The application of AI in project management and performance monitoring allows to keep under control the progress of a project and to be warned potential risks that could determine the success or the failure of a project and avoid those that may prove to be unprofitable.
There are 3 areas in which AI can produce excellent outcomes:
1. Risk evaluation
Keeping in consideration budget and planning caps allow to take apprised decisions about risk management. But planning interdependencies and the external environment can deviate the result of an apparently healthy project. The use of ML (Machine Learning) allows to analyze past projects information to, for example, provide a realistic time line and eventually keep track of statistically reasonable delays.
2. Resource management
To grant the successful outcome of a project on time, it’s fundamental to create the correct team. AI analyzes past data and provides real time information about available and necessary resources and allows to take useful decisions and, if necessary, add extra resources to the project.
3. Predictive analysis
Thanks to predictive analysis it’s easier to allocate the correct quantity of human and technical resources, and at the same time reduce labor costs. The idea at the base of predictive analysis is to identify, analyze and halt risks before they change the course of the project.
An important AI example is Internet of Things (IoT) applied to industry. Machines will be interconnected to each other, providing greater security and the predictive analysis of usage data will grant top performances and superior efficiency thanks to preventive maintenance.
