August 15, 2025: By Peter McAliney (Professional and Executive Education at Rutgers), Michael Marzano (St. Josephs University), and Mike Bruening (Sacred Heart University): Advanced Artificial Intelligence (AI) applications offer transformative potential to streamline Six Sigma projects by automating template population, data analysis, and output generation. Traditional Six Sigma methodologies, while effective, can become burdened by the time and organizational reach associated with extensive data inputs and analytical processes, leading to resource-intensive operations and extended project timelines. AI-driven solutions can significantly alleviate these bottlenecks, enabling rapid, cursory project execution for a subset of the organization’s portfolio, freeing organizational resources to focus on comprehensive analyses and more complex initiatives with high-yielding ROIs.

This paper explores how integrating AI into Six Sigma frameworks enhances operational efficiency, reduces cycle times, and ensures data handling and analysis consistency. By automating routine processes such as data entry, data scrubbing, statistical analyses, and preliminary reporting, organizations can improve accuracy and allocate more time to strategic, in-depth Six Sigma projects. The paper will discuss critical AI technologies, including natural language processing, machine learning algorithms, and generative and agentic AI, and their role in augmenting traditional Six Sigma tools in the DMAIC framework (Define, Measure, Analyze, Improve, Control).

Download the paper here.