Global EDA Tools Market to Reach US$26.9 Billion by 2030

The global market for EDA Tools estimated at US$13.9 Billion in the year 2023, is expected to reach US$26.9 Billion by 2030, growing at a CAGR of 9.8% over the analysis period 2023-2030. Consumer Electronics Application, one of the segments analyzed in the report, is expected to record a 10.3% CAGR and reach US$8.8 Billion by the end of the analysis period. Growth in the Communications Application segment is estimated at 8.6% CAGR over the analysis period.

The U.S. Market is Estimated at US$2.7 Billion While China is Forecast to Grow at 11.0% CAGR

The EDA Tools market in the U.S. is estimated at US$2.7 Billion in the year 2023. China, the world`s second largest economy, is forecast to reach a projected market size of US$5.3 Billion by the year 2030 trailing a CAGR of 11.0% over the analysis period 2023-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 8.2% and 9.1% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 9.2% CAGR.

What Are EDA Tools, and How Are They Transforming Chip Design?

Electronic Design Automation (EDA) tools form the backbone of the semiconductor and electronic circuit design process, enabling the automation of critical functions in integrated circuit (IC) design. EDA tools manage complex tasks across a spectrum of design processes, from circuit simulation and logic verification to physical layout and synthesis, offering solutions that save time and reduce errors. A pivotal moment in the EDA tools market’s growth came as consumer demands for faster, more energy-efficient, and compact devices pushed chipmakers to develop advanced architectures. EDA tools provide solutions across a range of design needs, from traditional 2D ICs to complex 3D stacked designs, playing an essential role in the increased shift towards system-on-chip (SoC) designs. Emerging sectors like 5G, automotive electronics, and the Internet of Things (IoT) have further expanded the use of EDA tools, with each application necessitating unique, complex design parameters that are nearly impossible to fulfill manually. Meanwhile, as these tools become smarter, capable of leveraging AI and machine learning (ML) capabilities, they are optimizing design processes by predicting design outcomes, identifying potential issues early in the workflow, and suggesting corrective actions. These advancements, combined with the increased deployment of EDA tools in cloud environments, have propelled market growth as industries seek to meet ever-evolving consumer demands with increasingly sophisticated designs.

How Are AI and ML Shaping the Future of EDA Tools?

The infusion of artificial intelligence (AI) and machine learning (ML) into EDA tools has led to one of the most transformative shifts in the sector’s history, reshaping both the design and verification phases. Traditionally, EDA tools relied on rule-based approaches and manual oversight, which were effective yet limited by human processing capabilities and fixed rules. AI and ML introduce new levels of automation, driving efficiency by identifying patterns within the immense volumes of data generated during chip design, thereby optimizing processes and reducing the likelihood of errors. In timing closure, for instance, AI-powered tools can predict potential timing violations and suggest preemptive solutions, accelerating one of the most time-intensive stages in chip production. Meanwhile, ML algorithms enable real-time learning and adaptation, making it possible to fine-tune design parameters iteratively based on previous design outputs. This results in a significant reduction in design iteration cycles, which can dramatically cut down both costs and production timelines. Beyond timing closure, these tools can streamline processes in the RTL to GDSII flow, handling complex challenges like manufacturability and layout optimization. In recent years, the industry has also seen startups and established players alike invest in generative AI solutions for EDA, such as natural language-based code generation and verification copilots, further underlining the transformative potential of AI and ML in this sector.

What Role Do 5G, Automotive Electronics, and IoT Play in Driving Demand for EDA Tools?

The evolution of high-performance computing (HPC) and emerging technologies like 5G, automotive electronics, and IoT has led to a surge in demand for customized, high-function EDA tools. The automotive industry, with its heavy reliance on advanced driver-assistance systems (ADAS) and electric vehicle (EV) battery management systems, requires IC designs that are both highly efficient and robustly secure. With automotive ICs containing millions of lines of code, EDA tools become invaluable for managing and verifying such complex designs in compliance with stringent functional safety standards like ISO 26262. In parallel, the advent of 5G technology is fueling the demand for high-performance chips capable of supporting massive device connectivity, high-speed data transfer, and low latency. EDA tools have evolved to address these needs, assisting in creating compact, multi-functional chips optimized for 5G’s demands. IoT, with applications across industrial automation, healthcare, and consumer electronics, further adds to the demand for EDA solutions, as each use case requires tailored chip configurations to support diverse functionalities like real-time processing and energy efficiency. These fields, which are defined by complex IC requirements, have increasingly turned to EDA tools not only for design simplification but also for ensuring compatibility and performance within highly specific operating environments. In turn, this industry-wide adoption has pushed vendors to develop specialized tools to meet these diverse, high-stakes application needs.

What Factors Are Driving Growth in the EDA Tools Market?

The growth in the EDA tools market is driven by several factors closely linked to technological advancements, changing consumer expectations, and increased use of electronics across sectors. First, the increasing complexity of IC designs due to shrinking node sizes and the demand for high-performance devices necessitate the use of advanced EDA tools, capable of handling intricate circuit layouts and high-level simulations. The growing integration of AI and ML in design workflows has further bolstered demand, as companies leverage these capabilities to automate time-consuming tasks and improve accuracy in high-stakes design phases. Additionally, the rise of heterogeneous integration, where multiple chip components like logic, memory, and sensor chips are integrated into one package, has created a need for highly specialized EDA tools that can manage varied process flows and ensure compatibility across diverse IC elements. Shifts in consumer behavior toward ultra-fast, compact, and power-efficient devices also drive demand, especially in high-growth sectors like smartphones, 5G infrastructure, and wearables. Finally, as cloud adoption increases across industries, EDA tools are increasingly offered as cloud-based services, allowing for better scalability, collaboration, and accessibility. The shift toward cloud-based EDA solutions has made these tools more accessible to startups and smaller firms, further expanding the market’s reach and contributing to sustained growth across applications, regions, and user bases.