Artificial Intelligence is disrupting every industry you can think of and project management is no exception to this rule. According to AI Innovators: Cracking the Code on Project Performance report by PMI, 81% of project managers admitted that their organization has already been impacted by AI. 

The report also predicted that projects managed with AI will increase from 23% to 37% in the next three years.  As the impact of AI grows, project managers will have to adapt. AI will change the way projects are managed, how the strategy will be implemented, tasks are performed, and decisions are taken.

AI In Project Management: 7 Ways AI Will Impact Project Management

In this article, you will learn about seven ways in which AI will change project management.

1- Predictive Analytics

McKinsey conducted a study on 1800 software projects and found out that only 30% of projects are delivered on time. What’s even worse is that 20% of these projects managed to meet the deadline because they have removed certain features and functions from the project scope.

McKinsey’s study also revealed that variation in dates decreased when project managers used predictive models. There is a 30-40% reduction in defects per line, which enhances the quality of code. By leveraging predictive analytics for planning and decision making, project managers can drastically reduce project failure and increase the project’s success rate. 

Predictive analytics can also help you with:

• Time management
• Team collaboration
• Better control over tasks

2- Risk Management

Every project has risks, interdependencies, and uncertainties attached to it. As a project manager, it is your duty to assess and respond to those risks efficiently otherwise, these risks could become a cause of project failure. With AI at your disposal, your job will become a lot easier. AI system will alert you of potential risks by analyzing real-time and historical project data. 

More importantly, it increases the visibility in your projects and can also predict possible project outcomes. For instance, project managers can see whether a task will be completed before the deadline or not by analyzing how much time is being spent on a task. The same goes for projects as well.

 3- Project Estimations

There are instances where you are not exactly sure how much time a project might take to complete or how much money you will have to spend on it. That is where you will have to rely on historic business data and project estimation, which can be a hit and miss on most occasions. AI and machine learning are great at analyzing a large amount of data and find patterns so they can deliver useful information that will help you with project estimation.

 4- Knowledge-Based Systems

Gone are the days when AI used to be dumb and can only act based on the data you feed. Today, AI-based systems are smarter than ever before and can learn new things with the passage of time. They can now understand the context of the data, which means that it can offer useful insights that can help you in taking the right decisions. Moreover, these knowledge-based systems can also support human learning, which can also make them more efficient at what they do.

Knowledge-based systems use machine learning and natural language generation to create the documentation for the individual. Mark Broome, chief data officer at PMI, “Learning from a plethora of previously executed projects and associated project management artifacts will be utilized to train AI to effectively assist the project manager in all aspects of project management including charter development, time and resource estimation, communications, risk identification and management.”

5- Machine Learning

Machine learning is at the heart of all AI technologies. It does a fantastic job when it comes to identifying patterns. Project managers can harness the power of machine learning to study patterns in your project schedule and it will highlight areas where you can accelerate the project process. You can also use machine learning to assess risks and allows finance managers to give a better offer to customers. This can increase company revenue and profits. It can also be used to automate approval workflows and remove friction.

6- Decision Support Systems

Two of the biggest questions most businesses are asking is “Can AI-powered decision support system can increase project success rate by reducing cost and errors?” or “Can these systems increase efficiency and prevent your project from exceeding deadlines and budget?” Fortunately, the answer to both these questions is yes.

These decision support systems create smart processes by using rules and logic and help you automate your decision-making process. Additionally, it can help you make the right decisions in complex situations. Broome predicted that “As decisions need to be made throughout the project, project managers will rely on predictive models to assess options and select those that provide the highest likelihood of a positive outcome.”

Machine learning algorithms can also help businesses visualize which features of your product customers are using and which ones they are not. This will allow project managers to take the right decision on which features they should improve and which ones they should drop.

7- Resource Management

Lance Olsen, Director of Microsoft’s Cloud AI team said, “Some AI-based tools businesses are already adopting such as predictive maintenance can make the project more efficient.” Task management tools like TaskQue is the best example in this regard. It uses an intelligent task assignment process to optimize resource utilization and maximize productivity without overburdening your employees. Project managers can also automate mundane and repetitive tasks with AI and make their team focus on more value drive activities.

How will AI impact project management? Share your thoughts with us in the comments section below.