AI's New 'Scaling Up' Method: Hype or Hope?

The AI revolution is upon us, and Asia is at the forefront. Researchers claim to have discovered a new method of 'scaling up' AI, promising unprecedented growth and innovation. But is this just another tech bubble waiting to burst, or is it the real deal? Let's dive in and separate the hype from the hope.



The Hype: A New Method of 'Scaling Up' AI

The new method of 'scaling up' AI involves several key components that differentiate it from existing techniques. One of the primary components is the utilization of AI in various business functions. According to the information provided, "The number of companies in Asia using AI in at least one business function surpassed 70 percent in 2024." This indicates a significant shift towards integrating AI into core business operations, which was not as prevalent in the past.

Another key component is the investment in AI solutions. The data shows that "investment in AI solutions could triple in some countries, including Japan, South Korea, China, and India." This surge in investment is a clear indicator of the new method's focus on building capabilities and infrastructure to support AI adoption. In contrast, existing techniques may have relied more on incremental improvements and smaller-scale implementations.

The new method also emphasizes the importance of infrastructure, products, and data collection. The information states that "opportunities can be found across the AI value chain with infrastructure, products, and data collection in high demand." This highlights the need for a comprehensive approach that includes not just the development of AI technologies but also the supporting infrastructure and data management systems.

Furthermore, the new method involves a focus on specific sectors and regions. For example, "the banking and financial services sectors were among the first to embrace it, and the trend is set to carry on with more applications being launched." This targeted approach allows for more effective scaling of AI technologies within industries that have a clear need and potential for AI integration.

The Hope: Potential Benefits and Drawbacks

The new method of AI investment in Asia, particularly the projected CAGR of nearly 25 percent between 2023 and 2028, presents several potential benefits and drawbacks that could significantly impact the AI industry and the broader economy.

# Potential Benefits:

1. Economic Growth and Job Creation:
- Economic Boost: AI investment in Asia is expected to surpass USD110 billion by 2028. This substantial investment is likely to drive economic growth, as more companies from various industries embrace AI's potential. For instance, ASEAN believes AI could boost the region’s gross domestic product by as much as 18 percent by 2030.
- Job Creation: The increased adoption of AI will create new job opportunities across the AI value chain, including infrastructure, products, and data collection. This will not only support the AI industry but also stimulate the broader economy by creating employment in related sectors.

2. Technological Advancement:
- Innovation: The high demand for AI-powered solutions will drive innovation. For example, the healthcare industry is starting to incorporate AI into processes like colonoscopies to improve detection, and numerous companies in China have incorporated DeepSeek into their operations.
- Infrastructure Development: The need for AI-related infrastructure, such as data centers and cloud computing, will lead to significant investments in these areas. Countries like Japan and South Korea are seeking more niche facilities capable of handling AI-specific functions, while India, Indonesia, and Vietnam are welcoming foreign data center operators.

3. Competitive Advantage:
- Global Leadership: Asia's rapid adoption of AI could position the region as a global leader in AI technology. Most countries now have a national AI framework in place, and many of the largest players globally, including Google, Amazon, Microsoft, and Nvidia, are scaling their efforts in the region.
- Market Expansion: The growing demand for AI solutions in sectors like banking, healthcare, and manufacturing will create new market opportunities. For example, the banking and financial services sectors were among the first to embrace AI, and the trend is set to continue with more applications being launched.

# Potential Drawbacks:

1. Economic Inequality:
- Wealth Concentration: The valuation gap between the biggest stocks (the megacaps) and the rest is unlikely to persist indefinitely. If the broader corporate universe does not see the clear use case of these technologies and are unwilling to pay for them, then a “catch down” scenario is more likely, which could exacerbate economic inequality.
- Regional Disparities: While technologically advanced countries like Japan and South Korea are leading the AI race, less developed markets in Southeast Asia may struggle to keep up. This could widen the economic gap between these regions.

