Project management remains a largely manually intensive function. The project manager creates a project management plan which includes the risk register, stakeholder register and numerous other documents. The PM also reviews changes, manages a project team and communicates to stakeholders which are all time-consuming activities. Automation consists of the scheduling software and this can only be considered automated if the project start date is hard coded and the remaining activities are coded as dependencies.
Attempts have been made to automate some tasks such as creating status reports or capturing and communicating meeting notes but these do not provide significant value to the project. Perhaps automation in project management is slow to materialize because each project is unique and every project has a myriad of challenges and changes that are difficult to predict. PMOs can only offer templates and hope for a consistent result. Integration of project management tools with the sponsoring organization’s other existing software applications is a potential to help provide value but is also problematic. For example, there are time tracking tools that can automatically update the project schedule by updating the time spent on an activity and then the PM can use the result to compare this to the forecast. However, the nuances of estimating the original amount of time required on an activity then matching it to time spent is an imperfect equation. For example, assume an estimated activity is planned to consume 40 hours with a variable of +/- 10%. Meanwhile the person working on the activity submits 30 hours which may include some non-work-related time. Is the activity complete? Is it ahead or behind schedule?
The problem with automation in the examples above is that there is no ‘intelligence’ behind it and this is exactly where AI contributes. It is AI development in project management that will drive automation and without AI, the automation of activities will be protracted and ineffective. AI offers the capability of providing a ‘trained’ intelligence to the automation of project management activities. It is incumbent on organizations and project managers to understand the preparation required and expectations of adopting AI based functionality.