  • Determine the start and end dates based on the rate of completion for an ongoing project
  • Visualize the current project statistics to determine the upward or downward risk trends
  • Help in studying the existing data to make decisions regarding the next steps
  • Update time estimates for individual tasks and notify the team about the deadlines

Resource management

AI project management tools are used to survey the resources employed in a project to not only optimize the performance but to make the project sustainable by:

  • Studying the past data and estimating the budget revisions with the help of regression models
  • Informing team members of their productive hours using real-time computation
  • Sorting emails and daily to-dos, leaving you free to focus on other tasks at hand
  • Estimating the productivity of each team member with statistical learning

Experimental learning

AI programs with their artificial cognition and reasoning abilities can simulate experimental models based on the information fed into them. These models can then be used to predict the outcomes of the experiments in the future. For instance:

  • Robotic process automation (RPA) can be used to create data models, which can evaluate and report process executions in the future
  • Pattern algorithms analyze the skill sets of the members to estimate the project tenure and sort people into teams based on their skill sets
  • Statistical learning methods from history and database to allow problem-solving

All these AI applications are being tried and tested to integrate with the existing project management software.