Wedoany.com Report on Mar 18th, Artificial intelligence is reshaping the plastics manufacturing industry, driving it towards sustainable development. Conor Carlin, former President of the Society of Plastics Engineers and President of Clefs Consulting, points out that the current applications involve narrow AI, such as large language models trained on specific domains and computer vision systems, rather than general artificial intelligence. 
Carlin emphasizes that one of the direct applications of AI in plastics manufacturing is knowledge preservation and access. He explains, "By capturing the tacit expertise that is about to be lost with retiring technicians and making that knowledge available to operators when they need it, this can be achieved through platforms specifically designed for plastics processing."
Manufacturers have invested heavily in equipping production lines with sensors and data loggers, but most of the data is underutilized. Carlin notes, "AI can bridge the gap between raw production data and actionable intelligence." However, he also mentions three major challenges for AI application in manufacturing: trust, change management, and data quality.
The plastics industry also faces increasing regulatory pressure, especially in Europe. Carlin describes the Packaging and Packaging Waste Regulation as a significant regulatory intervention in packaging design in Europe and stresses the importance of treating compliance as a design input. In North America, legislation such as California's SB 54 also presents challenges.
Structural labor challenges are particularly severe in North America, with Carlin pointing to the European apprenticeship model as a potential solution. In terms of material supply, both North America and Europe have been exposed due to reliance on global supply chains and are investing in domestic or nearshoring alternatives.
Global manufacturers are exploring the best strategies for integrating AI into their operations. A Cisco report shows that 59% of surveyed manufacturers have implemented AI at scale. The global AI market in manufacturing is expected to grow from $34 billion in 2025 to $155 billion in 2030.
Samuel Pasquier, Head of Product Management for Industrial IoT Networking at Cisco, states, "AI is driving significant improvements in manufacturing productivity, quality, and resilience. This is no longer a pilot project; it's how work is beginning to get done."
Carlin emphasizes that AI plays an important role in addressing sustainability challenges and enhancing competitiveness, but it needs to be positioned as a complement to organizational investment. He explains, "It works best when the technology is placed within a broader commitment to workforce development."
The maturation of advanced recycling technologies is another trend in plastics manufacturing. Carlin notes that PET depolymerization has proven more scalable, while pyrolysis of mixed plastics still faces economic challenges. The concept of a circular economy provides a framework for aligning sustainability with competitiveness.
Carlin concludes by emphasizing that the industry now has more tools at its disposal than ever before, including AI-assisted knowledge management and clearer regulatory signals. How these tools are used depends on leadership and will.
