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As generative artificial intelligence (AI) is expected to continue growing and playing a role in consumer experiences and data, learn how you as a manufacturer can prepare for changes it will bring to your processes.

According to a Euromonitor 2024 consumer trends report, 49% of professionals expect generative artificial intelligence (AI) to improve customer experiences by analyzing customer data to create more intelligent product development, virtual assistance, shopping experiences and more.  

As a manufacturer, it’s important for you to consider how AI may play a role in your processes to impact your end-use product performance, too. Learn how generative AI is anticipated to impact packaging, mobility and construction markets individually and collectively.  


How AI Helps Your Market Specifically 

How Generative AI is Expected to Impact Packaging Markets 

From flexible packaging to labels, all packaging markets are anticipated to evolve with changes that generative AI will bring to the value chain.  

Elevated Product Design & Development  

As consumers implement AI into their retail user experiences such as ecommerce shopping, it’s possible the demands for enhanced ecommerce methods will change as well so that packages are delivered faster for a wide variety of food and non-food products without sacrificing durability.  

AI can help enable you to address demands that are specific to your end-use products. 

  • Enhanced testing: AI algorithms can help you design packaging with integrated sensors or Radio Frequency Identification (RFID) technology, allowing for real-time tracking, temperature monitoring and authentication, enhancing product safety and traceability to meet ecommerce delivery demands. Similarly, AI can enable development of films with embedded sensors to enhance overall functionality in applications. 
  • Design optimization: By analyzing consumer preferences, market trends and branding strategies, AI algorithms can contribute to creating innovative and visually appealing designs for labels and other packaging components that will resonate with consumers. AI’s ability to also track this data will help you pinpoint strategies that are unique and attractive to your specific audience, allowing your end-use product to stand out amongst competitors. Further, by analyzing data on material properties, cost and environmental impact, AI algorithms can suggest optimal material combinations that will enhance performance, reduce costs and meet sustainability goals. 
  • Customization and personalization: AI allows for the customization of end-use products by leveraging algorithms and data analysis to tailor products to individual preferences or behaviors, helping you meet specific client or consumer requirements for personalized designs, sizes or performance features.   
Improved Manufacturing 

By analyzing data from production lines, AI can identify holdups in process methods and recommend improvements to enhance overall manufacturing efficiency. This also can result in cost savings and increased productivity. In particular, it contributes to: 

  • Optimized supply chain: AI also can optimize your supply chain by predicting demand, handling inventory and streamlining production schedules. This can help with reduced lead times, better resource utilization and improved overall supply chain efficiency. 
  • Enhanced quality control: AI-powered systems can enhance quality control in flexible packaging manufacturing. Using computer vision and machine learning, AI-powered systems can identify defects, ensure print quality, and detect inconsistencies, contributing to the production of high-quality materials. Additionally, AI can predict when machinery might require maintenance, helping you reduce slow-downs and extending the equipment’s lifespan.  
Increased Sustainability 

AI can contribute to helping you increase sustainable practices and find ways to make your end-use packaging more environmentally friendly.  

  • Waste: AI can help you streamline package cutting patterns to minimize material waste during production and utilize resources more efficiently. Similarly, it can optimize production schedules and machinery operation that results in less energy usage, reducing overall carbon emissions. 
  • Life cycle assessments: AI can perform life cycle assessments (LCAs) to evaluate the environmental impact of different packaging options. This includes considering factors such as raw material extraction, manufacturing, transportation, usage and end-of-life scenarios. With this information, LCAs can guide your decisions toward more sustainable packaging choices. 
  • Recyclable designs: By considering recycling infrastructure and processes, AI algorithms can generate designs that facilitate the recycling of packaging materials, making it more likely for the packaging to be reused in the circular economy. This includes generating suggestions for compatible materials, package structures that are easy to dismantle, informative recycling labels and recycling procedures that align with local recycling guidelines. 

How Generative AI is Expected to Impact Mobility Markets 

AI is anticipated to play a role in the end-user experience for automotive, road transportation, railway and marine applications. Along with utilizing AI in your own manufacturing processes, this may also mean you should consider implementing AI platforms into your product designs to enhance the overall experience for the consumer.  

Improved Safety 

AI algorithms analyze performance data, infrastructure and other key safety factors that can generate information to enhance overall safety for drivers. In particular, it can help with: 

  • Infrastructure and route planning: AI can optimize routes and schedules that increase safety for markets including marine and railway. By considering factors such as weather conditions, fuel efficiency and maintenance scheduling, AI has the potential to help these products reduce accidents. Further, AI can help optimize traffic flow and reduce congestion on roads. Traffic management systems powered by AI can analyze real-time data to suggest alternative routes, manage traffic signals, and improve overall transportation efficiency. 
  • Simulation and testing: AI can facilitate virtual simulations and testing of vehicles and transportation systems. This accelerates the design and testing processes for you, reducing error likelihood and development costs and increasing overall speed to market. 
Increased Sustainability 

As demand increases from both consumers and government leaders for vehicles that improve our environmental footprint, AI can serve as a reliable tool to help you reach your sustainable design goals faster.  

