Artificial intelligence (AI) is no longer a foreign concept to the world. The recent viral Studio Ghibli AI trend is just one example of how generative AI (gen AI) is capturing global attention. As AI transforms our everyday lives, it’s also shaking up the packaging industry. You’ve probably seen TikTok videos of designers using gen AI tools to create packaging designs from scratch in seconds.
But the revolution extends far beyond using AI for packaging design. Machine learning applications now span the entire custom packaging ecosystem, dramatically boosting efficiency and reducing costs across the board. In this blog, we’ll explore how AI is already being used in the industry and the exciting possibilities it holds for the future.
Why AI in Packaging Matters
AI adoption in the packaging industry is accelerating. A recent industry survey found that 77% of packaging companies have moderate to strong intentions to use gen AI in the near future. Already, one in four surveyed companies has either launched or is actively developing AI-powered tools, and more than 60% of them report that AI’s impact has exceeded their expectations.
The reason is clear—AI enhances efficiency and productivity by minimizing human error and reducing waste. In custom packaging, AI unlocks endless possibilities for innovation and personalization, elevating both branding and customer experience. It also plays a crucial role in sustainability, helping businesses identify eco-friendly materials, optimize procurement, and streamline logistics to cut down on waste and environmental impact.
How AI is Transforming the Custom Packaging Process
1. Personalized Consultation
Many packaging companies now use AI-powered chatbots to instantly reply to customer inquiries. These intelligent assistants recommend packaging options based on product requirements, budget constraints, and the client’s sustainability goals.
While sales representatives still handle follow-up communications, they can now leverage AI tools to create quotes much faster. These tools analyze historical sales data and real-time market trends to provide accurate cost estimates in minutes, instead of hours or days.
As AI continues to evolve, it’s not far-fetched to envision the entire quotation and ordering process can be fully automated.AI could go beyond simple recommendations, leveraging customer purchase history and industry trends to suggest innovative packaging solutions before businesses even realize they need them.
2. Efficient Packaging Design
Packaging designers are now using gen AI tools like Midjourney to create refined, high-quality packaging artwork in seconds. Meanwhile, platforms like Pacdora can instantly generate structural designs, including dielines and 3D mockups, further streamlining the design process.
Beyond aesthetics, AI-powered packaging design tools use advanced algorithms to optimize material usage, durability, and sustainability. Designers simply enter their requirements—like how much protection the product needs, weight restrictions, or sustainability goals—and the AI suggests designs that meet all these needs.
Soon, we’ll see machine learning take packaging design to the next level. By analyzing consumer behavior and emerging market trends, AI could generate design options that stand out on store shelves and strengthen brand identity. Major companies like L’Oréal and AptarGroup are already using AI models to predict how well different packaging designs will perform with customers.
Source: Monolith AI
3. Simulated Prototyping
AI is transforming the prototyping phase by making it faster, smarter, and more cost-effective. Companies now use AI-driven simulations to test how packaging performs in real-world conditions. These smart tools evaluate usability, durability, and product protection without creating physical prototypes. Some innovative firms have even developed VR software, helping businesses visualize how the packaging will look on store shelves in a virtual environment.
Looking ahead, AI simulation tools will be able to generate thousands of prototype variations at once. This would help businesses find the perfect balance between functionality and material efficiency. Automated AI feedback loops could also predict structural weaknesses and refine designs recurrently, so as to save time, reduce waste, and speed up innovation.
Source: Esko
4. Optimized Procurement
Packaging procurement is a complex and ever-changing process, but AI is making it smarter and more efficient. It can analyze supplier performance, material costs, and market conditions all at once, helping businesses make data-driven decisions. Through predictive analytics, businesses can also buy materials more efficiently and avoid supply chain disruptions.
In the future, AI forecasting will help companies in cost saving by predicting when material prices will change and how market demand might shift. Some forward-thinking businesses are already working on AI blockchain systems to make the entire supply chain more transparent and traceable. These systems provide real-time, tamper-proof data that ensures procurement processes remain fair, secure, and trustworthy for all stakeholders.
