Title: Paige Morse Discusses How AI is Used to Achieve ESG Goals and the Circular Economy Resource URL: https://www.youtube.com/watch?v=WXIO8wM8SIA Publication Date: 2024-03-18 Format Type: Podcast Reading Time: 28 minutes Contributors: Amanda Kuhl;Paige Morse; Source: ESG Decoded Podcast Keywords: [Sustainability, Artificial Intelligence, Circular Economy, Advanced Recycling, Industrial AI] Job Profiles: Chief Sustainability Officer (CSO);Environmental Consultant;ESG Analyst;Artificial Intelligence Engineer;Sustainability Manager; Synopsis: In this podcast, host Amanda Kuhl speaks with Dr. Paige Marie Morse about how industrial AI enhances sustainability efforts in the chemical and manufacturing industries. They explore AI's role in optimizing operations, reducing waste, and advancing the circular economy. Takeaways: [The Alliance to End Plastic Waste is an example of collaboration across the value chain, bringing together brands, waste management companies, and plastic producers to tackle global plastic waste challenges., Design for recycling is a critical strategy to ensure that products are easier to recycle, reducing the complexity of sorting and processing waste., In regions like Asia, where plastic production and demand are highest, efforts focus on cleaning up waste while also addressing the lack of established recycling infrastructure., AI and digital solutions, like energy dashboards and advanced recycling technologies, are becoming key enablers in industries like chemical production, driving efficiency and sustainability., At events like Optimize 2021, sharing success stories and innovations globally helps accelerate the adoption of sustainable practices, with a strong emphasis on circular economy models and AI-driven solutions.] Summary: The podcast episode of ESG Decoded features a conversation between Amanda Hsieh and Paige Marie Morse, focusing on the intersection of artificial intelligence (AI) and sustainability. Paige, who is the Enterprise Director of Sustainability at Aspen Technology, explains how AI is being utilized in industrial settings to enhance operational efficiency and sustainability. The discussion highlights the role of AI in optimizing processes, reducing energy consumption, and minimizing waste in industries such as oil, gas, and chemicals. The conversation also delves into the concept of the circular economy and the challenges of recycling plastics, emphasizing the importance of collaboration across the value chain. The episode underscores the potential of AI to drive innovation and efficiency in achieving long-term sustainability goals. Content: ## ESG Decoded Podcast Overview ESG Decoded is a podcast produced by a leading global advisory firm to deliver actionable insights on business innovation and sustainability. Hosted by experienced consultants, each episode features in-depth conversations with industry leaders, unpacking the complexities, risks, and opportunities embedded in environmental, social, and governance (ESG) initiatives. --- ## Introduction This episode explores the intersection of artificial intelligence (AI) and sustainability in industrial manufacturing. Our guest is the Industry Marketing Director for Chemicals at a major technology provider that specializes in embedding AI in oil and gas, chemical, and engineering operations. The discussion examines how AI drives safety, reduces environmental impact, and accelerates progress toward long-term sustainability goals. --- ## Defining Industrial AI for ESG ### Context and Capabilities Industrial AI refers to software solutions that leverage machine learning to optimize process operations within the physical constraints of refineries, petrochemical plants, and plastics units. By analyzing historical performance data, these tools identify patterns, anticipate anomalies, and recommend adjustments to enhance safety, operational efficiency, and sustainability metrics. ### Safety and Reliability • Early warnings and anomaly detection prevent incidents that could harm operators or the environment. • Smoother, more stable operations reduce the likelihood of safety-related shutdowns and unplanned emissions. --- ## Operational Optimization and Continuous Improvement ### Beyond Financial Gains Traditionally, process-control software prioritized throughput, yield, and margin. Today, the same platforms are reconfigured to minimize energy consumption, reduce waste between production streams, and lower greenhouse gas (GHG) emissions—all while maintaining or improving profitability. ### Accelerating Data-Driven Decisions • AI processes large volumes of sensor data more quickly and deeply than manual analysis. • Recommendations guide operators—especially those early in their careers—toward best practices, smoothing the learning curve and preserving institutional knowledge. --- ## Sustainability Framework in Three Pillars 1. **Resource Efficiency (Short-Term Assets)** • Optimize energy and feedstock use. • Reduce waste streams and water consumption. 2. **Strategic Transition (2030–2050 Targets)** • Explore alternative energy carriers such as hydrogen or ammonia. • Reimagine process flows to support net-zero objectives and new value chains. 3. **Circular Economy (Product Lifecycle Redesign)** • Design products for disassembly and reuse. • Develop closed-loop systems to recover and repurpose materials indefinitely. --- ## The Circular Economy and Advanced Recycling ### Design for Disassembly Major consumer-facing brands and chemical producers are collaborating to simplify packaging and reduce material complexity—enabling easier sorting, recycling, and reuse. ### Advanced (Chemical) Recycling Moving beyond mechanical recycling (melting and remolding), advanced recycling breaks plastics down to their molecular building blocks. Emerging technologies convert mixed or colored polymers into feedstock for new plastics or energy, closing the loop on material use. ### Role of Technology and AI • Simulation and in silico experimentation accelerate scale-up of recycling processes. • Predictive models guide unit design and operational parameters to maximize yield and minimize cost. --- ## Alliance to End Plastic Waste This global coalition, headquartered in Asia, unites plastics producers, consumer brands, and waste-management firms to tackle plastic leakage into the environment. Initiatives include: • Funding for startup innovations in advanced recycling. • Community cleanup and waste-collection projects, particularly in emerging-market regions. • Design-for-recycling guidelines to simplify material recovery. Collaboration across the value chain remains critical to solving the plastic-waste challenge. --- ## Optimize 2021 Conference Highlights Optimize 2021, the biennial virtual event hosted by the technology provider, showcased global success stories in digital transformation and sustainability: • Heat-exchanger AI model used by a Middle Eastern chemical company to reduce energy consumption across refinery and petrochemical units. • Circular-economy case studies from leading firms in Asia, Latin America, and Europe developing advanced recycling applications. • Live sessions and replays (available through June) offering practical guidance on energy dashboards, emissions tracking, and resource-optimization metrics. --- ## Conclusion The integration of industrial AI with ESG strategies is accelerating progress toward safer, more efficient, and environmentally responsible manufacturing. Success depends on cross-sector collaboration—from technology providers and operating companies to consumer brands and local communities. By sharing data, co-innovating on process design, and investing in next-generation recycling, businesses can drive long-term value while protecting people and the planet. To continue the conversation or explore partnership opportunities, connect with the podcast hosts and contributors via professional networking platforms. Until the next episode, apply these insights to advance your organization’s sustainability journey.