of its ability to quickly interpret vast amounts of data. Using a process known as machine learning, generative AI such as ChatGPT can make future predictions based on the analyzed data. AI allows this interpretation to be more real-time and also incorporates new sources of information that the business may not have. One source of information is the AI’s own experience with similar project management questions asked by users. Over time, it is able to develop a more accurate response.

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The use of newer generative AI allows easier use of preexisting machine learning models by allowing a wider range of inputs and outputs. This is easier to understand with an example of the opposite: weather forecasting. While there has been some recent addition of AI, weather forecasting traditionally uses models based on mathematics. Certain atmospheric conditions are likely to produce certain weather conditions. The input the computer needs to calculate is not a format that is easily understandable and analyzable to humans. AI instead uses natural language queries, so in that case one could ask "Look at the past (1 week) and current weather conditions for White River Junction, VT. What will happen next week?". The same can be applied to business analysis. For example, one can forecast future outcome metrics like estimated completion time. AI can use data from the project and other projects to predict whether the estimated completion time is still reasonable and offer suggestions to remediate the issue if not.