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Why AI project management is the ultimate game changer

Project managers can streamline their processes – such as their administrative duties – by incorporating AI into their workflow. In this guide, we’ll look at what AI project management entails as well as the importance of training your pre-existing staff in AI project management tools.

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What is AI in project management?

AI in project management can be used in the following ways:

  • helping you find out key performance indicators immediately
  • providing an overview of the status of a project and its developments
  • telling you which decisions a project manager should prioritise
  • telling you how long a project will take to complete
  • flagging any risks that might affect the outcome or progress of a project
  • analysing different data sets including speech and language processing
  • testing systems before a project is scheduled to go live
  • helping you to manage complex projects, or ‘megaprojects’

According to a recent report led by the University of Southampton, project managers currently find that AI is particularly helpful for analysing data in large projects, but is less relevant to smaller projects – and perhaps not cost-effective either. One of the key benefits of using AI to analyse large project data sets is that it can help simplify and reduce complex decision-making processes.

Using AI chatbots

AI in project management might also help project managers gain new insights into data sets that require speech and language processing. You might be able to, for instance, use an AI chatbot to provide project updates to team members or provide the right information to different team members without the project manager having to step in to do so. These are known as ‘virtual project assistants’.

Machine learning (ML)

Different AI techniques are beneficial for different purposes, so it’s important to educate your staff on this. Some AI tools will require what is known as machine learning, which is when you feed the AI with clean, complete data sets to provide solutions. 

Machine learning is useful in that it can identify clear patterns in the data that you’ve provided and is able to learn from the data. However, not all problems that you need to solve with AI will require machine learning. 

AI in digital transformation

You can therefore benefit from using ingenuity and imagination when it comes to incorporating AI into your project management processes. As using AI in project management is still relatively new, it is up to business owners to come up with new ways to use AI that work with their specific needs – there is no one-size-fits-all solution. 

While AI in project management can be a huge boon to your business, don’t forget that it will be a game changer for your entire team, including changing the way that they have run operations in the past. Your transformation could be a success or failure depending on how efficiently you have taken on board the considerations below.

Good data and machine learning 

When it comes to using machine learning, project managers might face some obstacles if they are not familiar with using these tools. As your managers are likely to use ML AI project management tools to spot patterns in data sets, it’s important for them to be aware of the differences between raw and clean data. Making sure that the data that you’re using is clean and structured in a way that your machine-learning tool is able to use is a crucial first step. 

What is good data and why is it important when using ML tools?

The ‘good data’ that you will need for your machine learning tools must meet the following requirements:

  • accurate
  • reliable
  • complete
  • timely
  • relevant

Therefore, it’s worth ensuring that you are already collecting the right kind of data – ‘good’ data. This means that you will be collecting data that is complete and meets the aims that you are looking to meet. In the case of project management, this could be collecting the right data so that you can train your AI to provide regular updates on key performance indicators.

When it comes to using AI machine learning for people analytics, you will most likely be using it for prescriptive analysis. This involves taking predictions made on the basis of data sets and using them to create possible outcomes. 

Using AI to test systems

One of the most fundamental parts of project management is testing systems. You can use AI in order to test projects before they are scheduled to go live, giving you key insights into whether the project is likely to be successful or not. Different aspects of project management testing that you can use with AI include:

  • detecting defects in software products early
  • analysing a system’s resilience and longevity
  • analysing a system’s safety (such as performing health checks)

Some of the benefits of using AI in this way may include:

  • reducing operator bias during checks
  • continuous testing over long periods of time
  • reducing any repetitive checking that project managers are responsible for
  • reducing how many reworks a project requires

Training your staff in AI project management

In order to use AI in project management most effectively, your project managers and other team members will have to understand the role that it plays, including how it works, its strengths and limitations. One huge benefit to project managers is that using project management AI in order to take on repetitive tasks can mean that they have more free time to work on other parts of the project delivery process.

According to the Southampton artificial intelligence in project management study, AI has a perceived usefulness in complex projects, but also a low ease of use. This means that your staff may consider AI to be a difficult new tool to learn, making this a hurdle that you will have to overcome in order to sufficiently train them in AI tools. Your managers may find using machine learning to be daunting, particularly if they aren’t sure if they are using it effectively or not. 

Project managers may lack the skills required to use AI effectively

What’s more, the study found that a large number of project management professionals believed that they weren’t sufficiently trained in AI, relying on their own self-teaching and programming skills to use it – which they believed were not adequate. It is also important to bear in mind that AI will affect the project management profession greatly and so has implications for early adoption. Another hurdle is the lack of trust in the technology, as well as staff believing that AI will replace their jobs.

Skills gap analysis

AI in project management also entails a move away from administrative skills and towards soft skills. Many project managers may have to upskill in order to incorporate AI into their skill set so that they are able to use it advantageously. You might want to conduct a skills gap analysis to see which skills they require.

Reskilling and upskilling

Therefore, reskilling and upskilling in skills like programming can help project managers develop the right abilities for using AI effectively. As using AI is relatively new when it comes to project management, it is difficult to tell how useful it will be in various stages of project management and where it will most often be used. This provides project managers with the opportunity to explore the tools available, meaning that a combination of self-teaching, exploration and professional training may benefit these professionals.

AI in project management can be a game changer when it comes to data analytics and automating repetitive tasks. When it comes to using AI for project management, you will likely be using machine learning tools in order to analyse patterns in large data sets. The inclusion of AI in your project management strategy will likely mean that your project manager’s responsibilities will shift, so don’t forget to train them in the skills that they will need in order to work alongside AI effectively. 

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