Artificial Intelligence as Your Next Project Team Member

About the author:

Fredrik Kockum has a master’s degree in project management and has recently completed his dissertation: “The role of AI in Project Management”. He is dedicated to continuously improving his knowledge of AI and project management, as well as improving the awareness of the topic within the project community. Fredrik is a Prince2 and AgilePM practitioner, and is currently applying for a PhD at University of Southampton. He is open for a discussion on the topic and if you would like to discuss it further, feel free to contact him through LinkedIn.

There is no question that Artificial Intelligence (AI) has gained major attention in recent years. Business leaders and researchers around the world generally agree on the role AI will have in the fourth industrial revolution. It’s fascinating to imagine a future scenario where AI is predicted to have the similar impact on societies as electricity once had. AI has moved from being primarily a research field within computer science and data analytics, to entering professions such as health care, finance and customer service. This blog post emphasizes the opportunities which AI brings to project organisations and encourages the project management profession to make AI part of the industry’s DNA.

AI and project management have received more attention recently. Project Management Institute (PMI) has put the spotlight on the topic through its Pulse of the Profession “The Future of Work”, while Association for Project Management (APM) spreads awareness on the topic through its Projecting the Future reports. PricewaterhouseCoopers (PwC) has presented their suggested Evolution of AI in Project Management, which brings high-level insights into the current situation and suggested future development.

Sustainable development of AI means to have a collaborate mindset. This is to be done through collaboration between AI-systems and project teams. The topic was well covered in a piece in Harvard Business Review by Wilson and Daughtry: “Collaborative Intelligence: Humans and AI Are Joining Forces” and Kolbjornsrud, Amico and Thomas: “How Artificial Intelligence Will Redefine Management”. An environment where AI-systems and humans benefit from each other is referred to as “Collaborative Intelligence” or “Hybrid Intelligence”. Humans and AI-systems need to build on each other and improve continuously.

In a collaborative environment, it is suggested treating intelligent machines as colleagues. By extending the cognitive ability among humans, AI can be used when handling complexity and be used to assist project teams in dealing with vast amount of data. An AI-model is only as good as the data input, which is based on the human ability to critically analyse the available data in order to decide whether the data is suited for the purpose.

In order to develop a sustainable human-AI symbiosis in project management, project managers and project practitioners need to ask themselves two questions:

  1. What AI-skills and knowledge do I and other project managers currently possess?

Individual project managers, industry organisations and business organisations need to self-assess their current knowledge and engage the project community to invest in personal development and training. By utilizing the available reports by industry organisations as an indication of the current state, knowledge within the project community can be seen.

Project managers are then able to determine how their knowledge is standing in comparison with their peers. The capability among project managers to combine a holistic view with the knowledge of knowing when and how to apply AI-systems is growing in value.

When an overall understanding of what AI is capable of and the under-pinning AI-principles are understood, it is time to move to question number two.

  1. What problem do we want to solve?

On an organisational level, senior management needs to narrow down where in the project process AI can be used. Further on, there are two directions for organisations to move forward: Do we want to cut costs by replacing project team members with AI-models? Or do we want to create a skilled community of project managers and utilize a collaborative environment between AI and project team members?

This blog post argues for the second alternative. As project teams become more exposed to AI-models, it is suggested to introduce AI as part of the project team.

AI may have two roles in a project team; firstly, as an independent party working parallel with the human project team and reinforces human estimations and predictions. Secondly, by working side by side in close collaboration. These two roles will overrun and essentially contribute to enhancing the decision-making process. In this chosen scenario, the only way forward is to picture AI-models as a collaborative colleague.

In order to integrate AI-systems into project teams, a wide change management process in project management best practice is necessary, where the adoption process is key for individuals to trust the estimations made by AI-systems. The adoption process needs to be continuous and begins with the understanding of the data input. Critically assessing whether the data is appropriate and suitable for the purpose, builds a foundation of trust among the project team.

The previous mentioned role, of AI-models working in parallel with human project teams, is to be used as a supplement to traditional project management techniques. Researchers Wauters and Vanhoucke, showed a combination of following AI-models: decision trees, random forest, bagging, boosting and support vector machines to make more accurate estimations of Earned Value Management. The same researchers have also shown positive results of project durations by using nearest neighbor-algorithm. These are clear examples of project management techniques being used in unconventional ways with AI-algorithms.

The analytical excellence of AI is significant, however the intuitive ability of human decision-makers managing uncertain situations remains unaffected. In a project environment where the AI-adoption process has created a successful symbiosis of AI-models and project teams, time will be freed up for project managers to improve human elements in the project process.

A collaborative exchange between AI-systems and human project managers need to utilize the natural capabilities among computers and humans. As project management is a data-rich profession, computers’ capability to assess great amount of data volumes has the ability to assist project managers who are exposed to extensive amount of information.

AI-models are able to provide correct information at the right time. This information can justify program and project managers decisions in any part of the project process. On the other hand, project managers are able to maintain human elements when time is freed up from autonomous project tasks. This time can be used for motivation of project team members, elements of leadership, personal development and building relationships with project stakeholders.

There are many unsubstantiated opinions regarding AI and future technologies. Predictions of X amount of increase in revenue from improved efficiency with AI and claims of X number of job losses when employees are to be replaced by AI are common. It is important to see through the vast number of hyped articles and form a pragmatic view of the entrance of AI and related technologies of the fourth industrial revolution. By learning from previous industrial revolutions, the most adaptive parties will see most success. Individuals and organisations need to focus on training and spreading awareness of AI.

The understanding that AI is not a “plug-in” for the IT-department is essential when project organisations are identifying problems where AI can be implemented. Individual project managers outside the inner circle of computers science and data analytics need to be exposed to AI in order to improve the AI-adoption process. In order to introduce AI as a collaborate party of project teams, continuous self-assessments are necessary on all levels of the project community.

 

 

References

APM, 2019. Projecting The Future: A big conversation about the future of the project profession. Available from: https://www.apm.org.uk/media/36360/projecting_the_future_msgd_final.pdf

Kolbjornsrud, V., R. Amico and R. Thomas, 2016. How Artificial Intelligence Will Redefine Management. Harvard Business Review. Available from: https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management

PMI, 2019. AI Innovators: Cracking the Code on Project Performance. Available from: https://www.pmi.org/-/media/pmi/documents/public/pdf/learning/thought-leadership/pulse/ai-innovators-cracking-the-code-project-performance.pdf?sc_lang_temp=en

Wauters, M. and M. Vanhoucke, 2016. A comparative study of Artificial Intelligence methods for project duration forecasting. Expert Systems with Applications, 46, 249-261

Wauters, M. and M. Vanhoucke, 2017. A Nearest Neighbour extension to project duration forecasting with Artificial Intelligence. European Journal of Operational Research, 259(3), 1097-1111

Wilson, J. and P. Daughetry, 2018. Collaborative Intelligence: Humans and AI Are Joining Forces. Business Harvard Review. Available from:

https://hbr.org/2018/07/collaborative-intelligence-humans-and-ai-are-joining-forces

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