Скачать или смотреть The Real Reason AI Success Stories Are Rare in Industrial Automation

In this clip, the conversation takes a candid look at why meaningful AI success stories in industrial automation and manufacturing remain so difficult to find. Despite widespread interest and heavy investment in industrial AI platforms, copilots, and digital twins, many real world manufacturing environments are still missing the most basic data foundations required to make these tools work. As discussed here, a large percentage of manufacturers still rely on paper, clipboards, and manual processes for production data collection, making advanced AI applications unrealistic before core systems are in place.

The discussion touches on industry studies suggesting extremely high failure rates for enterprise AI initiatives and explores whether successful implementations are rare, immature, or simply not being shared due to competitive advantage. Referencing examples such as Siemens, Nvidia, and Microsoft industrial initiatives, the clip highlights a recurring pattern seen across manufacturers of all sizes. Ambition often runs far ahead of reality. Before AI can deliver value on the plant floor, manufacturers need historians, MES platforms, reliable data pipelines, and strong change management practices.

‪@VladRomanov89‬ and Dave also explore why change management remains one of the biggest barriers to adoption. Even well designed tools struggle when operators view them as disruptive or threatening rather than supportive. If you work in industrial automation, manufacturing operations, engineering leadership, or digital transformation, this clip offers a grounded and honest perspective on why AI adoption is slower than expected and what foundational steps still need to happen first.