Integrated Project Management Company and Hitachi hosted a group of food and beverage industry leaders for an off-the-record, peer-driven discussion about shared operating challenges. The goal was to exchange practical experiences, identify what is working (and what isn’t), and surface frameworks leaders can take back to their organizations.
Across the discussions, participants consistently emphasized AI, but they stressed the need to start with the problem, rather than a technology solution. Investments in automation, digital tools, or AI stall when companies aren’t clear about the process or outcome they need to improve. Another theme was people as a constraint: adoption, behavior change, trust, and visible champions matter more than technical capability in driving sustained value.
The full day of conversation centered on these four topics:
Supply Chain Resilience & Transparency
Executives said supply chains are more complex due to unpredictable demand, faster channel shifts, and growing regulatory requirements. Also, traditional S&OP models and cost-focused KPIs are struggling to keep pace with volatility. Participants agreed that resilience should be measured by speed of sensing, decision-making, and recovery, supported by deeper partnerships and improved data transparency across the supply chain.
Addressing the Labor Shortage Through Automation
Labor shortages driven by attrition, retirement, and the low interest in factory work are persistent, not cyclical. In response, automation is increasingly necessary, but success is uneven. One of the challenges is having the necessary on-site technical resources to keep the automated equipment up and running. The group discussed starting with narrow problems (often where turnover and safety incidents are high), delivering phased wins, and clearly explaining the “why” behind automation to drive adoption.
Driving AI & Digital Transformation
Most organizations have experimented with AI, but few have scaled beyond pilots. The current use cases are primarily to enhance efficiency rather than to make decisions or improve processes. Several participants cited data quality and context gaps. Indeed, AI value depends on clearly defined decisions, trustworthy data, and internal capability to sustain models.
Ensuring Food Safety & Protecting Brand Trust
Food safety remains the frontline of consumer and customer trust, and quality, safety, brand reputation, and profitability are inseparable. The group agreed that a quality-first mindset ultimately protects profitability. Trusted partners, aligned testing methods, and thoughtful use of in-process data can prevent issues before they escalate.
June 24, 2026