Transformative Effect: AI in Semiconductor Design


Based on the ability of artificial intelligence (AI) to automate repetitive tasks and process massive amounts of data, AI technology is revolutionizing many industries. Such industries range from healthcare and banking to cyber security, transportation, marketing, customer service, manufacturing, and more.

One industry that’s undergoing a particularly significant transformation at the hands of AI technology is the field of semiconductor design.

The Landscape for Semiconductors

Semiconductors, also called chips, microchips, or integrated circuits, are tiny components that enable electronic switching and serve as the foundation for all computer processing. As a result, semiconductors are integral to everything from smart phones and laptops to wind turbines, solar technology, wearable technology (like fitness trackers), electronic control systems and driverless capabilities in modern vehicles, implantable medical technology (like pacemakers and insulin pumps), gaming hardware, and many more technologies consider essential in today’s industrialized economies.

As sales of connected technologies continue to grow, so does demand for the next-generation semiconductors needed to fuel them. According to Statista, the global market for semiconductors is expected to grow by 13% to nearly US$590 billion in 2024. At the same time, the semiconductor industry is highly competitive. Taiwan, South Korea, and Japan currently lead the world in semiconductor production. However, experts expect the landscape will get even more competitive. The United States and European Union are vigorously ramping up their activity following their enactment of The CHIPS and Science Act and The European CHIPS Act in August 2022 and September 2023, respectively.

In the semiconductor industry’s ongoing quest for tools that can enhance engineering efficiency and accelerate speed to market, thereby giving manufacturers a competitive edge, the use of artificial intelligence and machine learning (ML) stand as game-changers in semiconductor design and manufacturing.

A New Paradigm in Design

Experts confirm that the use of AI enhances semiconductor (chip) design, or the process known as “electronic design automation” (EDA), in many ways.

Among them, AI automates complex processing tasks, thereby reducing the risk of human error. Artificial intelligence’s ability to analyze past patterns across huge quantities of data, identify efficient pathways, and optimize the space (or “real estate”) within semiconductors helps improve semiconductor performance and meet design criteria. It also reduces chip size, resources required, and cost. By being able to “learn” from past experiences, AI algorithms help semiconductor engineers predict and prevent potential design issues down the road that could otherwise result in the need for costly changes.

Ultimately, AI helps semiconductor manufacturers optimize power, performance, and area, or “PPA”– the three goals of chip design– by helping engineers to both design advanced new chips as well as efficiently and cheaply overhaul and shrink the many older-technology (65 nanometer process node or larger) chip designs on which much of the semiconductor industry has been predicated for the past decade without the need to update their fabrication equipment.

The future continues to look bright for the integration of AI in semiconductor design, with Deloitte experts noting that “some chips are getting so complex that advanced AI may soon be required.”

Learn the Ins and Outs of AI in Semiconductor Design from an Industry Expert

In today’s fast-paced technological landscape, AI and ML techniques are revolutionizing chip design methodologies. Integrated-circuit (IC) chip companies and engineers have unprecedented opportunities to use these technologies to enhance product quality across crucial dimensions such as speed, energy efficiency, and cost. This, in turn, enables the achievement of goals with reduced engineering resources and accelerated time-to-market.

Stay on top of the dynamic field of AI in semiconductor design through a two-day virtual training from IEEE, Artificial Intelligence and Machine Learning in Chip Design. It is presented by Andrew B. Kahng, an IEEE Fellow, Distinguished Professor of CSE and ECE at the University of California San Diego, and co-founder of Blaze DFM, Inc., an EDA software company that delivered new cost and yield optimizations at the IC design-manufacturing interface.

This comprehensive two-day virtual training session will equip engineers with:

  • The essential knowledge to leverage AI and ML effectively in chip design and EDA,
  • An understanding of the rationale behind these technological shifts to identifying high-value applications and selecting relevant AI and ML technologies, and
  • Insights into optimizing design methods and preparing for the future of chip design.

Attendees will also have the opportunity for first-hand interaction with Professor Kahng and ask him questions during the interactive question-and-answer portion of the training.

Successful completion of this training and assessment will earn attendees an IEEE Certificate of Completion bearing professional development hours (PDHs) and continuing education units (CEUs).

Don’t miss this opportunity to get your questions answered directly by a renowned subject matter expert in the industry! Save your seat today to secure your spot in this enlightening training session.

Interested in access for yourself? Visit the IEEE Learning Network (ILN).

Connect with an IEEE Content Specialist today to learn how to get access to this program for your organization.


Anirudh, VK. (10 February 2022). 10 Industries AI Will Disrupt the Most by 2030. Spiceworks.

(2 February 2024). How AI is Transforming the Semiconductor Industry in 2024 and Beyond. ACL Digital.

McCallum, Shiona. (3 August 2023). What Are Semiconductors and How Are They Used? BBC.

(29 March 2024). Generative AI: The Next S-Curve for the Semiconductor Industry? McKinsey & Company.

Loucks, Jeff, Stewart, Duncan, Simons, Christie, and Kulik, Brandon. (30 November 2022). AI in Chip Design: Semiconductor Companies are Using AI to Design Better Chips Faster, Cheaper, and More Efficiently. Deloitte. 

Alsop, Thomas. (8 February 2024). Semiconductor Market Revenue Worldwide from 1987 to 2024. Statista.

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