The Value of Digital Twins in Modern Manufacturing
SOUTHWEST Session: Most manufacturers begin their AI journey with high expectations, yet research shows that 95 percent of GenAI projects fail to create real business value. A common trap is the shiny object syndrome, where leaders and empowered employees chase trendy tools that look impressive but do little to address core operational challenges. This is why only 5 percent of enterprise-built AI tools ever make it into production. The companies that succeed take a different path. They delve into the business itself, uncovering where AI can make the most significant difference. Predictive maintenance that prevents costly downtime, quality control that reduces waste, and supply chain optimization that improves resilience are just a few areas where measurable impact becomes possible. What often separates success from failure is expertise. Internal teams, no matter how skilled, can be limited by organizational bias, resource gaps, and familiar ways of thinking. That is why internal builds succeed only a third of the time. Third-party AI experts, on the other hand, bring fresh perspectives that identify blind spots, challenge assumptions, and apply proven frameworks that raise the success rate to nearly 70 percent. With the proper guidance, AI stops being an expensive experiment and becomes a powerful, revenue-generating asset. For manufacturers, this shift marks the difference between falling behind and building a sustainable competitive edge.