Introduction

AI and semiconductors are at the core of today’s most significant industry trends. Understanding these technologies will not only help students explore career opportunities but also provide valuable insights into the future of major global industries.

For students in middle and high school, this post will outline potential career paths over the next ten years and identify companies they should consider for future employment.

How Industries Evolve Over Time

Leading companies change as industries shift. Businesses that successfully adapt to emerging trends thrive, while those that fail to innovate decline. A decade ago, energy, distribution, and financial companies dominated the top ten global corporations. However, in 2025, the top companies are technology-driven, with semiconductor firms like NVIDIA, Broadcom, and TSMC playing key roles.

Since AI cannot exist without semiconductors, these two industries are now shaping the global market together.

Semiconductors: The New Commodity

Traditionally, commodities referred to raw materials such as oil, gold, iron ore, grains, coffee, and sugar. However, semiconductors are now fundamental to nearly all electronic products, making them the modern-era commodity.

To understand the significance of semiconductors, we must examine the eight key stages of their manufacturing process and identify the companies leading in each stage.

The 8 Semiconductor Manufacturing Processes

Using data from Samsung, we can connect each semiconductor process to the leading companies involved.

1. Wafer Manufacturing – The foundation of semiconductor production.

   • Leading companies: Shin-Etsu, Siltronic, SUMCO, SK Siltron

    

2. Oxidation – Forms an oxide layer on the wafer.

   • Leading companies: SUMCO, Shin-Etsu, Applied Materials, Tokyo Electron (TEL, Japan).

3. Photolithography – Uses masks and light to create circuit patterns.

   • Leading companies: ASML, Nikon.

4. Etching Process – Carves out circuits on the wafer.

   • Leading companies: Lam Research, Tokyo Electron (TEL, Japan).

5. Deposition & Ion Implantation – Applies thin films to enhance circuit function.

   • Leading companies: Applied Materials, Lam Research, Motorios.

6. Metal Wiring Process – Connects etched sections with metal wiring.

   • Leading companies: Applied Materials, Tokyo Electron (TEL, Japan).

7. Electrical Die Sorting (EDS) – Tests semiconductor functionality and conductivity.

   • Leading companies: Thermo Fisher Scientific, Oxford Instruments.

8. Packaging Process – Assembles semiconductors into final products.

   • Leading company: TSMC (accounts for 5.7% of Taiwan’s GDP).

The first six steps are considered front-end processes, where Japanese companies have a strong influence, while the final steps involve back-end processing, where companies like TSMC dominate.

Semiconductor Chip Design Companies

Several companies specialize in chip design:

• NVIDIA – Leading in GPU development.

• AMD – Designs both CPUs and GPUs.

• Qualcomm – Focuses on mobile device processors.

To understand the connection between AI and semiconductors, we must explore how semiconductor manufacturing has evolved.

Why Did Semiconductors Get Smaller?

From the 1990s until recently, reducing chip size was the industry’s primary focus. Smaller chips:

• Improve energy efficiency and performance.

• Reduce electrical resistance, lowering power consumption.

• Fit more efficiently into mobile devices.

Miniaturization made mobile computing possible, leading to significant industry milestones like the iPhone Moment (2007) when Steve Jobs introduced the iPhone, creating a demand for smaller, more efficient chips.

However, as chips continued shrinking, quantum tunneling effects—where electrons leak through thin barriers—became a problem. This led to a shift toward quantum computing.

ChatGPT Moment (2022) and AI’s Rising Demand

On December 30, 2022, ChatGPT was launched, marking the beginning of the AI era. The focus shifted from making chips smaller to combining multiple chips to build larger processing units for AI applications. This led to the rise of data centers, where multiple chips work together to process AI computations.

Chiplet Technology and Data Centers

The concept of chiplets emerged as a way to package multiple chips together, forming large AI processing units. Today, semiconductor companies not only design chips but also engineer and manufacture chiplets, typically outsourcing production to TSMC.

How Data Centers Work

Chiplets are combined into racks (modular units in data centers), which are then stacked together to build large-scale data centers. These facilities power AI applications, cloud computing, and enterprise solutions.

Key Technologies in Data Centers

To ensure efficient data processing, several technologies are critical:

• Chip-to-Chip Communication – Prevents data errors between chips.

• Chiplet-to-Chiplet Communication – Ensures smooth interaction within chiplets.

• Rack-to-Rack Communication – Optimizes large-scale data processing.

Broadcom leads in networking technology, specializing in SerDes (Serializer/Deserializer), a core technology for chip communication. Because of its dominance, Broadcom is often called “the next NVIDIA.”

Cloud Computing and AI Software Companies

Beyond hardware, AI-powered cloud computing plays a significant role. Major software companies leveraging AI and cloud infrastructure include:

• OpenAI – Developer of ChatGPT.

• Salesforce – Integrates AI into CRM tools.

• Snowflake – Specializes in cloud data management.

• Palantir – Focuses on data analytics and AI-driven automation.

• Applovin – Provides AI-based ad optimization for mobile apps.

These companies do not manufacture semiconductors but rely on cloud computing and AI integration to drive their business models.

Data Center Hardware and Infrastructure

Data centers require physical infrastructure, including:

• Temperature control

• Humidity regulation

• Efficient power supply

A key player in this space is Vertiv, which specializes in optimizing power grids, cooling systems, and structural designs for data centers.

Career Paths in AI & Semiconductors

For students considering future careers, there are three primary paths:

1. Semiconductor Manufacturing & Design

   • Design: NVIDIA, AMD, Qualcomm

   • Front-end processing: SUMCO, ASML, Lam Research

   • Back-end processing: TSMC, Broadcom

2. AI & Cloud Computing Startups

   • Unlike semiconductor firms, AI software startups can be launched with lower costs.

   • Future entrepreneurs may focus on cloud-based AI services.

3. Big Tech Careers

   • Students interested in AI and data centers can target companies like Apple, Amazon, Google, Tesla, Meta, and OpenAI.

Conclusion

The ChatGPT Moment accelerated AI adoption, increasing the importance of back-end semiconductor processing and data centers. Many of today’s most influential CEOs have backgrounds in engineering, natural sciences, and computer science, emphasizing the significance of technical expertise.

This concludes our second installment on industry trends, focusing on AI and semiconductors. Stay tuned for further updates on emerging industries.

Thank you!