What are the current capabilities and future trends for AI in project management? Can AI-supported tools deliver what is currently being promised in terms of increased efficiency, relief from repetitive tasks and improved decision-making? Learn all about it in the chapters outlined below:
- LLMs, AI and agents in project management
- Benefits of AI in project management
- Challenges and risks of AI in the project environment
- Specific examples of using AI in project management
- PMO Survey: Shaping the Future of Project Management with AI
- Important recommendations
- Future AI trends
- Conclusion on AI in project management
One thing up front:
AI will not replace the project manager at this stage. Rather, you will be more successful as a project manager if you integrate AI effectively into your work. And you should definitely do that!
After all, one thing seems certain given the rapid pace of development:
People who use AI will replace those who do not. What is more, companies that ignore AI today risk being overtaken by more agile and better-informed competitors tomorrow.
Let us begin with some basics on this groundbreaking topic!
LLMs, AI and Agents in Project Management
To tap the full potential of AI in project management, you need to understand important basics.
LLMs (Large Language Models) are a key component of many AI applications and focus on language processing. They are AI models trained on extensive text data and can understand and analyze natural language or text and generate content human-like content. However, they do not always understand the meaning behind it.
AI (Artificial Intelligence), on the other hand, is a broader field concerned with the development of intelligent systems and algorithms that can perform human-like tasks. AI systems are able to establish correlations from huge amounts of data. Yet they do not work with real understanding but with probabilities. They calculate which words or information are most likely to belong together with which. As a result, they will generate an answer even if they do not actually have any reliable data. This can lead to incorrect or sometimes even made-up answers (“hallucinating”).
GenAI (Generative AI) can be used to create texts, code, images or music. AI tools such as Microsoft Copilot enable you to take a dialogue-oriented approach. You can elaborate your questions in a dialogue based on previous answers. This makes them different from search engines like Google or Bing.
AI agents (AI Agents) are tools used to automate written and spoken tasks in software. For instance, an agent can single-handedly summarize meeting minutes. It structures the most important topics, discussed decisions, assigned tasks and next steps into sections in clear and concise language.
Benefits of AI in Project Management
AI can be used in a variety of ways in project management and offers a number of benefits. Below, you find a list of the key benefits of AI in project management:
- Increased efficiency and time savings in administration, leaving more time for working with the project team
- Automation of project management tasks through AI
- Generating results with GenAI
- Knowledge building in dialog with AI
- Greater certainty through confirmation from other sources
- Looking at one’s own tasks from a different perspective
- Checking for clarity and completeness
- Incorporating the experience of others
- Making informed decisions
- Learning from one’s own data by combining risks, issue and lessons learned with generic answers from the web
- Analysis of previous project plans to review the current planning
- Cost savings through process optimization and reduction of errors
We recommend you to start automating your repetitive tasks with AI as soon as possible. Given the rapid development of AI, this will keep you informed about what is already possible and what is not yet possible.
For important topics, you should always consult the “virtual coach” and ask yourself: “What would AI say to this?”
This is another way of already taking advantage of the benefits of AI in project management.
Our tip: Identify repetitive activities that could be performed by AI, e.g. creating status reports or evaluating survey results. By automating project management tasks via AI, you gain additional time for more important strategic tasks or “taking care” of your team.
Interested in PM trends? Read about current project management trends here.
Challenges and Risks of AI in the Project Environment
Despite all the benefits, AI also has disadvantages of which you should be aware. LLMs understand the content of data but not the meaning, as humans do. Therefore, you should always check results you generate with the aid of AI. It is often unclear whether AI has understood the meaning of the question or task correctly.
You should always have these key challenges at the back of your mind when working with AI.
- Hallucinations: Occasionally, AI systems can invent information making it important to always critically review the results.
- Data quality: The quality of the AI results depends heavily on the quality of the underlying data.
- Interpretability: There is a limited understanding of how AI systems arrive at their results.
- Data protection and security: You must ensure that sensitive data is protected and access permissions are limited accordingly.
Our tip: Do not accept AI results uncritically. Always scrutinize AI results critically. Compare them with your own knowledge and experience and revise the results as needed. If you report the changes back to AI, it can learn from them for the future.
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Specific Examples of Using AI in Project Management
AI offers a wide range of possible applications in project management. For example, it can take on assistance functions and expand your project management skills (augmentation). Find some specific examples below:
- Optimization of team work: Automatic summary of results from meetings, assignment of tasks and thus optimization of the information flow.
- Communication: Making e-mails sound friendlier and adapting the tone to the circumstances.
- Schedules: Assisting in the creation of schedules depending on the types of projects.
- Analyses: Creating first drafts of documents and providing support for the cost-benefit analyses.
- Automation: Generating reports, analyzing and summarizing documents as well as performing calculations.
- Strategic tasks: Creating business cases and simplifying decision-making for complex projects with many variables.
- Dealing with numbers: Analyzing data in tables, calculating average values and identifying patterns.
- Risk management: Evaluating historical data to identify potential risks at an early stage and propose appropriate actions.
- Resource planning: Assisting with optimal allocation of resources by taking into account the team members’ skills, their availability and the project requirements. However, automatic resource leveling is still a long way off.
