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AI In Project Management - The Humble Road To The Bright Future

Jul 225 min read

Jarosław Ziembiński

IT Project Manager at Ideamotive and agile advocate.

Project management is an interdisciplinary field that requires a vast array of soft and hard skills. Supporting the companies in this matter is another field that can be augmented with machine learning-based AI solutions.

 

Quin Shi Quang was not a nice guy for sure. The Chinese emperor who reigned 221 BC to 210 BC was cruel and ruthless, with shady episodes of burning of books and burying of scholars, which resulted in hatred among educated people of China. Commoners hated him for one of his greatest achievements - finishing the unification of defense systems into the one Great Wall of China. According to various sources, the construction could have cost over millions of lives. 

 



Apparently, when asking how to be a successful project manager you shouldn’t look only among nice guys for inspiration. 

 

On the other hand, the Great Wall is one of the earliest, apart from the Great Pyramid of Giza, examples of practical project management done on a large scale. Due to the gargantuan scale of the building to be constructed, the overseers had to divide the whole process into smaller chunks to make it bearable. 

 

It was far from modern project management, yet closer than most of the processes done before the 20th century, when the management theory was born with the Gantt and Adamiecki charts.

 

In modern management, a project can be basically anything, from designing and printing new leaflets for the upcoming event to finishing the delivery of a new aircraft carrier. Delivering a project is something unique and time-limited, in contrast to business operations. Thus, it requires a separate set of skills, especially from the IT project manager.

Modern Solutions - AI In Project Management

Considering the modern shift from operations toward project management, it is not a surprise, that there are multiple AI-powered tools to support the practice and provide managers with better insight. 

 

Artificial Intelligence solutions support nearly every industry with specialized tools that perform tasks previously unseen. According to the AI Innovators: Cracking the Code on Project Performance report delivered by PMI, up to 81% of project managers claim that their organization has already been impacted by the AI-powered solutions. 

 

Also, the report states that projects managed with AI-augmented solutions will increase from 23% to 37% in the next three years. The impact of AI is huge overall. Gartner predicts that by 2020 AI will generate 2.3 million jobs, exceeding the 1.8 million that will remove. So, there will be more specialists and projects to manage with the new technologies. That is a strong point for IT project managers.  




Google’s CEO says that AI can be even more important for human development than electricity or fire. So what are basic processes in project management to augment with artificial intelligence?

 

1. Project management assistance


Project management is a complex matter that lies on a crossroads between multiple departments. Usually, it requires knowledge from various fields, including the expertise of the company’s specialists that deliver the product, marketers who will spread the word about the achievement and accounting, responsible for budgeting the task. 

 

Due to the advancements in the AI and machine learning field, the role of artificial intelligence in project management is growing. But despite the developments, the “narrow AI” is currently the most popular option, providing support in only one, chosen field of interest. 

 

And by that, it can deliver significant support. 

 

Example:

Stratejos started by focusing on estimates and budgets. This field has always been data-rich due to legal and fiscal reasons. Companies always had to keep these data not only to support their daily operations but also to keep compliance with the law. Now, the data collected throughout the years can be used to support business in a new, ML-powered way. 

 

Memo is another example, but this time it is not about the numbers, but the knowledge that is in the team and is required to finish the project. Sometimes building the mutual understanding between different departments, be that engineering or marketing, can be equally challenging as delivering an intercultural dialogue and Memo aims to bridge these gaps in an AI-powered way. 

 

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2. Predictive analytics in project management


Since the dawn of big data, there is an increasing amount of information to process regarding nearly everything - from customer information to products to nearly everything. Analytics company IDC expects that there are going to be 175 zettabytes of data worldwide by 2025. 

 

But data is not necessarily knowledge. And the best tool to reforge meaningless records into valuable insights is Artificial Intelligence.

 

Example:

Predictive analytics is currently a feature that is hard to find on the market, especially considering the nature of the data to analyze - there will be other events to predict in the software development projects and another in civil engineering. 

