Abstract

In terms of project planning, the use of AI tool has several advantages compared to traditional approaches. A project plan generated using an AI model can provide a detailed coverage of project outcomes, a comprehensive breakdown of both functional and non-functional requirements, a simple schedule with limited number of activities which can facilitate a quick initial planning, a cost estimate that emphasizes regular monitoring and adjustments to account for the dynamic nature of project expenditures, a plan that includes manpower, equipment, and associated costs, a strategy that emphasizes user expectations (i.e., testing, code reviews, quality metrics), a plan that puts equal importance on the various stakeholders, a communications plan that prioritizes quality communication throughout the project life cycle, and a comprehensive approach to risk management with end-to-end planning in mind (Barcaui & Monat, 2023). An AI-assisted project management approach can provide support in decision making by providing descriptive, predictive, and prescriptive analytics particularly for agile projects (Dam et al., 2019). For example, AI techniques (i.e., machine learning) can augment basic analytics such as burndown charts and sprint reports to diagnose why something happened in a particular project. Deep learning can also be used to estimate the size of user stories based on previous estimates (Choetkiertikul et al., 2019). AI can also process large amounts of historical data and use these to forecast delay risks and sprint delivery risks (Choetkiertikul et al., 2019; Choetkiertikul et al., 2018). In a survey involving project management experts (Fridgeirsson et al., 2023), an overwhelming majority of the respondents indicated that AI has a significant positive effect on the schedule management plan and scope baseline, cost management estimates and estimations of resources based on market conditions, resource cost rates, exchange rates, inflation, probability and impact matrix, development of risk management plan, and setting of risk thresholds.

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tpp1337

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