2026 Agenda

• Stability as the Foundation for Excellence: How operational, workforce, and supply chain stability enable continuous improvement and long-term strategic planning.

• The Toyota Model for Workforce Loyalty: Exploring long-term employment practices that drive commitment, innovation, and efficiency—contrasting against the volatility seen in high-churn industries.

• The Human Element in a Digital Age: Balancing automation and robotics with the irreplaceable value of human insight, creativity, and problem-solving.

• Resilience Through Engagement: Understanding how job security, empowerment, and emotional well-being influence workforce performance amid widespread layoffs and technological disruption.

• Looking Ahead: How Toyota is preparing for the next era of manufacturing—combining human ingenuity with responsible technology integration to sustain competitiveness and innovation.

Artificial intelligence is ushering in a new age of highly automated, self-optimizing semiconductor factories, where tools communicate with each other and with enterprise systems to continuously refine process conditions, improve yield, and reduce variability, with minimal human interaction, so that our teams can focus on the more technical aspects of our business. As we enter the angstrom era and process flows become increasingly complex, we must incorporate a higher level of AI-driven process development, to generate recipes that use fewer materials and less energy, while simultaneously enhancing manufacturing efficiency through reduced cycle times. AI-augmented design tools will further reduce the time from design to manufacturing, creating chips that are inherently more manufacturable, higher quality, and better tuned for AI workloads. In parallel, we must incorporate AI to architect anti-fragile supply chains that become more resilient under stress by dynamically rerouting demand, qualifying alternate high-quality materials, and introducing new suppliers, while proactively managing constrained material availability, globally dispersed supply sources, extended design-to-revenue timelines, and variable material quality. While AI will become increasingly critical to run our factories and supply chain efficiently and sustainably, we cannot lose sight of the human side of our business – our reliance on the people who drive the innovations that lead to next-generation technology and applications. As we continue to integrate AI-driven capabilities and cultural transformation into our way of working, we have an opportunity to enable an intelligent, adaptive manufacturing ecosystem that will not only overcome current structural challenges, but also scale the reliable, sustainable production of future generations of AI-enabling chips.

• From Business Offender to Competitive Advantage: Four years ago, Mondelez North America’s supply chain was constraining business growth: service was unstable, costs were rising, and teams were trapped in reactive firefighting across a complex network. Roger will share how, in just four years, this supply chain was transformed into a reliable engine for growth and profitability.
• From Traditional to High Performance Culture: The keynote will share how new leadership confronted reality, reset the operating model, upgraded talent, rebuilt core fundamentals, and aligned supply chain goals to business needs. A strong focus on accountability, capability building, and talent elevation enabled a shift from instability to disciplined execution.
• From Impossible to Best in Class: You will hear from Roger an inspiring yet practical story of what it really took to fix a complex network (22 plants, 25 external manufacturing sites and 54 logistics facilities across USA, Canada & Northern Mexico) and to instill the Team a continuous improvement high performance mindset – while building strong foundations that will drive the 11,000 supply chain associates towards Industry Best in Class by 2030.

Ford Director of Manufacturing Tom Bradley will share how Ford improves manufacturing quality with Machine Integrated Learning and Optimization (MILO) — an AI-powered anomaly detection framework developed in-house and informed by more that 120 years of manufacturing expertise.

 MILO leverages existing test-station waveform data and machine learning to proactively detect quality issues that traditional methods can miss — without adding hardware, changing test stations or increasing cycle time. The result is faster containment, reduced waste and better quality for customers.

 Bradley will also highlight real-world results from Ford’s engines and  transmissions operations, including significant reductions in stop-ship events and millions of dollars in verified cost avoidance, and discuss how MILO is scaling across plants, processes and product lines to deliver practical, measurable quality improvements.