AI in business practice – basics and examples
Artificial intelligence (AI) is of central importance for companies in the area of project management, as it can relieve the project team in many areas and provide useful support. After all, efficient planning, implementation and control of projects is a basic prerequisite for implementing strategic goals, making your own company competitive and securing competitive advantages. The use of AI in project management is becoming increasingly important, especially as AI can support project management in many practical ways. This has been particularly true since the progress made in the development of products that use generative AI, most notably ChatGPT at the end of 2022.
It is true that AI-based predictions are still of great importance for the smooth running of projects – especially as they are becoming increasingly complex. Nevertheless, collaboration with people is and remains a decisive success factor. To date, even the best AI cannot replace the expertise, experience and networking of humans. The advantages of using AI in project management lie primarily in the automation of recurring or monotonous tasks, increasing efficiency and improving productivity. Automation in particular saves time, which project participants can use to concentrate on their core tasks.
AI systems are now regularly used in project management. Companies distinguish between different forms of AI. Large language models (LLMs) are AI algorithms that use deep learning techniques and extremely large data sets. They help to understand, summarize, create and predict new content. Another form is generative AI (GenAI for short). It is used to generate new content, ideas or data that imitate human creativity. Generative AI can translate texts, summarize reports and create presentations. Agents are the most powerful. These smart assistants analyze data, recognize patterns, learn and can automate processes.
Implementing AI in project management
If you want to use AI in project management, you need to prepare the implementation in your company well and plan it in detail. This is the only way to exploit its full potential. Implementation is a multi-stage process that comprises several consecutive steps. Companies should pay attention to the following points to ensure a successful implementation:
1. all current processes must be recorded. They form the basis for deciding whether an automation process with the help of AI really makes sense.
2. it is then a matter of identifying the AI solutions that are best suited to handling the project at hand.
3. in order to be able to implement the requirements of the project, companies should ensure that the selected AI systems are seamlessly integrated into the existing IT environment.
4. the AI systems used must be thoroughly checked and tested. It is important to ensure that they function smoothly and meet all requirements.
5. continuous monitoring and improvement should be sought during use. This ensures a high level of effectiveness.
To fully exploit the benefits of using AI systems in project management, the company should use AI systems in combination with human expertise. The decision-making process for the selection should be based on clear processes. At the same time, it is important to keep the AI systems used up to date and functional. In addition, all employees must be confident in using the AI systems, which requires continuous training.
AI reduces the failure rate of projects
According to recent studies, there are various reasons why projects fail. In Germany, for example, 17% of all projects are considered to have failed, with the percentage of failures in project implementation being even higher in the IT and construction sectors. For larger, multi-layered IT projects, the risk of failure is as high as 43 percent. The following reasons ensure that projects remain unsuccessful:
● Unplanned expansion of the project scope – It often happens that the original project plan is blown up. This leads to the estimated budget being exceeded and delays in implementation.
● Incorrect allocation of resources – inefficient resource management, including time, available staff and necessary materials, often has a negative impact on the progress of the project.
● Project data is not available in real time – if the project management tools in use do not reflect the status quo, they will not provide real-time data. This makes it difficult for teams to identify potential difficulties or problems at an early stage.
● Lack of creativity and innovation – many companies are skeptical of an active innovation culture. This limits their ability to make adjustments or change course when necessary.
However, the use of AI can make a significant contribution to improving project management. AI-supported systems help to improve planning and forecasting accuracy. Routine tasks can be automated, allowing people to focus on strategic issues. AI-supported systems also optimize communication and collaboration, which promotes transparency. Modern, AI-based tools show project progress in real time.
Possible uses for AI applications in project management
AI offers a wide range of applications in project management, for example to support the stakeholders of a project. Overall, AI helps in project management in three areas and to varying degrees. The following project management tasks can be supported by AI systems:
Run tasks automatically
Some tasks that are an integral part of project management and need to be completed – such as performing calculations and analyses or taking notes – can be completed by AI applications with a low level of difficulty.
Using AI as an assistant
AI can also be used to carry out more complex tasks – such as creating schedules or carrying out a risk analysis. It provides suggestions, creates analyses and initial drafts. The project manager must check the results for accuracy.
Using AI to augment human intelligence
This so-called augmentation supports project managers in the implementation of more complex and strategic tasks, such as the creation of business cases for projects. AI systems help to gain further insights. Humans assess the quality of AI results.
With its ability to analyze data, recognize complex patterns and prepare decisions, the use of AI is changing the work of modern project managers. Although this is a lengthy process for which the right prerequisites must be in place, AI will become and remain even more important for project management in the future.
Specific examples of the use of AI in project management
The aforementioned potential uses of AI in project management can be illustrated using specific examples, which are discussed in more detail here. They show in detail how AI systems are changing everyday project management:
● Optimization of work within the project team – the AI automatically summarizes the results of meetings. It also optimizes the flow of information and helps to assign upcoming tasks to the project team member.
● Organizational and strategic tasks – AI improves communication by creating digital content and schedules. In the strategic area, it provides support by processing complex projects with many variables and supports decision-making.
● Creation of analyses, reports and calculations – AI is able to create automated reports, analyze documents and perform calculations. Tabular data and average values can also be closely scrutinized with AI.
● Improvements for risk management – the evaluation of existing historical data helps to identify potential risks at an early stage in the processing of a project and suggest sensible improvement measures.
● Precise planning of resources used – AI systems can improve the ideal allocation of resources. This takes into account the skills of the team members, their availability and the project requirements. This ensures successful project implementation.
In order to make the implementation of the project as successful as possible, companies should always be open to the innovative approaches and ideas that AI systems provide. AI can also be used as a development partner. Data from the project should be collected and analyzed in order to open up new perspectives and uncover correlations.
