
Achieving operational excellence with AI
Quick Answer
Lean Six Sigma and BPM frameworks have revolutionized operational excellence by introducing structured methodologies for managing chaotic processes, emphasizing statistical rigor and end-to-end workflow mapping.
Quick Take
These approaches provide organizations with repeatable strategies to enhance quality control and streamline operations across departments.
Key Points
- Lean Six Sigma focuses on statistical rigor and quality control.
- BPM creates comprehensive maps for workflow across departments.
- Both frameworks aim to bring order to chaotic operational processes.
- Organizations can achieve repeatable strategies for operational improvement.
- These methodologies enhance efficiency and quality in business operations.
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As AI reshapes how work gets done, organizations with strong process frameworks are best positioned to lead and maintain operational rigor at scale.
July 2, 2026
Frameworks like Lean Six Sigma and business process management (BPM) first gained traction because they promised clarity in the chaos—a structured way to bring order to messy, sprawling operations. Lean Six Sigma emphasized statistical rigor and quality control; BPM created end-to-end maps of how work should flow across departments. Both offered a repeatable way to embed habits of measurement, analysis, and accountability into day-to-day company culture.

But today, those time-tested playbooks are evolving as companies seek to embed AI into established process excellence methodologies. By some estimates, the market for AI-powered process optimization is projected to exceed $113 billion within the next decade. In one study, a full 88% of business leaders anticipated increasing investments into AI-infused process intelligence in the next 12 to 18 months.

Yet without the right foundations, many of those investments may not fully deliver on their potential. Companies that already operate with discipline have an edge. They can channel new tools into proven systems rather than bolting them onto shaky foundations. Organizations with mature process disciplines are also better positioned to translate AI ambition into real outcomes, as they are already accustomed to data-driven decision-making and process discipline—precisely the cultural foundation AI systems need to deliver value.
Simply put: AI can accelerate process excellence, but existing process excellence is what makes AI truly impactful. Technology and process are no longer separate levers, and only organizations that pull them together stand to realize the full value of both.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
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