AI in Project Management: 8 Real Changes AI will bring to Project Management

AI in project management has been a hot topic and its not loosing any steam. We’ve heard all the mind boggling statistics like Gartner saying that 80 percent of project management tasks today will be taken over by artificial intelligence by 2030.

Should project managers be cowering in fear or leaping at the new opportunities? It all comes down to how well you understand AI and how prepared you are for it. Today, we’ll clear away some misunderstandings of AI and explain the 8 real ways AI will help change project management for the better.

What is Artificial Intelligence?

The film industry and pop culture has given us a wild image of artificial intelligence – spanning from a glitchy computer program to omnipresent digital overlords. But all this imagination hasn’t given us a realistic framework of understanding AI of today.

Gartner defines Artificial Intelligence (AI) as the application of ‘advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take actions.’ AI is a big overarching term used to discuss techniques that mimic human ‘intelligence’ such as pattern recognition, language processing and more.

But this does not mean they can suddenly think and work exactly like humans. AI is bound to strictly logic and rules-based frameworks that are heavily on timely and accurate human input to effectively process data. This straight-laced structure is why AI has largely been limited to repetitive tasks and struggles when more nuance is required.

Will AI replace project managers?

Quick answer: No. While AI excels in repetitive tasks without the constraints of biological or emotional burdens, they have yet to be able to handle highly nuanced tasks and are yet to be able to completely manage even the simplest of projects on their own. AI’s role in project management is to assist, not replace. As they help automate the more tedious tasks of project management, project managers can focus on handling human-centric tasks such as strategic thinking, ideation, problem-solving, communication, team-building, and more.

Though they may not replace project managers directly, they definitely will change the role of project managers from mere ‘managers’ to ‘leaders’ that strive to integrate AI capabilities with their teams to achieve the best results. AI will help project managers focus on what is really important and it is the development of those skills that will make project managers more valuable than ever. PMI’s Pulse Report: AI @ Work shows that while project manager roles are shifting, their jobs are not decreasing. Rather, 27% of project managers stated that project management jobs would increase in the next three years due to AI. 

Make sure to find out the most in-demand skills of future project managers to best prepare yourself for the oncoming AI revolution.

8 real changes AI will make in project management

So now that we have a realistic view of AI, what are the real and positive changes can we expect in project management in our near future? 

1. Optimized Virtual Assistants

You may have already had some experience with AI smart bots that help answer queries like Alexa or Siri. On this level, smart bots are able to significantly reduce time wasted from process-related questions. As AI technology evolves, smart bots will eventually become active virtual assistants that help identify relationships and trends, automatically optimise schedules, provide business insight, conduct status-reporting, and more, in real-time without an over dependence on error-prone human input .

2. Enhanced Predictive Analysis 

Budgets, estimations, and actuals. The three core elements that inform decision making to keep a project in scope, budget and time. But keeping track of these constantly moving parts is a challenge and as the world runs faster and faster, human calculations can no longer keep up. The machine learning, calculation and analytical capabilities of AI are able to take predictive analysis to a new level. 

Not only will it be able to keep track of moving parts in real-time, through analysing historical data and trends, it will be able to make accurate predictive analysis and produce models of different scenarios, providing much needed data to support decision-making. Predictive analysis will allow project managers to make better plans and smarter decisions, leading to more successful projects.

3. Intuitive Resource Management

One of the key ways AI will impact resource management is through adaptive workload management. Where currently workload limits are pre-determined and allocated by users, AI will allow for real-time monitoring and analysis of workloads and runtimes. This capability paired with access to historic data allows the AI to calculate potential resource adjustments that can be made to optimise resources.

Though many PPM software are currently able to handle a certain degree of resource management automation, they often still require manual evaluation and adjustments to make full use of the available data. With AI, this can be simplified by directly notifying project managers of the changes and linking resources directly to places they can be best utilized. This entire process may someday even be fully automated, significantly reducing wastages and fully optimizing portfolios.

4. Accurate Risk Management

Risks are one of the biggest factors to project failure and even the most vigilant of project managers can miss potentially project-derailing risks. AI will allow project managers to dig below the surface, identify trends and patterns that can evade cursory glances and give them the ability to make informed data-based decisions. This does not replace the importance of intuition, contexts, and personal experience when identifying project risks but simply adds another layer of accuracy and depth.

Not only will AI help identify potential risks, it can also perform risk modelling and analysis based on accurate, real-time data from a multitude of data sources on the spot. That means any minute changes across the span of the project, be it the slightest change in scope, budget, schedule, and so on, can be actively considered into risk predictions and planning. A better understanding of risks means less opportunities for project failure.

5. Precise cost management

Two of the biggest challenges of precise cost management is inaccurate or delayed reporting. With a high dependency on accurate human data input and approvals, projects lose valuable dollars from time wasted waiting on people and errors made within projects. 

AI helps streamline and automate most of the project cost management activities with higher accuracy by leveraging historical data in real-time for cost estimation calculations, providing reports and updates in real-time, automating approval processes to eliminate bottlenecks and minimizing manual data entry to reduce error. All of these benefits will have the added benefit of allowing businesses to properly reward their employees, boosting productivity and happiness.

6. Improved data-based decision making

The problem many organisations face is not that they aren’t collecting enough data, but rather they don’t know how to use their data effectively. AI’s ability to sift through massive volumes of data, apply analytical frameworks and present meaningful data in easy to understand formats is one of the key benefits it brings to future project managers. Don’t underestimate how big of a difference data-based decision making will make because IBM estimates that by 2025, the market for data-based decision making will sit at $2 trillion.

7. Extensive error reduction

Being human, we’re bound to make mistakes and in projects they happen a lot. Some times minor errors will only add an extra 5 minutes to your day. Other times, it can cost you a whole project and a whole lot more. As project managers are expected to complete projects faster and faster, more errors are bound to happen. For consumer reporting agency Equifax, that one human error led to a 145 million person data breach. With AI, not only will a significant proportion of data input be automated, it will also be able to identify and notify managers of potential errors before they lead to catastrophic consequences. 

8. Increased efficiency and productivity

In the end, this is one of the biggest sellers for AI project management. A direct result of automation, reduced errors, and real-time accessibility is that projects can run faster and team members can focus on more important tasks. One major task to be completely optimized by AI in the future is reporting. Currently, reports shows organisations spend 1 or more days collating project reports, even when they are considered one of the least valued project management processes compared to stakeholder management, risk management and more. AI makes sure we don’t waste time on the things that don’t matter.

The evolution of AI in project management

Hopefully this post has given you a bit more hope, confidence, and excitement for the future potential AI can bring to project management. But how will all these innovations unfold? We believe that AI will go through three distinct phases before reaching its full potential in project management. Make sure to read more about the evolution of AI in project management here.

How to prepare for AI?

Now you know all about the big changes AI will bring to project management and you want to get in on the action before it’s too late. But where do you start? We’ve made a little guide to help you get started on preparing your PMO for an AI future. Make sure to read more to find out the 3 key challenges and opportunities faced by project managers and the PMO in becoming AI future-proof!

Bill Allars

Bill Allars

Bill is a Business Development Manager with 20+ of experience in Project and Portfolio Management, Project Administration, Risk Management and Process Redevelopment.

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