人工智慧包装市场机会、成长动力、产业趋势分析及 2025 - 2034 年预测

2024 年全球人工智慧包装市场价值为 24 亿美元，预计到 2034 年将以 10.1% 的复合年增长率成长，达到 62 亿美元。随着全球包装产业经历数位转型，人工智慧 (AI) 的整合已成为创新和效率的关键推动因素。越来越多的公司开始采用人工智慧解决方案来提高包装准确性、改善即时决策并简化营运工作流程。这种转变的驱动力在于降低生产成本、减少环境影响以及满足日益增长的智慧、客製化和永续包装的需求。

人工智慧技术正在食品饮料、製药、化妆品和物流等不同行业中大规模应用。随着电子商务的蓬勃发展以及客户对包装功能性、个人化和永续性的期望迅速增长，人工智慧提供了满足这些不断变化的需求的工具。人工智慧包装系统可实现即时资料分析、增强预测能力并提供自动化功能，从而降低劳动力成本并提高包装一致性。从智慧标籤和追踪到自适应包装设计，人工智慧从根本上改变了品牌与消费者互动和管理供应链的方式。

市场根据技术进行细分，其中机器学习类别占据最大份额，到 2024 年将达到 27.6%。这种主导地位源自于机器学习分析大量生产资料的能力不断增强，使企业能够提高营运绩效、预测设备维护并优化资源配置。随着机器学习的不断发展，製造商正在利用它来增强异常检测、减少浪费和需求预测，最终帮助提高生产力并降低成本。人工智慧在包装领域的应用非常广泛，包括品质检测、智慧包装、供应链优化以及包装设计和客製化。

仅包装设计和客製化领域在 2024 年就创造了 9.488 亿美元的收入。这种扩张主要归功于人工智慧提供客製化、美观且可持续的包装解决方案的能力。品牌正在使用人工智慧工具来开发包装，不仅符合消费者的喜好，而且还减少材料的使用，增强环境责任。此外，互动元素和二维码等智慧功能等创新使品牌能够与消费者即时互动，提高忠诚度并改善客户旅程。

预计到 2034 年，美国人工智慧包装市场规模将达到 21 亿美元。自动化投资的增加以及人工智慧驱动技术的部署以加强供应链推动了市场的成长。永续包装法规的强力推动和电子商务的快速增长进一步支持了智慧包装系统的采用。美国各地的企业正在利用人工智慧来提高生产力、降低成本，并透过智慧包装提供增强的消费者体验。

全球人工智慧包装产业的主要参与者包括 Otto Motors、ABB、Avathon、微软公司、亚马逊公司和 Neurala。这些公司策略性地专注于先进的自动化、机器学习和物联网集成，以彻底改变包装操作、改善即时监控、实现预测性维护并提供针对特定市场需求的高度客製化的包装解决方案。

目录

第一章：方法论与范围

第二章：执行摘要

第三章：行业洞察

• 产业生态系统分析
• 产业衝击力
  • 成长动力
    • 对永续和环保包装解决方案的需求不断增长，推动人工智慧的整合
    • 越来越多采用物联网和感测器技术进行即时包装优化
    • 提高供应链透明度和包装可追溯性的需求日益增长
    • 机器学习演算法的进步加速了包装自动化
  • 产业陷阱与挑战
    • 包装领域实施人工智慧的初始投资和营运成本较高
    • 对连网包装环境中资料安全和隐私的担忧
• 成长潜力分析
• 监管格局
• 技术格局
• 未来市场趋势
• 差距分析
• 波特的分析
• PESTEL分析

