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8/1/2025
How Can AI Help Improve Lean Six Sigma Projects?
Bisk Amplified
August 1, 2025
As with all advances in technology, the uses of artificial intelligence (AI) systems haven’t all become known in just a few months. As with everything from smartphones to driver assistance systems, the many uses of AI are slowly becoming apparent over time. One area that is starting to feel the impact is Lean Six Sigma.
Lean Six Sigma practitioners are already getting a significant boost from AI's ability to analyze large datasets and recognize patterns. Its use may potentially revolutionize the way companies implement Lean Six Sigma principles.
The Harvard Business Review (HBR) reported that the change is inevitable because AI tools can perform tasks faster and less expensively than humans alone. The biggest issue for managers is finding a way to integrate advanced technology with the expertise of human experts. AI “will never fully replace people - and that poses management challenges,” according to HBR.
Lean Six Sigma combines the practices of two methodologies. Lean focuses on eliminating waste - non-value-added actions and materials - to speed up processes and reduce costs. Six Sigma focuses on reducing variation within processes that lead to errors in products and services. By integrating the two approaches, Lean Six Sigma aims to streamline operations, enhance product quality and improve overall business efficiency. The goal is to create higher customer satisfaction and better bottom-line results.
Both methodologies take a data-driven approach to solving problems and optimizing business processes. Lean Six Sigma projects require a deep understanding of process flow and statistical analysis, and they typically involve certified practitioners (Yellow Belts, Green Belts, Black Belts, Master Black Belts) who are trained extensively in these methodologies. One goal of Lean Six Sigma is to create a culture of continuous improvement within an organization.
All this requires human expertise. But HBR reported that the belief that humans alone can accomplish these goals “seems increasingly out of date,” noting that Johnson & Johnson already has an “Intelligent Automation” initiative that applies automation and AI tools to automate processes and enhance employees’ productivity. They note that Voya Financial is also combining traditional process improvement with AI and automation tools.
Currently, companies are looking to combine the expertise of Lean Six Sigma practitioners with the benefits of AI. Some of the ways this can happen include the following.
Lean Six Sigma projects require data collection and analysis to identify the root causes of problems. Traditionally, this process requires significant human effort and is prone to errors. AI changes the game by automating data analysis. Machine learning algorithms quickly process large datasets, identify trends and even predict future occurrences. This capability speeds up the data analysis phase and enhances the accuracy of the insights gained.
For instance, in manufacturing, AI can continuously monitor production lines to detect real-time deviations from the norm. By applying predictive analytics, AI can forecast potential failures or quality issues before they occur, allowing preemptive action that minimizes downtime and improves product quality.
AI can simulate different process changes and predict outcomes. By using AI-driven simulation models, businesses can visualize potential impacts of process adjustments without disrupting ongoing operations. This approach helps in making data-backed decisions.
Furthermore, AI can optimize workflows by suggesting the most efficient sequence of operations or by automating routine tasks. This optimization often leads to significant reductions in process time and cost.
Decision-making in Lean Six Sigma projects can greatly benefit from AI's capability to provide comprehensive, data-driven insights. AI systems can integrate data from multiple sources and quickly deliver analyses that would take much longer for human teams to produce. This rapid, holistic view supports more informed, timely decision-making in critical project phases.
AI tools also minimize biases that typically affect human judgments. By relying on data and patterns, rather than assumptions or experiences, decisions become more objective and effective.
In industries where equipment maintenance is crucial, such as manufacturing and transportation, predictive maintenance facilitated by AI can lead to substantial cost savings and efficiency improvements. AI algorithms analyze historical data, operational conditions and other relevant factors to predict when maintenance is needed. This predictive capability ensures maintenance is done only when necessary, rather than following a fixed schedule. It also reduces the likelihood of unexpected equipment failures and the costs associated with excessive maintenance
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AI's integration into Lean Six Sigma projects is not just a trend but a transformative shift that enhances the efficiency and effectiveness of these initiatives.
One of the biggest obstacles to adopting AI in Lean Six Sigma is the lack of clarity on how it will be used, and concerns that it will replace humans. For example, HBR reported that since AI can do calculations necessary to many of the tools and techniques used in Lean Six Sigma, experts in the field may resist adopting it.
However, most companies still know that humans are needed to guide these projects and use Lean Six Sigma tools in a way that best aligns with company goals. The challenge will be getting employees to buy into the use of AI tools in supporting Lean Six Sigma projects.
“AI can revolutionize process improvement and dramatically reduce labor-intensive tasks employed in traditional methods,” HBR reported. “To realize the technology’s potential, however, leaders will need to reorient front line workers to these new tools.”