 

Riter is currently the tool that aims to augment project management with general predictive analytics. The core functionalities are aimed to automate sprints planning by distributing them in an optimal way with the data gathered before. 

 

3. Expanding project understanding


There is ongoing research on general Artificial Intelligence that will be able to process a wide array of data, without being limited to the one type of one domain. The difference can be shown with the example of image recognition software. 

 

The solution can be trained to sort the incoming images to a cat pile and dog pile. But if there is an image of a horse or a car incoming, the solution will get confused and deliver an error. Even the best software existing is unable to extrapolate the owned knowledge into other areas of the project. Examples can include: 

 

  • Predicting the rejection of the code on the estimated delivery time
  • Measuring the impact of lifting prices of the components on the overall ROI of the project 
  • Correlating the general delivery stats to provide better time estimations. 

 

The possibilities are endless. Also, the machine is never biased nor overfocused on its field of expertise. Thus, there is no risk that it will filter the delivered predictions with previous experiences or presuppositions. Good support for the IT project manager



4. Risk predictions


The risk of failure is an immanent element of every project and a key indicator of how to be a better project manager. Proper identifying the risks before launching the project is crucial to properly manage the project development and increase the chance of success. There are at least five reasons why projects fail: 

 

  1. Lack of resources - an obvious one. The team overestimated its abilities or underestimated the required resources
  2. Scope creep - according to the Geneca survey, only 55% of project managers are clear about the business objectives of their projects. In a nutshell - 45% of project managers have no idea what is the purpose of their work! 
  3. Poor project handling - sometimes the lack of management is the greatest threat to the management. Trite but true. 
  4. Lack of interest form stakeholders - another obvious one, the project not considered important will either proceed by the insertion or will fade into the oblivion
  5. Not paying attention to the warning signs - it is natural for a team to believe in their ability to deliver the project. Sometimes such optimism can be deadly. 

 

The artificial intelligence-powered solution is able to spot all problems above apart from the lack of interest from stakeholders. This one is (and will always be) the responsibility of the project manager. 

 

5. Task automation

Last but not least, the AI-powered solutions, when fed with enough data, can automate many tasks related to project management. The scope of automated tasks can vary depending on the project and the will of the manager to leave the management to the machine. In the end, nobody wants their job to be fully automated. 

 

The tasks to automate can include sending prompts and reminders to the team, automatic budgeting or cost estimations or delivering pre-processed schedules. You can set such automations in many project management tools. At Ideamotive, we use - ClickUp - it is a powerful project management tool with easy-to-set automations to make your job more pleasant and more efficient.

 

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PROTIP: To take the automation even further, make sure you leverage the full power of Zapier and connect all the tools you are using into one ecosystem!

Summary

Project management is currently the dominant way of delivering results in business. Management was always an element of every human venture, be that building the Great Wall of China, producing steam engines or delivering software. 

 

In ancient times the key component of the project management was the manager and his ability to hold and process everything in his mind. The hermetic knowledge and brilliancy enabled masons of the middle age to handle large-scale projects like the Cologne Cathedral. According to folklore, Master Gerhard of Ryle had a bargain with the devil to complete the well… project. 

 

In the same way, the Great Wall of China was coordinated by a small army of overseers, basically sub-project managers (junior project managers?). So everything was based purely on keeping all processes in mind. A thing that modern managers avoid and expect to be supported by systems and tools ( or any AI based project management tools) with that.   

 

With the interdisciplinary nature of the project management, it is unlikely for it to be fully automated in the near future. But elements of the process or single tasks can be augmented today. 

 

If you would like to know more about that, feel free to contact us and discuss your needs. We will outthink your challenges together and deliver something interesting for sure!

Jarosław Ziembiński

Jarosław is an IT Project Manager at Ideamotive. Agile enthusiast with master experience on working with technical teams.

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