第四章：竞争格局

• 介绍
• 公司市占率分析
• 主要市场参与者的竞争分析
• 竞争定位矩阵
• 策略仪表板

第五章：市场估计与预测：按技术，2021 - 2034 年

• 主要趋势
• 机器学习
• 电脑视觉
• 自然语言处理
• 预测分析
• 扩增实境/虚拟现实
• 其他的

第六章：市场估计与预测：按应用，2021 - 2034 年

• 主要趋势
• 品质控制和检验
• 包装设计与客製化
• 供应链优化
• 智慧包装

第七章：市场估计与预测：按最终用途产业，2021 - 2034 年

• 主要趋势
• 食品和饮料
• 製药和医疗保健
• 零售和消费品
• 化妆品和个人护理
• 汽车
• 工业品
• 其他的

第八章：市场估计与预测：按地区，2021 - 2034 年

• 主要趋势
• 北美洲
  • 我们
  • 加拿大
• 欧洲
  • 德国
  • 英国
  • 法国
  • 西班牙
  • 义大利
  • 荷兰
• 亚太地区
  • 中国
  • 印度
  • 澳洲
  • 韩国
  • 日本
• 拉丁美洲
  • 巴西
  • 墨西哥
  • 阿根廷
• 中东和非洲
  • 沙乌地阿拉伯
  • 阿联酋
  • 南非

第九章：公司简介

• Ardagh Group
• Augmentir
• Avathon
• Cognex
• Georgia Pacific
• Keyence
• Landing AI
• Microsoft Corporation
• Midjourney Inc.
• Neurala
• Packsize
• Systech (Markem-Imaje and Dover)
• Tetra Pak

The Global Artificial Intelligent Packaging Market was valued at USD 2.4 billion in 2024 and is estimated to grow at a CAGR of 10.1% to reach USD 6.2 billion by 2034. As the global packaging industry experiences a digital transformation, the integration of artificial intelligence (AI) has emerged as a critical enabler of innovation and efficiency. Companies are increasingly turning to AI-powered solutions to enhance packaging accuracy, improve real-time decision-making, and streamline operational workflows. This shift is driven by the need to minimize production costs, reduce environmental impact, and cater to the rising demand for smart, customized, and sustainable packaging.

AI technologies are being adopted at scale across diverse industries such as food & beverage, pharmaceuticals, cosmetics, and logistics. With e-commerce booming and customer expectations around packaging functionality, personalization, and sustainability growing rapidly, AI provides the tools to meet these evolving requirements. AI-powered packaging systems enable real-time data analysis, enhance predictive capabilities, and offer automation that drives down labor costs while elevating packaging consistency. From intelligent labeling and tracking to adaptive packaging design, AI is fundamentally transforming how brands engage with consumers and manage their supply chains.

The market is segmented based on technology, with the machine learning category accounting for the largest share at 27.6% in 2024. This dominance stems from the growing ability of machine learning to analyze large volumes of production data, allowing businesses to enhance operational performance, predict equipment maintenance, and optimize resource allocation. As machine learning continues to evolve, manufacturers are leveraging it for enhanced anomaly detection, waste reduction, and demand forecasting, ultimately helping to increase productivity and cut costs. Applications of AI in packaging are extensive and include quality inspection, smart packaging, supply chain optimization, and packaging design and customization.

The packaging design and customization segment alone generated USD 948.8 million in 2024. This expansion is largely attributed to the capabilities of AI to deliver tailored, aesthetically compelling, and sustainable packaging solutions. Brands are using AI tools to develop packaging that not only aligns with consumer preferences but also reduces material usage, enhancing environmental responsibility. Additionally, innovations such as interactive elements and smart features like QR codes are allowing brands to foster real-time engagement with consumers, driving loyalty and improving the customer journey.

The U.S. Artificial Intelligent Packaging Market is expected to reach USD 2.1 billion by 2034. The market's growth is being propelled by rising automation investments and the deployment of AI-driven technologies to strengthen supply chains. A strong push for sustainable packaging regulations and the exponential growth of e-commerce further support the adoption of smart packaging systems. Businesses across the U.S. are tapping into AI to boost productivity, reduce costs, and deliver enhanced consumer experiences through intelligent packaging.

Key players in the Global Artificial Intelligent Packaging Industry include Otto Motors, ABB, Avathon, Microsoft Corporation, Amazon Inc., and Neurala. These companies are strategically focusing on advanced automation, machine learning, and IoT integration to revolutionize packaging operations, improve real-time monitoring, enable predictive maintenance, and offer highly customized packaging solutions tailored to specific market needs.