Be open to new ideas and approaches that AI can provide. Use AI in project management as a sparring partner. Collect and analyze large amounts of data from your project environment, uncover hidden correlations, review your analyses and gain new perspectives in this way.
PMI Survey: Shaping the Future of Project Management with AI
In their Shaping the Future of Project Management with AI survey from October 2023 (there is currently no more recent one) the Project Management Institute (PMI®) examined the impact of AI on project management. The results are as follows:
- 21% of respondents were already using AI.
- 82% believed that AI would have an impact on projects.
- 91% were convinced that AI would change the way we manage our projects.
At the time of the survey (late 2023) there is a discrepancy between the opinion that AI will have an impact and the low number of people already using it. It can be assumed that the figure would be different today.
The report emphasizes that AI cannot yet take over project management entirely. However, people and companies using it will have an advantage over those not using it in the long term. The recommendation is to get to grips with AI at an early stage.
(source: Project Management Institute, 2023)
Our tip: Keep the ball rolling and find out about the latest studies and developments in the field of AI in project management. Subscribe to technical journals, attend conferences and exchange ideas with other project managers to continuously expand your knowledge. Use the insights from studies and surveys to develop and optimize your own AI strategies.
Important recommendations
The introduction of artificial intelligence into project management offers significant opportunities but also poses challenges. AI will not replace the role of project manager at this stage. Rather, AI-supported tools will enable more efficient ways of working and improved decision-making. Please consider the following recommendations for your work in the project environment.
- Early integration: Do not wait until AI tools are “fully mature.” Start using them now to automate repetitive tasks and gain some experience.
- Critical review: AI-generated results should never be accepted without checking them. Validate the results with your own expertise and complete or correct them if required.
- Focus on automation: Identify repetitive tasks to automate with AI, e.g. the creation of status reports or the analysis of survey results.
- Use as sparring partner: Use AI not only as a tool but also as a coach to obtain alternative perspectives, assess risks and improve decision-making processes.
- Ensure data quality: The accuracy of the AI results depends heavily on the quality of the underlying data. Make sure that your data is up to date, complete and correct.
- Consider security aspects: Protect sensitive company data and set clear access rights for AI tools.
- Establish AI in your team: Train your teams in the use of AI and promote a culture of openness to technological innovation.
Future AI Trends
In the future, AI and especially machine learning will increasingly help analyze huge amounts of data and thus make informed decisions. Natural Language Processing (NLP) is used to process unstructured text data such as e-mails, meeting minutes and reports automatically and filter out relevant information. At the same time, Predictive Analytics make it possible to predict future project progression and potential risks more accurately. This enables more proactive planning and control. Together, these technologies help optimize processes, use resources more efficiently and ensure the long-term success of the project.
Future trends of AI in project management currently focus on improving planning, automating repetitive tasks and making better decisions. Some important use cases could be the following:
- Automatic resource leveling: There is hope that AI will be able to automatically balance resources in the future. Thus, it would be possible to reduce conflicts and suggest people for certain tasks based on historical data.
- Automatic updates of the project plan: It is another trend to automatically update project plans. Ideally, this would be possible by compiling status reports from spoken information in Microsoft Teams meetings.
- What-if scenarios: In the future, AI might analyze the impact of changes in project plans and generate corresponding statements.
- Stronger integration with existing systems: The integration of AI tools in existing software and workflows is becoming better and better. This enables more seamless use. For example, AI agents may also incorporate data from other systems like SAP in order to provide more comprehensive analyses and support.
Our tip: Keep an eye on current trends, and be open to new technologies and applications. Experiment with different AI tools to find out which ones are best suited to your needs. Continuously educate yourself to keep up with the latest developments.
Conclusion on AI in Project Management
The AI revolution in project management is not a hype but a real and rapid development. And it is catching on fast! Companies that adapt AI at an early stage and use it effectively will have a competitive advantage in the long term.
The challenge is to use the diverse options of various AI-supported tools in a targeted and responsible manner. This will allow you to make the most of their strengths. Do use AI for support – but always keep your projects under control.
One very important final point: if you ignore AI today, you risk being overtaken by more agile and better-informed competitors tomorrow.
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Johann Strasser
Managing partner at TPG The Project Group
The certified engineer, has been a managing partner at TPG The Project Group since 2001. After many years as a development engineer in the automotive and energy sectors, Johann Strasser spent a decade as an independent trainer and consultant in the field of project management. During his tenure, he also served as project manager for software projects in the construction industry and provided scheduling and cost management support for large-scale construction projects. At TPG, he applies his expertise in product development and consulting services for international clients. His special focus is on PMO, project portfolios, hybrid project management, and resource management. For many years now, he has shared his knowledge through presentations, seminars, articles, and webinars.
Achim Schmidt-Sibeth
Senior Marketing Manager
After earning his engineering degree in environmental technology, he gained many years of experience in project management through his work at an engineering office, an equipment manufacturer, and a multimedia agency. Achim Schmidt-Sibeth and his team have been responsible for content marketing and communication at TPG The Project Group for many years now.
Read more about Achim Schmidt-Sibeth on LinkedIn.
