ChatPGT, NLP, and Project Management

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The launch of ChatGPT has created a buzz and a sense of interest among various sections of society with heightened curiosity about its utility and implications. It can be used for a wide range of purposes including (but not limited to) customer experience journey improvements, sales cycle improvements, and content creation and management. Hence, expectations are that the applications of ChatGPT will be diverse and for all sorts of things. Not surprisingly, there was a report that a Colombian judge consulted ChatGPT for preparing a ruling in a case.

It opens up opportunities to explore the utility of ChatGPT for project management as well. Some of the potential avenues are knowledge augmentation, problem resolutions (where possible by gaining clarity and answers to some questions), sparking creative thoughts, and learning from human-machine interaction for developing this relationship further to improve project efficiencies.

What is more exciting is the fact that the developments in ChatGPT have brought the spotlight on the use of Natural Language Processing (NLP), one of the most widely used applications of artificial intelligence (AI). To put things in perspective, NLP is defined as “any computer-based algorithm that handles, augments, and transforms natural language so that it can be represented for computation“ (Niimi, 2021, p.2150). NLP is used for applications in healthcare, education, and banking, just to name a few. NLP solutions come in various forms such as chatbots, callbots, and smart assistants.

The growing dependence on NLP and AI-based solutions (e.g., customer experience improvements) for day-to-day business and organisational management (including project management) shows the promise and role that such solutions could and will play in the future. Specifically, in relation to project management, it is predicted that by 2030, “80% of project management tasks will be run by AI, powered by big data, machine learning (ML), and natural language processing” (Nieto-Rodrigue & Vargas, 2023). If these predictions are to come true, this sounds staggering and deserves careful consideration.

There is no doubt that technology will play a significant role and shape the future. One may like it or not, but that is what it is. This raises the question of how NLP and AI are being used and can be used for project management. Or, in other words, what are the current uses of NLP and AI in project management and how can NLP and AI be used to improve project efficiency? To answer the question, below we have looked at some of the current uses as well as potential areas of NLP use for project management.

Current Uses of NLP and AI for project-based work

NLP can process and recognise the spoken words (language), grammar of language (syntactic analysis), meaning of words (semantic analysis), and context of utterance (pragmatics), which can be very useful for project-based work as project management is used in every context and culture. As such, NLP and AI-driven solutions are being used for a variety of purposes in project management. These include, planning and forecasting, task automation, risk management, monitoring and control, and coordination (Yang, 2019).

For project-based task automation, such as organising standup meetings during agile project delivery, Geekbot and Standuply are some of the examples of AI-driven solutions. Yang, (2019) also highlights the application of NLP and AI for scanning historical data to predict project completion times and expected budget estimates for the projects. Other applications include JIRA for tracking work completion, Aptage to provide action insights for project delivery, and a project management digital assistant (Schmelzer, 2019; These few examples are just the tip of the iceberg in terms of the variety and breadth of use of NLP and AI-driven solutions for project management. It leads to the question, “What’s in the store?” which we discuss below.

Future and possible uses of NLP and AI in PM

Certainly, the future is bright for the use of NLP and AI-driven solutions for project-based work. For sure, a large number of thoughts and predictions exist on this strand. Nieto-Rodriguez and Vargas, (2023) highlight six areas that will be affected the most due to the use of NLP and AI-driven solutions for project-based work. These are:

  • better selection and prioritization (for identifying and selecting the best projects and establishing a balanced portfolio);
  • support for the project management office (for capability development, monitoring, and compliance)
  • improved, faster project definition, planning, and reporting (for scoping, risk management, etc.)
  • virtual project assistants (for helping users become more efficient in their work performance)
  • advanced testing systems and software (for defect identification and deploying self-correcting processes)
  • a new role for the project manager (teaching project professionals, including project managers and educators, how to use AI)

In addition, NLP and AI will also be very helpful in human performance modelling to model project staff cognition and behaviours to suggest improvements in their performance and overall efficiency, reduce human errors, and improve overall satisfaction for the client. Schmelzer, (2019) argued the role of predictive analytics in enhancing project efficiencies, which is also highlighted in the six areas of impact discussed above. Predictive analytics appears to be a game changer for understanding anomalies and predicting patterns in order to make informed decisions. Given the high rates of project failures, the above-limited discussion points to the utility of AI to reduce such failures, and this could be just the beginning of what NLP and AI could offer.


Despite the fast-growing evolution of project management concept (see more at:, there is no doubt that the current knowledge on the use of NLP and AI in project management is focused on “low-hanging fruits” (i.e., to highlight the positive outlook). It requires further exploration of the potentially negative consequences of the use of NLP and AI for project planning and delivery. What it means is that to further develop understanding and leverage NLP and AI for project management, we must focus on both the beneficence and nonmaleficence contexts of their use. Only then will we be able to strike a reasonable balance.

However, as a starter, it is critical to capitalise on the positives and work to correct the negative consequences. With that in mind, we have looked at the potential of NLP and AI for project work. Needless to say, the discussion focused on highlighting the significant opportunities and the future outlook is intended to stimulate thought and is not conclusive or exhaustive, but with the hope of advancing further work in this domain.

Note: This article was previously published on 




Jiwat Ram
Jiwat Ram
Jiwat is currently working as a Professor in Project management at Excelia Business School France. He did his Ph.D. from the University of South Australia and MBA in International Business from AIT Thailand. Jiwat has over 20 years experience of working in industry across banking, construction, service, and education sectors in an international setting. For the last more than 10 years, Jiwat has worked in academia teaching at Executive Education, Master’s, and bachelor’s levels. His teaching includes courses on Artificial Intelligence, project management, management, and research methodology. Jiwat has published his research work in top-tier, high-impact factor journals including the International Journal of Production Economics, the International Journal of Project Management, Computers in Human Behaviour, the Journal of Global Information Management, and Enterprise Information Systems, among others. Combining academic and non-academic work, he has published over 100 articles in journals, conferences and industry outlets. His published work has been well received and four of his published papers have ranked in the Top 25 most downloaded papers from ScienceDirect. His two papers have been ranked in the Top 25 Most Cited articles as well. Jiwat’s research is focused on the impacts of technologies such as Social Media, Big Data, and Artificial Intelligence on businesses and society. Jiwat likes to understand how we can leverage upon the use of innovative technologies for business growth and productivity. Jiwat regularly contributes towards the development of new thought and ideas in business and technology management. As such, he has a growing portfolio of publications on some of the contemporary issues in the management of projects and organizations. Jiwat also publishes his work on social media platform Linkedin to connect and reach out to other industry professionals. His work has received a good following with a significant number of posts cited as reaching top 1% engagement on Linkedin. Jiwat’s content on LinkedIn can be accessed at: #ideannovation_jiwat Please feel free to connect with Jiwat on LinkedIn by clicking on the Icon above.

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