  • Reduced emissions: AI can identify ways that may help you design cleaner, more fuel-efficient engines to reduce emissions across mobility markets. This includes providing material recommendations as well as logistical and transportation routes.  
  • Energy efficiency: AI can present algorithms that analyze historical and real-time data to identify opportunities for energy optimization. This may be helpful particularly for designing electric vehicles (EV) or streamlining energy usage in propulsion systems for railway and marine applications.  
  • Lightweighting materials: By providing material analysis and simulation, AI can predict how different material sand designs will behave under various conditions, helping you identify the right structures to reduce weight in your application. Lightweighting can contribute to improved fuel efficiencies to reduce carbon emissions.  

How Generative AI is Expected to Impact Industrial Construction Markets 

AI is expected to have an impact on industrial construction material manufacturing with the potential to move assembly processes along faster and improve installation and end-user experience.  

Enhanced Design Optimization 

By analyzing various parameters and constraints, AI algorithms can generate designs that are both structurally sound and more efficient in terms of material usage and performance. In particular, it can also help with: 

  • Material development: AI algorithms can explore a wide range of material compositions, considering properties including strength, flexibility and resistance to chemicals, moisture and extreme temperatures. This can help you create customized materials based on specific project requirements. This level of customization from AI can lead to more efficient and effective construction processes, as materials are tailored to meet the exact needs of a particular project. 
  • Regulatory compliance: AI systems can assist in monitoring and ensuring compliance with industry regulations and standards, reducing the risk of potential legal issues and ensuring the safety and quality of construction materials. 
Improved Processing 

AI can supply features that will help you streamline your assembly steps and move construction materials through your production line at a faster, more efficient rate that without it. AI also helps identify inefficiencies, suggest improvements, and enhance overall manufacturing efficiency through data analysis, which can result in cost savings. Additionally, it helps with: 

  • Quality control: AI-powered systems can recognize defects or irregularities in construction materials during the manufacturing process. This can prevent damaged end-use products from being delivered to end users or construction sites and further maintain overall customer satisfaction with the decrease of error likelihood.  
  • Process automation: Utilizing AI-powered robots and automation systems can help you increase production speeds and accuracy with repetitive, labor-intensive tasks, including material handling, packaging and transporting goods.  
Increased Sustainability 

By addressing both your processes and product materials, AI can help you improve sustainability and contribute to reducing the overall environmental footprint of a residential or commercial building project. Specifically, it can: 

  • Optimize building systems: AI can optimize building systems within manufacturing facilities, including lighting, HVAC and other systems to reduce energy consumption and improve overall facility efficiency. In addition to energy consumption monitoring mentioned above, AI-driven occupancy sensors can optimize energy usage in your plant by adjusting lighting, heating and cooling based on real-time occupancy data.  

How AI Helps Markets Collectively 

While you may be trying to implement AI features directly to your specific application needs, AI can provide these benefits across all industry markets:  

  • Supply chain optimization: By predicting demand, managing inventory and recommending efficient sourcing strategies, you can use AI to reduce lead times, improve cost-effectiveness and improve your overall supply chain efficiencies. 
  • Predictive maintenance: You can use AI algorithms to predict when machinery in your operation is due for potential maintenance, helping you schedule repairs at times that will not pause production for long. This can help you reduce overall downtime and extend your equipment’s lifespan. 
  • Improved energy consumption: AI can monitor energy usage in manufacturing facilities and recommend opportunities for improved efficiencies. This includes assessing machinery operation and adjusting production schedules to reduce peak energy demand. Further, AI can suggest methods to integrate renewable energy sources into your processes, helping you transition to a cleaner, most sustainable facility. 

Bostik’s Adhesives and Sealants Can Help You Meet Demands as AI Evolves 

As the adhesives solutions segment of Arkema, Bostik is committed to providing you with options that can help you address growing, changing market demands. We know AI is important to consider not only with the full scope of your manufacturing processes and end-use products, but also within individual components such as your adhesives and sealants. At Bostik, we are vertically integrated to help you address specific performance, processing or sustainability requirements wherever you are located. Further, we offer a large portfolio with technical support to help you customize formulations to your specific needs.  

Are you ready to utilize AI to address market demands and see how it can benefit you? Contact a Bostik expert to learn how our adhesive and sealant solutions can also help you further improve your end-use performance, production efficiencies and sustainability and work well with your AI tools. 


©2024 Bostik, Inc. All Rights Reserved

All information contained herein is believed to be accurate as of the date of publication, is provided “as-is” and is subject to change without notice. To review our full U.S. Legal Disclaimer, visit:

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