How Project Management and AI Will Work Together in the Future

Ogi Djuraskovic is the founder of FirstSiteGuide.com. On his website, he is trying to help people build a successful online business with the right mix of skills. Besides his online tutoring, he really enjoys offline activities, such as mount biking and walking his Frenchie, Jumbo.

Keeping fingers on the pulse of the industry or niche that interests you is very important, but what do you do when you wake up one day to see that Gartner predicts that Artificial Intelligence (AI) will take over 80% of project management tasks by 2030? Do you consider it as good or alarming news?

The moment the first project management software suite was launched the entire niche began heading towards automation, AI, and ML implementation.

And, no, you shouldn’t see it as alarming news because AI is not going to replace project managers. It’s bound to take over dull, repetitive tasks and leverage data to provide precious insights in real-time.

Let’s see how AI and project management will work together in the future.

This Article Contains:

Where Is AI in Project Management Currently?

In its essence, project management is a category that encompasses processes vital for any project’s success. These processes include every aspect of the project plan:

Outlining and defining tasks
Budget planning
Identifying risks and devising a risk management strategy
Outlining communication channels and communication plan
Making project schedule
The resource to task allocation

AI has managed to find its way into project management, helping with various things. The most common use case is workflow automation. However, AI can also help streamline other parts of work including:

Predict project deliver dates
Perform project cost estimations
Capacity needs forecasting
Auto scheduling
Resource optimization
Risk monitoring in real-time
Bottleneck identification
AI marketing tools

Whether you’re already running a company or planning to start an online business, AI can help you streamline your projects on auto-pilot.

AI’s Ability to Understand Complex Projects

It’s easy to understand a simple project. It doesn’t take more than one person to do it when there are a couple of tasks, a handful of people, and simple resource requirements. The problem starts when things start to scale up. Understanding projects and making in-time decisions before the projects goes off track becomes borderline impossible with hundreds of tasks, task dependencies, people, and resources.

Planning those projects is hard on its own, let alone managing them. It’s simply too much information for a human being to handle. This is exactly where AI can help. Why? Because AI doesn’t care how much information it has to handle. In fact, the more data you give to it, the more accurate decisions it will make.

The Hangover thinking — The Hangover via GIPHY

There’s one more thing that makes AI better when it comes to understanding projects. You can feed all your past project data to an AI. It will go through every data set, discover patterns, and most importantly, learn from them. Thanks to that data, AI can make accurate predictions for your upcoming projects.

It can also transfer this knowledge to help you with your current projects. It can help you catch errors and bottlenecks early on.

Bonus: AI Content Creation Tools & Copy AI Alternatives

A Better Understanding of Data

The ability of AI to better understand projects is based on its ability to comprehend data. AI is not only capable of identifying patterns and learning from the data you feed it. It can also identify the correlation between two variables in the data set that nobody else would have thought existed.

AI can use the historical data to create perfectly optimized workflows, create balanced work and time-off schedules, and estimate workloads for every phase of the project. It can even assess things such as whether the current workforce has sufficient knowledge and skill to complete the project. And if not, pinpoint team members who are required to improve via training.

How does AI understand data better? Here are the most important AI sub-domains that enable it:

Machine Learning- this is perhaps the most important AI sub-domain for understanding data. It helps machines learn from past experiences and make informed conclusions
Deep Learning-as an ML subdomain, deep learning furthermore extends machines’ capability to make intelligent decisions independently
Neural Networks-it stands for a number of algorithms developed to help understand the data and discover connections between variables
Natural Language Processing-it helps machines understand language
Cognitive Computing-it helps machines emulate our thought processes

The Pirates of the Caribbean Johnny Depp — The Pirates of the Caribbean via GIPHY

Improved Risk Management

While every project is unique, they all share in common—no matter how well they are planned, there will always be risks that pose a threat to the quality and competition of a project. Risk management strategies are as old as project management is. However, AI is here to bring it to an entirely new level.

AI can manage it in two ways: learning from past project data and project simulation. AI can determine all the risk factors that contributed to project delays and failures in the past and decide whether or not they are present in the current project.

The second one refers to AI running a simulation of a project. It can simulate risk and opportunities in thousands of different scenarios to pick the best project management strategy for any particular project.

Bonus: AI Text Generators

Applicable Advice and Insights

Project managers don’t have the luxury of going through dozens of completed projects looking for factors that contributed to project delays. It’s hard to have insights from piles of reports, hundreds of tables, and performance assessments. It’s also time-consuming to manually create custom workflows for every project.

AI can completely automate it. It has the capabilities to learn from past project data, run countless project execution simulations, optimize workflows, and monitor projects in real-time. AI can deliver actionable advice and insights on demand. Whether you want to have insight in real-time or seek advice for future projects, AI can deliver and help you streamline task automation risk-free.

So, Where Does All of It Leave Us?

There are many touchpoints between AI and project management today.

Given the current situation, it’s safe to assume that AI will continue to penetrate the project management software niche introducing new useful features and capabilities.

The cutting-edge project management automation tools such as ClickUp already offer many benefits ranging from the multifunctional dashboard to full-blown task automation.

If you’re interested in more software-related guides, feel free to visit FirstSiteGuide.

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