Where Human Ingenuity Meets Machine Intelligence: The Future of Continuous Improvement

"It all boils down to people. People have to review data, input data, solve problems, and make improvement." Jamie Bonini's words during our inaugural Lean Into AI webinar capture a fundamental truth that many organizations miss in their rush toward artificial intelligence. As President of Toyota Production System Support Center, Bonini knows that sustainable transformation requires more than technology—it demands engaged human problem-solvers working in harmony with intelligent systems.

Optimization Before Automation 

Last week's launch of the Lean Into AI series marked a pivotal moment for the continuous improvement community. For the first time, seven leading operational excellence organizations united under the Future of People at Work initiative to tackle the question that keeps leaders awake: How do we integrate AI without losing the human-centered foundation that makes lean thinking so powerful? [read more at link...]

The 87% Failure Rate Has a Solution

Professor Ali Shakouri from Purdue dropped a sobering statistic: 87% of AI projects fail to achieve ROI. But rather than accepting this as inevitable, Shakouri and his team have been systematically addressing the root causes through hands-on work with 27 manufacturers since 2018. Their findings reveal something profound—AI needs what lean practitioners have been building for decades: standardized processes, engaged workers, and systematic problem-solving capabilities.

During the webinar, Bonini illustrated this through a compelling manufacturing scenario. Picture a 100-person casting operation facing a 10% price reduction demand while operating on 5% margins. The traditional lean transformation would create continuous flow, reduce changeover from 20 minutes to under one minute, and redeploy workers as problem-solving team leaders. But here's where it gets interesting: with this foundation in place, AI can take performance to unprecedented levels.

By adding low-cost sensors and machine learning algorithms, the same operation can now predict internal casting voids without destructive testing and monitor 20+ equipment parameters instead of just three or four. This isn't automation replacing human judgment—it's technology amplifying human problem-solving capability. As Bonini explained, "We can put a plasma screen on top of that piece of equipment... and actually say, almost like statistical process control on steroids."

Democratizing AI for the 98%

What makes the Future of People at Work initiative revolutionary isn't just the technology—it's the collaborative approach to deployment. Small and medium manufacturers, representing 98% of U.S. manufacturing, typically lack the resources for dedicated AI departments. Shakouri's cohort model addresses this gap through collective learning while preserving competitive advantages.

Companies facing similar challenges—whether CNC machining, seam welding, or plasma cutting—join cohorts that meet every 30 days to share learnings. Using privacy-preserving platforms, they benefit from collective data insights without exposing proprietary information. One participant, Kirby Risk, doubled productivity in a single year despite workforce attrition challenges. This wasn't achieved through massive technology investments but through systematic application of real-time feedback loops and engaged operator participation.

The journey follows a clear progression: from descriptive (establishing good data) to diagnostic (understanding patterns) to predictive (anticipating problems) to prescriptive (optimizing decisions). Most organizations currently sit between descriptive and diagnostic stages—and that's perfectly fine. As Steve Pereira, our series MC, emphasized, success comes from understanding where you are and taking appropriately sized steps forward.

The Abundance Mindset: Yes, And...

Perhaps the most powerful insight from the session was the shift from scarcity to abundance thinking. Traditional lean sometimes gets trapped in minimization—cutting costs, reducing waste, eliminating variation. While these remain important, AI opens new possibilities for expansion and enhancement.

Consider the challenge of capturing tacit knowledge—the experiential wisdom that takes years to develop. That maintenance expert who can diagnose equipment problems by sound, the operator who senses quality issues before they manifest—their knowledge has been nearly impossible to scale. Now, AI coaching tools being developed could provide "good or good-plus" problem-solving support at 11 PM when the expert coach is unavailable. This isn't about replacing masters but democratizing access to their expertise, and allowing those experts to scale their impact.

Building Tomorrow's Problem-Solvers Today

The collaboration between TSSC, Purdue, and partner organizations (GBMP, LEI, Shingo Institute, Catalysis, Central Coast Lean, Ohio State's COE) represents more than institutional cooperation—it's a blueprint for workforce development. As Shakouri noted, "AI enables people on the floor to access data and manipulate data in a way that they could not do before."

This transformation requires new organizational structures. Traditional IT departments focused on security and infrastructure must collaborate with operations teams who understand process nuances. Operators become data annotators, teaching AI systems to recognize anomalies. Team leaders evolve from firefighters to predictive problem-solvers. The entire organization shifts from reactive to proactive, from intuition-based to data-informed intuition.

Your Next Steps in the Journey

The message is clear: start small, learn fast, scale wisely. Whether you're a small manufacturer wondering how to begin or a lean practitioner questioning AI's role, the path forward involves experimentation, not revolution. As Bonini advised, "Start with a small project, get some experience, and you'll be much wiser to figure out where to go."

You can watch the complete webinar at this link

The Future of People at Work initiative continues monthly, bringing together practitioners, researchers, and leaders to shape how operational excellence evolves with artificial intelligence. This isn't about choosing between human creativity and machine intelligence—it's about achieving what neither could accomplish alone.

Join the movement:

• Next Lean Into AI session: [Registration details coming soon]

• Monthly FPW virtual gatherings: forms.gle/yXPbCXURdfvYtjmn9

• Follow Future of People at Work: linkedin.com/company/future-people-work/

• Learn more: fpwork.org

This post was developed through collaboration between Future of People at Work leadership and synthesized with Claude.AI assistance. It represents ongoing work by the Future of People at Work initiative, a collaboration of Toyota Production System Support Center (TSSC), GBMP Consulting Group, Central Coast Lean, The Ohio State University Center for Operational Excellence, Shingo Institute, Lean Enterprise Institute, and Catalysis.