By JB Baker, VP of Products, ScaleFlux

Artificial intelligence is driving one of the fastest-growing demands for hardware in modern history. Deloitte projects that AI chip sales will account for 11% of the $576 billion global semiconductor market this year, potentially reaching $400 billion by 2027. The rise of generative AI and large language models (LLMs) has dramatically increased the need for GPUs, which excel at parallel processing tasks for training these models. As AI expands beyond IT into smart devices and edge computing, demand for advanced hardware will only accelerate.

This surge in demand —a more than 20% increase— is straining the global semiconductor supply chain. High-performance GPUs and specialized chips have become critical to AI progress but are increasingly difficult to source due to production limitations. As more enterprises deploy AI models and AI-powered devices, the risk of supply chain bottlenecks grows. Without strategic investments in expanding production and strengthening supply chains, the tech industry could face severe slowdowns, hindering AI adoption and stalling innovation across industries.

Supply Chain Challenges in the Semiconductor Industry

The industry relies on a delicate and intricate supply chain that supports the production of advanced chips necessary for modern technology. However, meeting the growing demand, particularly for AI-driven hardware, presents significant challenges such as:

  • Supplier Concentration Risks: As the sector relies on a few key suppliers for essential components, any disruption to one of these companies can potentially create significant bottlenecks, delaying production and impacting the entire supply chain.
  • Infrastructure Limitations: Constructing new facilities from scratch is more challenging than expanding existing plants. This makes it difficult for manufacturers to quickly ramp up production, leaving some regions lagging behind global competitors.
  • Resource Dependency and Shortages: Producing semiconductors involves a complex global supply chain, with chips traveling thousands of miles and crossing borders multiple times. The process relies on critical materials such as silicon, copper, and neon gas. Shortages or delays in obtaining these materials can significantly disrupt production timelines.
  • Regulatory Hurdles: Chip manufacturing facilities consume large amounts of water and emit greenhouse gases, making them subject to strict environmental regulations. Navigating these rules, particularly those related to air and water quality, can challenge the viability of projects, especially for companies that are less familiar with stringent standards and lack a clear battle plan to address such regulations.
  • Specialized Labor Shortages: Building and operating advanced semiconductor plants requires highly skilled workers. However, there is a shortage of talent with the necessary expertise. This labor gap can lead to delays, particularly if efforts to bring in workers from other regions face resistance or logistical challenges.

Industry Innovations and Strategic Moves

To meet the growing demands of AI-driven workloads, innovative storage and memory solutions have emerged as pivotal for enhancing performance and efficiency. These technologies integrate processing capabilities directly within storage systems and memory subsystems, minimizing data movement and accelerating task processing.

By managing data closer to its storage location, these advanced approaches reduce both latency and energy consumption—critical factors as AI models grow increasingly complex and data-intensive. This allows data centers to handle rising workloads more effectively without frequent hardware upgrades.

Adopting such solutions enables enterprises to optimize their existing infrastructure, achieving more with fewer resources. These innovations enhance scalability, empowering organizations to manage large datasets efficiently. As AI continues to drive demand for advanced computing power, these storage advancements are set to play a crucial role in maintaining data center performance and responsiveness while supporting sustainability and cost-efficiency goals.

About JB Baker, VP of Products at ScaleFlux  

JB Baker is a successful technology business leader with a 20+ year track record of driving top and bottom-line growth through new products for enterprise and data center storage. He joined ScaleFlux in 2018 to lead Product Planning & Marketing as the company innovates efficiencies for the data pipeline. JB entered the data storage field with Intel in 2000, later moving on to LSI where he led the definition and launch of the LSI Nytro PCIe Flash products and was instrumental in ramping up the new product line. With Seagate’s acquisition of the LSI Flash assets in 2014, JB transitioned to Seagate where his role expanded to cover the entire SSD product portfolio. He earned his BA from Harvard and his MBA from Cornell’s Johnson School.