5. Streamlined Manufacturing
In manufacturing, AI’s potential seems unlimited. Machine learning algorithms improve print quality, color accuracy, and production speeds, boosting efficiency while greatly reducing human errors. AI is also transforming quality control. Computer vision inspection systems can spot packaging defects instantly, which helps in waste reduction and avoids customer complaints.
Another major advancement is AI-based predictive maintenance. These intelligent systems use sensors and real-time data to monitor manufacturing equipment and can predict potential problems before machines break down, minimizing costly production interruptions.
Additionally, many manufacturers now use RFID technology to track materials and equipment in real-time, making operations more efficient. As AI integration advances, future smart factories will utilize the Internet of Things (IoT) to automatically adjust production schedules based on consumer demand, creating a more agile and responsive manufacturing ecosystem.
6. Smart Logistics
AI solutions open up new opportunities in logistics. Warehousing, order fulfillment, and delivery are faster and more efficient than ever. In warehouses, AI-powered sorting and picking systems streamline operations, making sure packaging reaches customers on time.
For delivery, AI-driven route optimization is already helping logistics companies reduce transit times, cut costs, and lower carbon emissions. Soon, we’ll likely see widespread adoption of fully automated deliveries using drones and self-driving trucks.
Amazon, for example, has been expanding its drone delivery service since its launch in the U.S. in 2022. These drones use advanced algorithms to detect and avoid obstacles like people, animals, and aircraft, ensuring safe and precise deliveries. As AI, IoT, and cognitive computing continue to evolve, automated deliveries are poised to become the norm across various industries and regions.
7. Enhanced Packaging Recycling
Recycling has always been a critical focus in the packaging industry. Companies committed to sustainability typically implement packaging recycling programs to minimize waste. Now, AI-powered robotics are taking recycling efficiency to the next level.
Some forward-thinking businesses now employ AI-powered robots to enhance the recycling process. These robots use optical sensors and machine learning algorithms to rapidly identify packaging types and sort recyclable materials, even when items appear in different shapes, colors, or conditions than what they’ve been trained on. This improved accuracy and speed reduces contamination in recycling streams, improving efficiency.
Looking to the future, smart packaging embedded with RFID tags or sensors could provide real-time data on material composition and recyclability. AI could also help develop closed-loop recycling systems, where packaging materials are continuously repurposed into new products, achieving a more sustainable, waste-free cycle.
Challenges & Concerns of AI in Packaging
Despite AI’s promising opportunities, the packaging industry faces several important challenges and ethical concerns to address before fully committing to this technology:
- Data Privacy: AI thrives on data, but how can companies ensure they handle it responsibly and securely? Striking the right balance between AI-driven insights and data protection is crucial.
- AI Bias & Decision-Making: As AI takes on more decision-making roles, how do we ensure fairness and transparency? If an AI-driven system produces biased or flawed results, who is held accountable?
- Potential Copyright and IP Infringement: Gen AI creates designs by drawing inspiration online or emulating art styles from well-known IP, like Studio Ghibli. Can AI-generated designs be considered original, or do they infringe on the work of established brands and artists? The legal landscape surrounding AI-created art remains highly debated.
- Job Displacement Concerns: While AI enhances efficiency, it also threatens traditional human labor. How can businesses ensure that skilled workers are not left behind? Striking a balance between automation benefits and workforce sustainability will be key.
Embrace the AI-Driven Future of Packaging
With AI advancing at an unprecedented pace, a future where custom packaging is designed, produced, and delivered with minimal human intervention is no longer a distant vision, but a fast-becoming reality. AI-powered factories, intelligent automation, and data-driven decision-making will reshape the industry, unlocking new levels of efficiency, customization, and sustainability.
To stay ahead, packaging businesses must embrace innovation while upholding ethical responsibility. The industry’s transformation is not a question of if, but when—and those who adapt early will lead the way.
The future of packaging is AI-driven. Will you seize the opportunity or risk being left behind? Now is the time to innovate, evolve, and redefine what’s possible.
