For decades, navigating economic implications in packaging meant optimizing supply chains, predicting commodity prices, and forecasting demand with established models. Your career leverage came from deep historical data analysis and incremental efficiency gains, a predictable path built on known variables and established relationships.
The fact of the matter is, the old models can't keep up with the volatility AI introduces to demand, supply, and material innovation. What's really happening is that AI-driven market shifts are creating unpredictable ripple effects across the entire packaging value chain, making your traditional forecasting tools feel like a rearview mirror.
The new model demands you move beyond static reports to dynamic, AI-informed scenario planning that can adapt in real-time. This means leveraging AI not just for data analysis, but for predictive modeling that anticipates shifts in consumer behavior, material costs, and regulatory impacts before they hit.
You have a choice: either you learn to direct AI to build new economic insights and competitive advantage in packaging, or you wait for the old market to come back, which it won't. The people who go first will build the next ladder, period full stop.