Categories: Artificial Intelligence
Project managers are inundated with training and education opportunities. As AI becomes more common in how projects are managed, project managers must ensure they have the right skills to be successful.
1) Fundamentals of machine learning (ML) and natural language processing (NLP). Whether the AI-based solution is provided by a vendor or created internally by programmers, the project manager should understand the fundamental capability of these two components. Machine learning is the engine that drives most but not all AI solutions. A software program uses loops or iterations to refine the correlation performed by regression analysis. Hyperparameters are set before the program begins and include items such as the number of iterations and the number of layers in the neural network. It is essential to be able to ask relevant questions, such as the number of datasets used to make the prediction.
NLP uses numerous techniques to interpret language and generate a response. Generative AI, such as ChatGPT, depends on a corpus or body of work to provide useful responses since the data that is accessed significantly impacts the output. A project manager understands project information and needs to be involved in how project data is applied to Generative AI tools.
2) Data management. AI requires data, and, in most situations, relevant data will be more important than volumes of data. Data wrangling and feature engineering are necessary for proper input. An information technology (IT) person and a data scientist will not understand the nuances of project data. The project manager is the best person to identify the correct data, relevant data fields, and amount of data required for AI tools.
3) Math and statistics. AI is based on math. The algorithms use regression analysis to produce results. Statistics is an important component for understanding and interpreting the output. A high-level degree in math is not required. However, project managers must become familiar with managing different aspects of statistical analysis. What is an outlier? Can the outlier be ignored, or is it the start of a new trend?
Project managers have a critical role in the adoption and successful application of AI to improve project performance. There are new areas where training and additional knowledge are essential for this process. Collaborating with AI tools is an opportunity for project managers to demonstrate their value to project stakeholders. Improving these three skills should help you improve your value to any organization.




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