What You Should Know About AI in Project Management

What You Should Know About AI in Project Management

According to a forecast by Gartner, artificial intelligence will take about 1.8 million jobs by 2020. However, it will also create 2.3 million jobs, which means that the impact of the growing popularity of AI will be rather positive.

AI taking jobs from humans- this is the most common myth about this technology, however, there are real challenges associated with AI, as well as numerous tangible benefits. It offers lots of opportunity for various fields, and project management is no exception.

Artificial intelligence is often called a disruptive technology, and it’s going to change project management as we know it. Some of these changes will be subtle, but the overall improvement effect will increase every year, as more businesses adopt AI.

Why It’s Important to Incorporate AI into Project Management Processes

Any project requires proper planning. Project managers have to monitor many aspects of project development, including finance, software development, construction, logistics, etc.

There are many complex tools designed for such purposes but they often don’t provide the necessary results and cannot warn resources about the potential problems.

Automation and AI-based decision support systems allow companies to reduce costs and to eliminate many common mistakes, being able to analyze possible risks and allowing companies to spend their budget more efficiently.

According to research, managers spend as much as 54% of their time on tasks related to project management, and AI is able to cut this time in half.

AI-powered solutions allow companies to adjust numerous business operations, making them much easier and less time-consuming.

AI-powered project management systems offer businesses an opportunity to get insights into project performance, to simplify decision-making, and to obtain actionable recommendations.

Such project management systems can cope with everyday management tasks and administration of projects.

Many cumbersome and monotonous tasks can be automated, while the system also develops an understanding of the project performance.

How AI Affects Project Management Today

We can already see how AI becomes a part of project management. For example, Chatbot assistants have become very popular.

50% of medium and large companies are expected to use Chatbots by 2020. Advanced language processing algorithms allow Chatbots to quickly enter the workplace, playing an important role in project management. Chatbots can assign tasks and deliver status updates.

They can also help in organizing meetings, consulting participants about schedules. This feature of AI is also a reason why AI gains popularity in event planning.

Another area where AI solutions come in handy is the prediction of errors. The number of defects found at any stage of project development is a very important parameter that allows IT projects to measure the quality of projects.

Machine learning enables computers to identify common patterns and to predict risks and errors before they occur, improving the quality of the product and suggesting possible solutions.

One of the most popular types of AI solutions in the market is predictive analytics tools. They help businesses estimate the resources and efforts required for a particular project. For example, although all software projects are different, they often rely on the same resources.

Machine learning enables teams to identify common patterns and plan everything accurately. According to statistics, predictive analytics also allows software companies to eliminate up to 40% of defects per line of code.

Benefits and Limitations AI Brings to Project Management

First, let’s take a look at some benefits of artificial intelligence:

  • Actionable insights from data
    Data analysis is the second most common purpose of artificial intelligence in project management after automation. AI is able to detect patterns and correlations in data that would otherwise remain unnoticed by humans. AI enables teams to analyze their past performance with accuracy, creating more efficient plans and predicting possible problems that might undermine the success of the project.
  • Improved efficiency and productivity
    The reduction of errors and forecasting allows companies to increase efficiency significantly. AI can automate many cumbersome tasks, including sending notifications about delays, sending emails, etc. Automation allows companies to save a lot of time, enabling teams to focus on more important things, such as improvements to the project and innovations.
  • Decreasing project costs
    One of the main challenges for most project managers is to make sure that their teams don’t exceed the budget. Not only does AI deal with many administrative tasks, but it can also spot shortcomings in various processes that would otherwise remain hidden. In addition, AI can analyze information on completion time for different teams and estimate the likelihood of projects being completed on time.

Although the advantages of AI are apparent, this technology also has certain limitations.

  • Most AI-powered project management solutions are still at the development stage
    It’s still difficult to convince some decision-makers to invest in AI solutions as they are not mainstream yet. There are many traditional tools that are more familiar and popular. On the other hand, there are promising AI projects, but not all companies are willing to become early adopters. Most often, tech professionals choose to wait and see whether AI project management tools are indeed effective. Nevertheless, enterprise-level use of artificial intelligence has increased by 270% over the last four years, which means that AI has a bright future.
  • Machines can make wrong conclusions if not properly trained
    Many experts point out the fact that computers still lag behind when it comes to critical thinking and decision-making. The success of AI-based solutions directly depends on the data and training process. Companies need to spend more time on training AI programs so that the latter can analyze the data properly and provide insights that will be actually useful. In addition to that, the data should be prepared to use in algorithms, which is also a time-consuming process.

One of the promising applications of AI in project planning is knowledge-based expert systems (KBE). Such systems consist of an interference engine and a knowledge base.

They are based on a traditional “if-then” principle, being able to provide critical recommendations and schedule phases of projects.

Project managers can feed historical data to KBEs, getting estimated resource requirements and project duration.

Another great application is Fuzzy logic. Fuzzy is based on a binary “true or false” logic. Fuzzy logic allows teams to determine project priorities, which is great for portfolio management.

In addition, it improves cost-time trade-offs in construction projects, allowing companies to plan an optimal budget for logistics and material supplies.

Last but not the least, AI is often presented in a form of artificial neural networks that can predict costs based on the scope of a project, types of contracts, and the professional level of a team.

Conclusion

Artificial intelligence is still a new technology; however, it has already proven to be quite useful for project managers.

Not only it helps to simplify repetitive tasks through automation of various processes, but it can also help in decision-making.

AI is capable of analyzing large amounts of data, predicting possible challenges and suggesting optimal solutions.

AI is a great tool for risk estimation and resource management, which makes this technology capable of changing project management as we know it.