Project Management in Wonderland
SECOND EDITION
By Suchitra Veera
Dallas, Texas, USA
1. Introduction
Artificial intelligence (AI) is becoming the center piece of products and services in today’s business environment. After the introduction of Generative AI tools like Chat GPT over the past year this technology is beginning to play a key role in the commercialization and growing popularity of AI. With advances in machine learning (ML) as well as large language models (LLMs) such as ChatGPT, AI can help to improve business processes and team efficiency and enhance business and project decision-making. According to a 2023 annual global survey on project management, 82% of senior leaders indicated that AI will impact projects while 91% believe that AI will impact the project management profession (PMI, 2023b).
Technology has been an essential component of business innovation – be it the utilization of technology as part of the innovation process, or as a component of the final product or service itself. The advances in digital technology over the past decade with powerful digital platforms have been disruptive and transformational for innovation and entrepreneurship, leading to the formation of new types of business models, and new types of products/services and customer experiences (Nambisan et al., 2019). The types of functionalities that are provided by emerging technologies and particularly those offered through AI can be a source of great discovery and amazement. It has given rise to various types of applications that were previously unheard of or even imaginable, giving the impression of being magical and somewhat mysterious in its behavior and capabilities.
The next sections of this paper cover the topics of the strategic and business implications of AI followed by an analysis of the use of AI for project management practices, and a set of metrics to measure successful AI implementation. The final sections of the paper include a description of the barriers to successful implementation and required approaches to increase the likelihood of project success with an understanding and knowledge of AI and its capabilities.
2. The Emergence of AI
A one-hundred-year study of AI which was launched in 2014 described AI as “Technology capable of actions and behaviors requiring intelligence when done by humans” (PANEL, 2016). More recently, a report published by the Project Management Institute (PMI) described AI as “the theory and development of computers that can approximate the functions and capabilities of human intelligence” (PMI, 2023a). ML is a subfield of AI, which involves the use of algorithms that enable machines to “learn and adapt without following instructions” (PMI, 2023a). Information is extracted from raw data and represented in a model, which is then used to make inferences about new data that is fed into the model. ML systems built in this manner can apply the knowledge and patterns learned from processing large volumes of data sets which are used to train these models. Based on such training, the functionality of facial recognition, speech recognition, object recognition, language translation and many others can be used to build a wide range of products and services serving many industries and customer segments.
“The digital wave, including the Internet of things, big data, cloud computing platforms, and other cyber-physical systems, has fundamentally altered how equipment is built and maintained and, consequently, how organizations are structured, and how they collaborate and think”(Tronvoll, et al., 2020). With improved wireless networks, the popularity of smartphones and tablets, and the widespread use of social media, today, many business-to-business (B2B) and business-to-consumer (B2C) products and services are tightly integrated with technology. This is evident in clothes that have wearables embedded in them, services that depend on real-time streaming data, home equipment that have smart speakers and temperature gauges, medical devices, and many other examples that generate tremendous volumes of data in a business as well as personal context. It is possible to combine such newly available data obtained from a wide variety of sources including customer relationship management (CRM) systems, manufacturing systems, and internet-of-things (IoT) devices. When ML algorithms are applied to such data integrated from multiple sources, it can provide many opportunities to predict and potentially explain consumer behavior as well as industrial systems processes. ML can be used as a key tool for decision making by businesses focused on marketing, social media, customer service, driverless cars, and many more.
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Editor’s note: Second Editions are previously published papers that have continued relevance in today’s project management world, or which were originally published in conference proceedings or in a language other than English. Original publication acknowledged; authors retain copyright. This paper was originally presented at the 16th UT Dallas PM Symposium in May 2024. It is republished here with the permission of the author and conference organizers.
How to cite this paper: Veera, S. (2024). Through the looking glass of AI – Project Management in Wonderland; presented at the 16th University of Texas at Dallas Project Management Symposium in Richardson, TX, USA in May 2024; republished in the PM World Journal, Vol. XIII, Issue VII, July. Available online at https://pmworldlibrary.net/wp-content/uploads/2024/07/pmwj143-Jul2024-Veera-through-the-looking-glass-of-AI.pdf
About the Author
Dr. Suchitra Veera
Dallas, Texas, USA
Dr. Suchitra Veera has over 20 years of experience in the consumer goods, retail, financial, travel/transportation, and healthcare industries leading as product manager and leading projects and programs. She has accomplishments in developing and implementing systems integration and software product development, digital transformation, data analytics, data science and engineering. She also has over 15 years of experience in training, coaching and teaching Project Management, Systems and Business courses.
She was volunteer corporate trainer at a Fortune 100 company teaching Successful Project Management and IT Service Operations, and a training facilitator for the Project Management Institute (PMI) Cincinnati Chapter and Education Director for PMI Dallas Chapter. She holds an MBA from the University of Maryland, a master’s degree from University of Virginia, and master’s and doctoral degree from Henley Business School, UK. In addition to Project Management Professional (PMP)® certification, she also holds ASQ certifications of CMQ/OE, CSSGB and CSQE, ITIL, New Product Development Professional (NPDP), Certified ScrumMaster (CSM), and SAFe Agilist (SA) certifications.
She can be contacted at suchitraveera@gmail.com