Enhance your Project Management with Artificial Intelligence

1. Accelerate Project Creation

Generative Artificial Intelligence can be used to accelerate the project management process. In this video, we demo how AI can assist in creating the WBS and schedule of the project, as well as generate a first list of risks to work with. 

Learn more about our Generative AI use cases in our product blog

In this video, we demo how AI can assist in creating the WBS and schedule of the project, as well as generate a first list of risks to work with.

2. Ease user adoption

Oscar bot demo

Chatbots speed up user adoption by automating data retrieval and manual entry.

The AI-powered chatbot Oscar in Planisware Enterprise enables automated information retrieval in seconds through the mobile app. Curious about the status of all projects across your portfolio? Just ask Oscar!

Oscar streamlines the data entry process and improves speed and accuracy through augmented data entry. It auto-corrects mistakes, reducing errors.


3. Improve data quality

Data quality is critical because it directly impacts the accuracy of AI models. Poor data quality, such as missing or inconsistent values, can lead to incorrect or biased results.

With Planisware Enterprise, you get access to anomaly detection features that automatically flag potential data issues. Fixing these will improve your data quality over time.

Project managers can also use AI in Planisware Enterprise to find similar completed projects. This information can provide valuable insights into potential risks and help estimate task durations.

AI fixing quality issues

4. Automate forecasting

How to use Planisware Enterprise predictive analytics to uncover insights in your data.

AI can improve the accuracy and speed of project forecasting. By analyzing data from previous projects, machine learning algorithms can predict project outcomes, such as completion times and costs, and help organizations to plan more effectively.

With predictive analytics in Planisware Enterprise, you can train a model on any data in the tool and use it to estimate any output. Typical use cases include:

  • Estimating task durations during the planning phase
  • Forecasting project budgets
  • Predicting resource utilization and workloads

By incorporating AI-powered predictive analytics into their PPM processes, organizations gain a more accurate understanding of their projects, and make data-driven decisions that maximize efficiency, minimize risk, and drive better outcomes. 

Hear from Moustafa Mahmoud Hefny, manager of Project Management Systems and Data Management at ADNOC, on how his business started its AI journey with Planisware Enterprise

AI heat map