Table of Contents

Chapter 1 Methodology and Scope

• 1.1 Market scope and definitions
• 1.2 Research design
  • 1.2.1 Research Approach
  • 1.2.2 Data collection methods
• 1.3 Base estimates and calculations
  • 1.3.1 Base year calculation
  • 1.3.2 Key trends for market estimation
• 1.4 Forecast model
• 1.5 Primary research and validation
  • 1.5.1 Primary sources
  • 1.5.2 Data mining sources

Chapter 2 Executive Summary

• 2.1 Industry 360⁰ synopsis

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
• 3.2 Industry impact forces
  • 3.2.1 Growth drivers
    • 3.2.1.1 Growing demand for sustainable and eco-friendly packaging solutions driving AI integration
    • 3.2.1.2 Increasing adoption of IoT and sensor technologies for real-time packaging optimization
    • 3.2.1.3 Rising need for improved supply chain transparency and traceability in packaging
    • 3.2.1.4 Advancements in machine learning algorithms accelerating packaging automation
  • 3.2.2 Industry pitfalls and challenges
    • 3.2.2.1 High initial investment and operational costs for AI implementation in packaging
    • 3.2.2.2 Concerns over data security and privacy in connected packaging environments
• 3.3 Growth potential analysis
• 3.4 Regulatory landscape
• 3.5 Technology landscape
• 3.6 Future market trends
• 3.7 Gap analysis
• 3.8 Porter’s analysis
• 3.9 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

• 4.1 Introduction
• 4.2 Company market share analysis
• 4.3 Competitive analysis of major market players
• 4.4 Competitive positioning matrix
• 4.5 Strategy dashboard

Chapter 5 Market Estimates and Forecast, By Technology, 2021 - 2034 ($ Mn)

• 5.1 Key trends
• 5.2 Machine learning
• 5.3 Computer vision
• 5.4 Natural language processing
• 5.5 Predictive analysis
• 5.6 AR/VR
• 5.7 Others

Chapter 6 Market Estimates and Forecast, By Application, 2021 - 2034 ($ Mn)

• 6.1 Key trends
• 6.2 Quality control and inspection
• 6.3 Packaging design and customization
• 6.4 Supply chain optimization
• 6.5 Smart packaging

Chapter 7 Market Estimates and Forecast, By End Use Industry, 2021 - 2034 ($ Mn)

• 7.1 Key trends
• 7.2 Food & beverage
• 7.3 Pharmaceuticals & healthcare
• 7.4 Retail & consumer goods
• 7.5 Cosmetics & personal care
• 7.6 Automotive
• 7.7 Industrial goods
• 7.8 Others

Chapter 8 Market Estimates and Forecast, By Region, 2021 - 2034 ($ Mn & Tons)

• 8.1 Key trends
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
• 8.3 Europe
  • 8.3.1 Germany
  • 8.3.2 UK
  • 8.3.3 France
  • 8.3.4 Spain
  • 8.3.5 Italy
  • 8.3.6 Netherlands
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 India
  • 8.4.3 Australia
  • 8.4.4 South Korea
  • 8.4.5 Japan
• 8.5 Latin America
  • 8.5.1 Brazil
  • 8.5.2 Mexico
  • 8.5.3 Argentina
• 8.6 Middle East and Africa
  • 8.6.1 Saudi Arabia
  • 8.6.2 U.A.E.
  • 8.6.3 South Africa

Chapter 9 Company Profiles

• 9.1 Ardagh Group
• 9.2 Augmentir
• 9.3 Avathon
• 9.4 Cognex
• 9.5 Georgia Pacific
• 9.6 Keyence
• 9.7 Landing AI
• 9.8 Microsoft Corporation
• 9.9 Midjourney Inc.
• 9.10 Neurala
• 9.11 Packsize
• 9.12 Systech (Markem-Imaje and Dover)
• 9.13 Tetra Pak