Generative AI (Gen AI) is no longer a concept of the future—it is increasingly shaping industries, creating new possibilities for efficiency, innovation, and growth.
In sectors such as finance and healthcare, AI adoption has accelerated rapidly over the past decade. Historically, however, the packaging and paper industry has been slower to embrace digital transformation, often sticking to conventional methods.
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Now, the conversation is changing: Gen AI promises to transform operations across the packaging and paper value chain, from research and development to customer engagement.
According to industry analysts, the potential value added by Gen AI across industries could reach trillions of dollars annually. While this might sound abstract, its impact on the paper and packaging sector is tangible.
Companies are already exploring AI-driven design tools, automated supply chain optimisation, and data-driven marketing strategies. As adoption grows, the benefits are expected to include faster innovation cycles, lower costs, improved sustainability, and enhanced customer experiences.
This article explores the opportunities, applications, and challenges of generative AI in the packaging and paper industry, drawing on insights from surveys of industry executives and case studies from leading firms.
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By GlobalDataGenerative AI and the packaging sector: unlocking latent potential
The packaging and paper industry has traditionally lagged behind sectors such as technology or pharmaceuticals in digital adoption. Production processes often involve complex supply chains, high capital expenditure, and regulatory considerations.
These factors have made companies cautious about investing in cutting-edge digital tools, including AI.
However, recent surveys of industry executives suggest that attitudes are shifting. Around 95% of respondents believe that their companies should invest in Gen AI, and roughly three-quarters report a strong intention to implement AI-driven solutions in the near term.
Despite this enthusiasm, adoption is still in its early stages: only about 24% of companies have launched or are actively developing Gen AI initiatives.
The reason for this cautious approach is clear. Executives report a lack of deep understanding of Gen AI’s potential, limited access to clean and structured data, and uncertainty about the technology’s integration with existing systems.
Yet, early adopters are seeing encouraging results. More than 60% of companies that have implemented Gen AI report that its impact meets or exceeds their expectations, particularly in areas such as operational efficiency, product development, and customer engagement.
One area where Gen AI is particularly valuable is idea generation. By analysing patents, consumer feedback, and competitor products, AI can help packaging designers rapidly develop new concepts, test materials, and simulate production processes before committing to physical prototypes.
This accelerates innovation while reducing costs and waste—a critical advantage in an industry increasingly focused on sustainability.
Applications across the value chain: from design to customer engagement
Generative AI has applications at virtually every stage of the packaging and paper value chain. Its capabilities are especially suited to tasks that involve large volumes of unstructured data, pattern recognition, and content creation.
Research and development
Innovation is a key driver of growth in the packaging and paper sector, particularly as companies respond to the demand for sustainable and recyclable materials. Gen AI can assist in R&D by:
- Conducting competitive patent analysis and generating new IP ideas.
- Accelerating idea-to-visualisation workflows, enabling designers to quickly see concepts in 3D or virtual environments.
- Facilitating rapid consumer testing and iteration by analysing feedback and suggesting modifications.
- Streamlining field testing and material validation, reducing time-to-market for new products.
A practical example comes from a global plastics packaging firm that has integrated Gen AI into its design studio. The tool helps designers produce user-centric packaging solutions that meet environmental compliance standards, allowing faster iteration and fewer costly prototypes.
Commercial operations
Sales and marketing functions are expected to be among the most significantly impacted by Gen AI. Executives report that AI tools can:
- Optimise lead generation and prioritisation through predictive analytics.
- Enhance marketing efficiency with automated A/B testing, campaign personalisation, and omnichannel content creation.
- Support sales teams in real time with AI-driven advisers, providing tailored recommendations to improve conversion rates.
- Improve pricing strategies by combining internal cost data with market intelligence and consumer behaviour insights.
These applications not only boost revenue but also allow companies to engage more effectively with clients, providing personalised experiences that were previously difficult to scale.
Supply chain, manufacturing, and procurement
Operational efficiency is another area where Gen AI can deliver tangible value. AI algorithms can simulate warehouse layouts, optimise inventory levels, and predict supply chain disruptions. In manufacturing, Gen AI tools are being used to:
- Enhance production planning and scheduling.
- Monitor equipment health through predictive maintenance.
- Improve quality control via image recognition, identifying defects in real time.
Procurement departments also benefit from AI-assisted contract analysis, fraud detection, and automated order processing, reducing administrative overhead while improving compliance and accuracy. For instance, a major paper producer now uses AI to personalise order processing according to individual customer preferences, while another applies AI to enhance visual inspection of recycled materials, improving quality and sustainability outcomes.
Corporate functions
Even administrative and support functions are seeing transformation. Gen AI can assist in:
- Financial planning and reporting, providing dashboards that summarise complex datasets.
- Human resources, with AI-driven recruitment, automated HR queries, and workflow optimisation.
- Legal and compliance, by analysing contracts and identifying risks or anomalies.
The overall result is a more agile, responsive, and data-driven organisation that can innovate faster, reduce costs, and better serve customers.
Challenges and considerations in gen AI adoption
Despite its promise, the adoption of Gen AI in the packaging and paper industry is not without hurdles. Executives highlight several key challenges that companies must address to realise the full potential of AI.
Data and technology infrastructure
One of the most frequently cited obstacles is limited access to clean, structured, and comprehensive data. Many packaging companies still rely on legacy IT systems that are not optimised for AI applications.
Modernising these systems and creating a robust data architecture is critical for successful AI integration.
Skills and expertise
Generative AI requires a different set of skills than traditional operations. Organisations need employees who can design AI prompts, interpret outputs, and integrate solutions into business processes.
Currently, a minority of companies report having leadership with a high degree of AI knowledge, highlighting the importance of training and external partnerships.
Privacy, IP, and regulatory concerns
The use of AI raises questions around intellectual property ownership, confidentiality, and compliance with privacy regulations. Packaging companies must ensure that their AI practices respect these legal boundaries, particularly when handling sensitive customer data or proprietary designs.
Cost and ROI
While AI can generate substantial long-term value, initial investments in software, data management, and talent can be significant. Companies must carefully evaluate the expected return on investment and prioritise applications with the highest potential impact.
Overcoming these challenges requires a strategic approach: starting with small, high-value pilot projects, building internal expertise, and establishing clear governance frameworks to manage risks. Companies that approach adoption thoughtfully are most likely to reap the rewards of faster innovation, operational efficiency, and competitive advantage.
Looking ahead: the future of ai in packaging
The potential of generative AI in the packaging and paper industry is vast, touching nearly every function of the business.
From accelerating R&D and boosting commercial performance to optimising supply chains and modernising corporate functions, Gen AI offers tools to reshape operations for greater efficiency, creativity, and sustainability.
Companies that embrace AI early are likely to gain a competitive edge, particularly as consumers and regulators increasingly prioritise environmentally responsible packaging solutions.
AI-driven insights can help organisations respond quickly to market shifts, personalise customer experiences, and achieve cost savings that were previously unattainable.
In the next decade, Gen AI is expected to become a standard part of the packaging and paper industry toolkit.
Firms that proactively invest in data infrastructure, skills development, and pilot projects will be well-positioned to capitalise on this transformative technology.
For an industry once considered slow to digitise, generative AI represents not just a technological upgrade, but a new frontier for innovation and growth.