2. Technological Dependence:
- Over-Reliance on AI: As more industries adopt AI, there is a risk of over-reliance on technology, which could lead to job displacement in certain sectors. For example, the manufacturing and logistics sectors are investing heavily in AI to optimize supply chains and eliminate waste, which could result in job losses.
- Security Risks: The growing demand for AI-powered security solutions highlights the need to address safety issues in the digital economy. Countries focusing on expanding their digital economies must also invest in cybersecurity to protect against potential threats.

3. Regulatory Challenges:
- Legal and Ethical Issues: The rapid advancement of AI technology could outpace regulatory frameworks, leading to legal and ethical challenges. For instance, laws and regulations involving copyright could evolve and vary across geographies, affecting investments and the adoption of AI solutions.
- Data Privacy: The increased collection and use of data for AI applications raise concerns about data privacy and security. Companies and governments must ensure that data is handled responsibly to maintain public trust in AI technology.

The Skepticism: Addressing Concerns

The main reasons for skepticism surrounding the new method of AI investments in Asia can be attributed to several factors, including the rapid pace of technological change, the concentration of investments in a few megacap companies, and the potential for a valuation gap between these companies and the rest of the market. These concerns can be addressed or mitigated through a more diversified investment approach and a deeper understanding of the AI value chain.

Firstly, the rapid pace of technological change can make it difficult to predict the future of AI investments. As noted, "It is now increasingly consensus that a booming artificial intelligence (AI) industry is driving the next technology revolution. For investors, however, the most important question to address is whether the expectations embedded in financial markets today project a realistic path ahead." This uncertainty can be mitigated by investing in a diversified portfolio of AI-related stocks and ETFs, rather than focusing on a few megacap companies. For example, Forbes Advisor has identified 10 of the best AI stocks, each with different risk profiles and growth potential. By investing in a mix of these stocks, investors can reduce their exposure to any single company or sector.

Secondly, the concentration of investments in a few megacap companies can create a valuation gap between these companies and the rest of the market. As noted, "The valuation gap between the biggest stocks (the megacaps) and the rest is unlikely to persist indefinitely. If the broad AI ecosystem generates sufficient revenues to justify the earnings expectations already assumed for a handful of companies, the 'rest' should catch up over time." This concern can be addressed by investing in companies across the AI value chain, rather than focusing on a few megacap companies. For example, investors can consider investing in AI hardware companies, such as Nvidia and ASML, as well as AI hyperscalers, such as Amazon's Web Services business and Google Cloud. By investing in a diversified portfolio of AI-related companies, investors can reduce their exposure to any single company or sector and take advantage of the growth potential across the entire AI value chain.

Finally, the potential for a valuation gap between megacap companies and the rest of the market can be mitigated by focusing on companies with strong fundamentals and a proven track record of earnings growth. As noted, "The strong fundamentals of the megacaps, both relative to other parts of the S&P 500 today, as well as relative to the 2000s tech bubble, provide some comfort that a major 'catch down' is unlikely." For example, Nvidia has a high forecasted 5-year EPS growth of 46.5% and a strong financial health rating from Morningstar. By investing in companies with strong fundamentals and a proven track record of earnings growth, investors can reduce their exposure to valuation risk and take advantage of the growth potential of the AI industry.

The Consequence: A Balanced Future for AI

The new method of AI investment in Asia presents both significant opportunities and challenges. While the potential benefits of economic growth, technological advancement, and competitive advantage are substantial, the drawbacks of economic inequality, technological dependence, and regulatory challenges must be carefully managed to ensure a balanced and sustainable future for the AI industry and the broader economy.

Investors and policymakers must work together to address these concerns and create an environment that fosters innovation while protecting against the risks of over-reliance on technology and economic inequality. By taking a diversified investment approach and focusing on companies with strong fundamentals, investors can reduce their exposure to valuation risk and take advantage of the growth potential of the AI industry.

In conclusion, the new method of AI investment in Asia is a double-edged sword. While it holds the promise of unprecedented growth and innovation, it also presents significant challenges that must be carefully managed. By addressing these concerns and taking a balanced approach, we can ensure a sustainable and prosperous future for the AI industry and the broader economy.