TORONTO—Integrating generative artificial intelligence with digital twin technology will transform the manufacturing industry, according to a recent report by Info-Tech Research Group.

“Digital twins have long been recognized for their potential to revolutionize predictive maintenance and streamline processes,” says Shreyas Shukla, principal research director at Info-Tech Research Group. “When combined with generative AI, the possibilities for the manufacturing industry expand exponentially.

“However, many manufacturers worldwide continue to grapple with the challenges of Industry 4.0 and the remnants of pandemic-era supply chain disruptions,” claims Shukla. “The fusion of Gen AI and digital twins promises not only to optimize current manufacturing processes, but also to usher in a new era of design, simulation and real-time predictive analysis."

According to Shukla, AI will play a significant role in manufacturing over the next decade, potentially outpacing the impact of automation in the past. He believes that manufacturers prioritizing AI investments now can significantly expand their offerings and capabilities, leading to increased market presence, revenue growth and improved customer satisfaction. This strategic move is seen as crucial for staying competitive.

The transformative potential of integrating Gen AI with digital twins indicates how this combination can propel manufacturers from reactive to proactive modes of operation. “This shift can help organizations achieve greater efficiency, sustainability and resilience in the hyper-competitive and constantly changing global market,” says Shukla.

Info-Tech’s report identifies several obstacles facing the manufacturing sector, including the significant compatibility of integrating new technologies with existing systems. It also reveals there is a lack of skilled professionals who are well-versed in both the manufacturing industry and advanced technologies, including AI.

However, Shukla points out that there’s a pressing need for a comprehensive understanding and ethical use of AI to ensure integrity in decision-making processes within manufacturing operations.