Hyperscalers and chip makers are the beneficiaries of AI: Sherlund

Key Concepts

• Hyperscalers: Large cloud computing providers (e.g., Amazon Web Services, Microsoft Azure, Google Cloud) that are major beneficiaries of AI due to their provision of compute capacity, storage, and networking.
• Compute Capacity: The processing power and resources required for AI operations, particularly for training and inference.
• AI Inference: The process of using a trained AI model to make predictions or decisions on new data. This is becoming increasingly important as enterprises integrate AI into their workflows.
• AI Training: The process of feeding large datasets to an AI model to enable it to learn and improve.
• Electrification Sector: Industries involved in power generation and distribution, experiencing a renaissance due to the immense power demands of AI.
• Data as a Gold Mine for AI: The critical role of large datasets in fueling AI development and performance.
• Knowledge Workers: Professionals whose jobs involve processing and analyzing information, making them particularly vulnerable to AI automation.
• Blue-Collar Workers: Individuals in manual labor roles requiring physical presence and dexterity, generally considered less vulnerable to current AI automation.
• Artificial General Intelligence (AGI): A hypothetical level of AI that possesses human-like cognitive abilities.
• Superintelligence: A hypothetical level of AI that surpasses human intelligence.
• Human in the Loop: The concept of ensuring human oversight and control in AI decision-making processes.

Tech Shares and AI Spending Commitments

Last week, tech shares experienced pressure due to investor concerns about the substantial spending commitments being made by AI giants like OpenAI. Rick Sherlin, Managing Director in Tech Investment Banking at Wedbush, advises clients on strategic and financial deals within the AI and broader technology landscape. He notes that his firm, Sherland Partners, now partnered with Wedbush, focuses on AI and disruptive technologies, anticipating significant consolidation and advisory opportunities in this sector. Sherlin emphasizes the transformative idea that "every company becomes an AI company."

Winners in the AI Landscape

While avoiding specific stock recommendations, Sherlin identifies key sectors poised to benefit from the AI boom:

• Hyperscalers: These companies are clear beneficiaries as they provide the essential compute capacity, storage, and networking required for AI's near-infinite demand.
• Chip Companies: The demand for advanced chips to power AI operations is immense.
• Electrification Sector: AI's tremendous power requirements are driving a renaissance in this sector, highlighting power as a potential constraint.
• Software Companies with Data: Data is crucial for AI. As AI moves beyond consumer applications (like Perplexity or ChatGPT) to enterprise workflows, the demand for AI inference within enterprise software is expected to surge.

The primary concern for investors is the capital expenditure required to meet this demand, which is currently supply-constrained rather than demand-constrained.

Vulnerable Jobs and Economic Impact

Sherlin discusses the impact of AI on the job market:

• Vulnerable Jobs:

  • Coding/Programming: AI has become proficient in coding, making entry-level programming jobs difficult to secure.
  • Knowledge Workers: AI's ability to quickly look up, summarize, and process information makes entry-level roles in fields like finance (Wall Street) and law more exposed.
  • Healthcare (Diagnosis): AI's diagnostic capabilities, such as reading X-rays, are advancing rapidly.
  • Drug Design: AI can significantly accelerate the discovery of new molecules, a process that traditionally takes PhDs months or years.

• Less Exposed Jobs:

  • Blue-Collar Workers: Jobs requiring physical presence, dexterity, and muscle are currently less vulnerable, though future robotics advancements may change this.

Sherlin likens the current AI revolution to previous industrial automations (factory automation, electricity, automotive industry), which created new industries and jobs while displacing others. He believes AI will not necessarily make people "stupid" but acknowledges concerns about unemployment and the need for reskilling.

Financial Commitments and Capital Markets

The scale of investment in AI is breathtaking. The five major cloud computing companies are spending an estimated $375 billion on AI in the current year. Companies like OpenAI are making trillion-dollar commitments. This has raised concerns about the ability to fund such massive expenditures. However, Sherlin believes the capital markets are deep, and debt markets are being utilized. He is optimistic that the necessary funding will be found due to the profound global economic impact and the need for increased productivity driven by AI.

Broader Concerns and Future Outlook

Beyond financial and employment concerns, Sherlin touches upon:

• Geopolitical and Social Stability: The widespread impact of AI across economies and countries raises concerns about stability.
• AI Safety and Control: As AI approaches Artificial General Intelligence (AGI) and potentially Superintelligence, there are significant concerns about ensuring AI decisions are made with human oversight ("human in the loop") and understanding the implications of AI surpassing human intelligence.
• The Race for AI Dominance: The current focus on developing AI rapidly, particularly in the race between the US and China, may lead to guardrails being a secondary concern for some companies. However, Sherlin anticipates this will become a more significant issue in the future.

Conclusion

The AI revolution is in its early stages, presenting immense opportunities and challenges. While hyperscalers, chip manufacturers, and the electrification sector are poised to benefit significantly, the demand for compute power and data is driving substantial capital investment. The impact on the job market, particularly for knowledge workers, is a key concern, alongside broader societal and safety implications as AI capabilities advance. Despite the scale of financial commitments, Sherlin expresses confidence in the capital markets' ability to support AI expansion, driven by the transformative potential of the technology for global economies.