The AI effect: Supply, demand, and continued adoption

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One aspect of the electronic supply chain that is unchanging is the effect emerging technologies have on the ebb and flow of the market. As technologies cycle in and evolve, they play a significant role in demand, supply, price, lead times, and manufacturing operations.

Of course, this is dependent on consumer adoption as well, but as companies integrate more advanced technologies into end-user products, the market behavior all points in the same direction—up in demand and down in supply.

Generative AI: The Emerging Technology that Continues to Evolve

Today, generative artificial intelligence (AI) is the major stakeholder in technological advancement. With $1.3 trillion in growth expected by 2032, generative AI is the major driver of electronic component market activity, impacting supply, demand, pricing, and lead times.

What Is Generative AI?

*The term refers to the algorithms and models that identify the patterns and structures within the existing content.
*The purpose is to create new content based on existing content (text, images, video, audio, and other media).
*The intent is to deliver real-time, automated results for the end-user.

Chipmakers and companies continue to see the rise in its applications with industries like automotive, consumer electronics, energy, healthcare, and more including it in end-user products. These industries apply AI for various use cases like customer communication, improved automation, and optimization.

The "popularity" of generative AI stems from its usability, which chipmakers and companies are seeing with the adoption of chatbot programs like ChatGPT, DALL-E, and Bard. These programs rely on AI technologies like natural language processing (NLP), such as language models (LLMs), speech synthesis (SS), and computer vision (CV), which all create a user-friendly, convenient end-product.

Demand for High-Performance Chips

The speed of adoption and continued evolution of AI results in the need for high-performance chips like GPUs and FPGAs. As an example of how these chips are applied,

*GPUs are specialized chips that can perform parallel computations for graphics and AI tasks.
*FPGAs are reconfigurable chips that can be customized for specific AI tasks.

While chipmakers update production lines to support the continued demand for supply, the companies continue to develop end-products to apply them. Among the companies increasing development and driving demand are Nvidia, Google, Amazon, and Microsoft, as they seek more market opportunities in AI applications.

While these companies see revenue growth from this technology, it doesn't come without the challenges of competing for manufacturing support from the chipmakers.

As Technologies Emerge, Manufacturers Pivot Plans

Producing the chips that power AI applications comes with complex challenges. Nvidia leads the pack in the latest benchmark tests for chip speed, but competitors like Google and Advanced Micro Devices are attempting to carve out their own position. However, producing high-performing chips comes at a higher cost due to the design and fabrication requirements. As generative AI models become more advanced, chipmakers must pivot.

Currently, manufacturers are allocating resources toward research and development (R&D) and implementing innovative manufacturing techniques. The balancing act between supporting the rise of AI and other verticals is tricky, especially considering Nvidia's head start. Today, Nvidia accounts for more than 70% of AI chip sales, a vast gap for other companies to bridge.

Even with their popularity, Nvidia cannot keep up with all the demand, opening the window for other manufacturers to carve out market share. The same level of investment and support is needed in AI hardware and all the other parts of the technology stack, encompassing the data centers where AI applications occur. These centers include components from memory to interconnects, packing, and systems.

It remains to be seen if manufacturers seeking unique solutions can allocate manufacturing support to keep up with demand.

Strategic Supply Chain Building

Amid the boon of generative AI, distributors encourage manufacturers and companies to think strategically to source the parts they need for the short and long term. As generative AI evolves, the market will move as it moves with the continued growth in demand and ways to manage supply over time.

To learn how to get Out In Front of risks to your supply chain, reach out to Fusion Worldwide today to speak to a procurement specialist. Contact us today.

Author: Tobey Gonnerman, President, Fusion Worldwide

The AI Effect: Supply, Demand, and Continued Adoption

The AI Effect: Supply, Demand, and Continued Adoption