In January 2025, IPC International, Inc., the global electronics association, conducted an industry-wide sentiment survey to assess the state of sustainability efforts. Responses came from a range of sub-industries, geographies, and company sizes, reflecting a broad industry perspective.
Key Findings
• Growing Sustainability Momentum – 59% of respondents expect their companies to increase sustainability efforts in 2025. Printed circuit board (PCB) and contract manufacturers anticipate the most growth.
• Sustainability as a Competitive Advantage – Regulatory compliance is a key driver for 66% of respondents, but companies are also motivated by efficiency gains (58%), technological advancements (56%), and long-term competitive positioning (55%).
• Implementation Challenges – Budget constraints, regulatory complexity, and limited expertise are the top three barriers to sustainability.
• Industry Collaboration Key – Respondents emphasized the need for greater industry-wide interaction, sharing of best practices, and access to resources to navigate sustainability challenges.
IPC supports the industry to take advantage of opportunities and overcome challenges identified in the survey through its sustainability program Evolve. Through Evolve, IPC brings together experts, ideas, and solutions from across the industry to drive progress toward a more sustainable future. Further tools and resources will be added in 2025 that will empower the industry to address financial and non-financial impact assessments, greenhouse gas reporting, safer and more sustainable chemical alternatives, and circularity for electronics.

This two-part paper will explore how electronics suppliers within the e-mobility transportation sectors can address the exploding sustainability requirements. Part 1 contains background about regulatory drivers that led to the creation of an automotive specific database for the entire supply chain to report material content. This reporting system has evolved over time to encompass multiple Environmental, Social, and Governance (ESG) topics with a comprehensive, harmonized set of requirements. We’ll detail these current topics’ data structure needs and connectivity to existing electronics material compliance. In Part II of this paper, we cover current and expected future regulatory efforts and automotive industry approaches to managing overall supply chain compliance, such as their focus on CarbonNet0 metrics as a measure. The focus will shift toward providing actionable recommendations for electronics suppliers aiming to meet the evolving demands of the automotive industry’s environmental compliance requirements. These recommendations will cover best practices in regulatory compliance, supply chain management, and product redesign, as well as strategies for building stronger partnerships with automotive OEMs to ensure smoother transitions toward future regulatory frameworks. The goal is to help electronics suppliers not only stay ahead of regulatory trends but also leverage sustainability initiatives as a competitive advantage.

Artificial intelligence (AI) is the theory and development of computer systems able to perform tasks that normally require human intelligence. This includes visual perception and pattern recognition, speech recognition, decision-making, natural language processing and translation. Machine learning is the branch of AI in which computers learn from data without human assistance. Deep learning is a type of machine learning that trains a computer to perform human-like tasks such as recognizing speech, identifying images, or making predictions. AI refers to the simulation of human intelligence processes by machines, particularly computer systems with appropriate hardware and software. It involves creating systems that can perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, making decisions, solving problems and learning from experience. AI encompasses a wide range of technologies, algorithms and methodologies, each serving different purposes. In recent years, AI has been rapidly emerging in areas such as computer vision, generative AI with large language models, etc. AI in computer vision has found relevant use cases in quality inspection. Neural-network-based deep learning models have demonstrated high accuracy in object detection and classification in the area of digital image processing. As AI models start to show 
great potential to replace human cognition in quality inspection process through object detection and classification, AI-assisted quality inspection promises to further automate these processes. While this white paper focuses on the application of computer vision AI for automating inspection (i.e., applying AI for pattern recognition on inspection images), the rapidly growing availability and maturity of generative AI presents future possibility in generating inspection criteria.

IPC International, Inc. recognizes the challenges and opportunities facing companies in the electronics industry in the evolving practice of sustainability, most notably, the obligations established by the Corporate Sustainability Reporting Directive (CSRD). That is why IPC is dedicated to empowering the industry with guidance and resources to assist in navigating these obligations, including double materiality assessments (DMAs). DMAs oblige companies to identify and assess their actual or potential impacts related to environmental, societal, and economic sustainability matters (impact materiality), and sustainability matters that affect or may affect their current or future financial performance (financial materiality). A DMA is performed by a company to identify which sustainability topics are most important – or material – to its operations and stakeholders; these topics are evaluated and included in a company’s CSRD report. The purpose of this white paper is to help companies to prepare for achieving their DMA obligations.

As the United States turns to generative artificial intelligence (AI) to drive a wide range of manufacturing applications, it is critical to ensure the strength of assembly capabilities to remain competitive in the global marketplace. These applications leverage the high computational power, data processing capabilities, and machine learning models AI-based servers provide. The AI server market is expected to grow rapidly, with the biggest change coming from accelerated servers, including GPU servers. This whitepaper serves as a blueprint for strengthening assembly capabilities in the United States, particularly in printed circuit board assembly (PCBA) capability and capacity. Topics covered include key technologies, important applications, and global and regional supply chains needed to produce AI-based servers for data centers. The report includes a SWOT analysis illustrating the issues facing the United States and requiring the attention of the Department of Defense (DoD) and the Department of Commerce (DoC). Recommendations are also provided to ensure that U.S. AI data centers are resilient and competitive globally.

HPC data center markets now demand components with the highest processing and communication rates (low latencies and high bandwidth, often both simultaneously) and highest capacities with extreme requirements for advanced packaging solutions at both the component level and system level [1,2]. Insatiable demands have been projected for heterogeneous compute, memory, storage, and data communications. Interconnect has become one of the most important pillars of compute for these systems. If the taxonomy of interconnects within data centers are examined, the off-package interconnects include network interconnects (4-8 lanes) which are latency tolerant, and load store interconnects (hundreds of lanes) which are latency sensitive. On package die to die Interconnects for load store (tens of thousands of lanes) are extremely latency sensitive. Load store interconnects should be thought of as a continuum and needs to scale from die to package to board level and finally to node level [3].

Electronics manufacturers globally report that their growth is constrained by an inability to recruit, onboard, retain, and upskill workers. This white paper presents a holistic view of the workforce challenges facing the industry and outlines IPC’s approach to developing industry—wide solutions that are engaging, scalable, efficient, and effective. At the heart of IPC’s approach is an unprecedented and ambitious initiative to create career pathways within this dynamic industry.