Gen AI transforms manufacturing, but…

New data that shows manufacturing organisations worldwide are increasingly turning to GenAI to establish smart factories, spur innovation, improve productivity, build resilience and gain competitive advantage. However, there are also significant challenges related to workforce and infrastructure readiness as, well as ethical frameworks for governance.

The findings are contained in an NTT Data report, Feet on the Floor, Eyes on AI: Do you have a plan or a problem?, based on a survey of more than 500 manufacturing leaders and decision makers in 34 countries.

Key findings include:

• 95% of respondents said GenAI is already directly improving efficiency and bottom-line performance.
• 94% expect the integration of Internet of Things (i.e., IoT/edge) data into GenAI models will significantly improve the accuracy and relevance of AI-generated outputs.
• 91% say combining digital twins and GenAI will improve both physical asset performance and supply chain resilience.
• Respondents said their most frequent use cases are supply chain and inventory management; knowledge management; quality control; research and development; and process automation.

“AI is streamlining processes and redefining what’s possible across the entire manufacturing value chain, from supply chain predictions to quality control,” said Prasoon Saxena, co-lead for products and industries at NTT Data. “GenAI can help organisations achieve flexibility in fast-changing business environments, especially in the face of uncertain tariff policies worldwide.”

Challenges to Success

Satisfaction with AI initiatives has surged over the past year, yet manufacturers still face significant challenges that include:

• Infrastructure: 92% of manufacturers said old technologies hinder vital initiatives, but less than half have conducted a full infrastructure readiness assessment.
• Complementary technologies: 94% expect the integration of Internet of Things (i.e., IoT/edge) data into GenAI models will significantly improve the accuracy and relevance of AI-generated outputs, yet not all are confident in their ability to complete such integrations.
• Responsible frameworks: While ethical AI is on the radar, only 47% of manufacturing leaders strongly agree their organisation follows a robust framework that balances risk with value creation.
• Workforce readiness: Two-thirds of manufacturers say their employees lack the necessary skills to use GenAI effectively, creating functional and operational disadvantages and risks.
• Data Management: Just 41% of manufacturers strongly agree they have enough data storage and processing capabilities to support their GenAI workload needs, which will limit success.

“The most successful manufacturing organisations have already integrated GenAI into essential operations,” Saxena said. “Companies failing to plan, deploy and govern GenAI strategically will not only have a problem, they may be planning to fail.”

• Visit the NTT Data website to learn more.