AI Slowdown Argument Just a Market Misconception

With market fatigue and stress accumulating, there's no need to overreact to every stock movement.

It should be understood as an adjustment period preparing for the upcoming bull market, requiring a detached response to short-term stock volatility.

Since early September, the market has been in a neutral zone without leading stocks, leading to a frustrating period. The market is struggling to rise or fall, and patience is required.

Stock prices fluctuate based on short-term factors, and weak supply and demand make confident investment difficult.

In such a market, it's better to observe the overall market flow rather than seeking specific leading stocks.

However, this actually proves the strong development of the AI cycle.

The perception that stopping development poses a greater risk is dominant, and the premise of accelerating AI technology development has strengthened.

These discussions are seen as evidence that AI technology is evolving faster than expected.

The current S&P 500 forward PER is about 18-19x, similar to lows seen during the 2022 interest rate shock, 2023 tariff pressures, and 2024 Iran war.

This indicates a period of significantly increased valuation attractiveness, making it advisable to accumulate with spare funds when the market declines.

With valuation support confirmed and continued earnings growth expected, approaching from a long-term investment perspective, such as through dollar-cost averaging or pensions, is effective.

There is a historical record of stock prices invariably rising during this period.

A rise exceeding the annual average growth rate of 8-10% is expected.

As uncertainties related to the midterm elections dissipate, market direction becomes clearer, and institutional and smart money buying at lower prices is likely to continue.

While managing cash or adjusting positions due to concerns about macro variables is possible, abandoning investment ideas could lead to missed opportunities.

The effectiveness of the U.S. Treasury's 30-year bond yield stabilization policy is being confirmed, but the impact of oil prices due to strengthened sanctions and economic pressure on Iran remains a variable.

Therefore, it is crucial to maintain positions by focusing on corporate fundamentals and AI trends.

The AI slowdown argument is analogous to developing brakes alongside the accelerator in car development. This is a natural process, where companies discuss temporarily slowing down for safety standards.

Amidst the competitive landscape with China, a complete unilateral halt to AI development is practically impossible.

Therefore, the AI growth trend will continue, and the slowdown should be understood as an essential safety check for technological advancement.

There's a possibility that China could overtake the U.S. while the latter slows down AI development. Currently, AI infrastructure and semiconductor investments are still accelerating.

China is unlikely to cooperate on AI development, so the race for technological leadership is expected to continue.

In this situation, a unilateral slowdown is unrealistic, and competition to maintain U.S. AI technological superiority is inevitable.

The discussion to slow down AI development created a perception that it would negatively impact AI infrastructure demand. This led to a sell-off in semiconductor stocks, but it is considered a mechanical reaction to short-term psychological contraction.

Institutional investors tended to mechanically reduce positions to protect quarterly returns.

Therefore, the AI slowdown argument is interpreted as an overreaction by the market, and the growth of the AI industry should be continuously monitored from a long-term perspective.

Even if OpenAI and Anthropic agree to slow down AI development within the U.S., it's unlikely that other aspiring companies like Meta, Google, and Perplexity would cease development. AI has expanded beyond mere economic logic into military and technological hegemony.

Therefore, the possibility of a structural slowdown in AI demand is very limited.

In the context of global AI competition, slowing down AI development based solely on an agreement by specific companies or nations is unrealistic.

While there's debate on how effectively AI will replace white-collar jobs, it's evolving beyond simple chatbots to performing proxy tasks.

The market worries whether such massive investment will eventually lead to a bubble, but its feasibility needs careful examination.

Expectations and concerns about the economic effects of AI technology advancement coexist.

By 2030, AI could hypothetically replace 55% of white-collar tasks.

Applying a 75% discount rate, considering adoption speed and cost savings, AI is estimated to replace about 20-25% of white-collar labor value.

This analysis shows that AI infrastructure investment is targeting a very large market.

According to IMF and McKinsey reports, AI can significantly save labor hours.

For example, the time required to prepare a presentation could be reduced from 5 hours to 1 hour.

These calculations for economic value further solidify the justification for AI infrastructure investment.

Labor income displacement due to AI development can cause inevitable harm to workers. This concern is particularly high among professionals like tax accountants and regular accountants.

If data sharing becomes active, tax filing could reach a level of automation.

Similar to autonomous driving technology, a process for verifying AI technology's reliability is needed, and social acceptance and worker backlash will be major variables for industrial development.

To confirm the sustainability of the AI industry by 2030, there are several checkpoints. It's crucial to verify actual productivity improvements by companies; for example, checking if NH Investment & Securities' call center staff are replaced by AI, leading to cost savings and improved performance.

Other important indicators include whether AI companies can maintain profitability despite token price drops, the possibility of HBM and other semiconductor oversupply, and whether big tech companies maintain their CAPEX.

Finally, the ability to overcome social conflicts, such as worker backlash, will determine the continuous growth of the AI industry.

This can be interpreted as a process of complementing the side effects of technology, similar to cases like Instagram and other social media.

This regulation-focused trend is expected to bring positive narrative changes to the market.

Market attention is focused on the potential for enhanced safety and security to provide new momentum for AI industry development.