Overseas financial markets are experiencing severe turmoil, with concerns about the downward trend of the US economy and the prospects of AI technology. This morning, my colleagues provided a grounded analysis of recent economic and market issues. In this session, I will explore the new qualitative productivity opportunities for the global economy over the next five years, gazing at the distant horizon after the storm.
In the past month, the US market, led by AI giants, seems to have lost steam, with scholars and Wall Street reflecting on whether AI may have been overhyped and become a bubble. Entering August, coupled with signs of softening in the US economy and employment, as well as the unwinding of yen carry trades, global markets have been rocked. I believe that the adjustment and reflection on the AI industry are healthy, in line with the development laws of new things, and represent an adjustment after the capital market's extreme trend trading has gone too far. This does not negate the judgment that the world is still at the beginning of a new round of technological revolution. Over the next 5-10 years, we expect three major trends: the widespread promotion of AI artificial intelligence; the rise and widespread use of humanoid robots; and the medical revolution bringing overall longevity and health to humanity, which will profoundly impact the global economy and society. This is a major change that has not been seen in thirty years since the internet technology revolution and the globalization of industrial chains at the end of the 1990s.
Firstly, AI artificial intelligence. The emergence of ChatGPT at the end of 2022 ignited the debate on AI引爆 the next technological revolution. Despite the high market enthusiasm, it should be recognized that we are still at the initial stage of the AI technological revolution. Although the next two years will certainly be the years when AI applications emerge and land, there is still a long way to go before widespread adoption by the whole society, and its role in promoting productivity may only become apparent in a few years. Referring to the context of past technological innovations, including the internet revolution from the 1990s to the early 2000s, we believe that the impact of the AI revolution on the enterprise level will be in the following order: the first wave of beneficiaries will be enterprises that provide equipment and tools for AI, such as large model and GPU-related providers. The second stage will be equipment manufacturing enterprises with AI technology, such as consumer electronics like mobile phones. The third stage will be enterprises that use AI, including traditional enterprises, benefiting from AI-driven efficiency improvements. Currently, the beneficiaries of the first two stages have gradually emerged, and the third category will emerge in the third wave, ultimately bringing a broader impact on productivity.
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Over the past year, the AI trend has generally been in the first stage, with beneficiaries including well-known leaders in GPU chips such as NVIDIA and pioneers in large language models such as OpenAI. However, as the AI revolution gradually enters the second stage, from Apple to Samsung, from Bloomberg terminals to autonomous driving cars, new AI technologies have been sequentially equipped, becoming new selling points for ordinary consumers. The pull of these two stages on AI's own development tools and the capital goods GPUs it uses has already emerged. We estimate that in the next few years, US businesses will invest $3 trillion in AI. The third stage will be the widespread application of AI by a large number of enterprises in various scenarios to improve enterprise efficiency. This stage has not yet been reached, leading many people to worry whether the huge investment in AI will be a castle in the air? I believe this is related to the curve of technological progress.
The enhancement of productivity by AI tools can be divided into three stages: 1) General language tools for information retrieval and answering questions. 2) Custom models that can access company and private domain data, tailored to specific needs. 3) Custom models that can take action based on commands. Currently, we are still in the first stage, where most companies use general AI tools, such as ChatGPT, for information retrieval and organization. Between 2024 and the following two years, investment in custom tools and models will increase. Our technology team's survey of CIOs (Chief Information Officers) of US listed companies shows that 1/7 of the surveyed companies have identified AI as the company's top priority, indicating a trend towards large-scale adoption of AI technology in the medium and long term. However, due to investment returns, data volume, regulatory and technical obstacles, this stage will be relatively slow, and it will not be until the end of 2025 that we can see a broader increase in productivity. To reach the third stage, it will take several more years because further technological breakthroughs are needed to attract more enterprises to use AI on a large scale.
From some early empirical studies and company feedback, AI has already improved enterprise productivity to varying degrees, such as:
- Companies that have adopted AI-assisted programming tools, mainly large internet companies in Silicon Valley, such as Microsoft, Amazon AWS, Airbnb, PayPal, etc., have reported that their programming productivity has increased by about 20-50%.
- For drafting documents, AI tools can reduce the average writing time by at least 40%, and the output quality can also be improved by about 20% (a study by MIT on 453 professionals).
- Consultants using AI can complete 12% more work than before, and the quality of work has improved by at least 40% (a study by Harvard on 758 consultants from Boston Consulting Group).
- In the financial industry, AI tools are embedded in company databases to integrate research reports, macro models, corporate earnings, and asset allocation plans, thereby achieving intelligent advisory functions.**Emphasis on artistic creation and the generation of entertainment content is also gaining momentum. Feedback from Unity and Adobe indicates that the time required to create 3D content can be significantly reduced with the assistance of AI tools, leading to a 20% increase in creator productivity and saving an average of 8 hours per person per week.**
These are some exemplary industries currently benefiting from AI. As AI technology proliferates, it will further support productivity growth. Industry-wise, the most direct impact of AI is on the productive service sector. The enhancement of service industry productivity in the future is expected to become the main driver of Total Factor Productivity (TFP).
One significant industry judgment is that AI will drive the rise of humanoid robots. The four major bottlenecks faced by traditional robots were limited data volume, insufficient learning and observational capabilities, a lack of reasoning and predictive abilities, and limited human-robot interaction capabilities. The evolution of Large Language Models (LLMs) and General AI (GenAI) helps to overcome these obstacles. It significantly changes the learning ability and methods of robots, allowing them to observe and imitate behaviors in the physical world, communicate in natural language, and iterate in data centers. AI algorithms can automate repetitive requests, enhance predictive capabilities, enable virtual simulations, and significantly shorten the R&D cycle of robots.
By conducting a top-down and bottom-up analysis of the US labor market, considering the repetitiveness,危险性, and labor intensity of jobs across different industries, we have assessed the potential for humanoid robots to be implemented at the industry level. Industries with the best adaptability include agriculture, construction, mining, and building and ground cleaning and maintenance. However, in management, artistic design, and entertainment industries, the adaptability of humanoid robots is relatively lower.
In terms of cost, taking Tesla's Optimus Gen2 as an example, considering quotes from various components, we estimate the material cost is currently between $50,000 and $60,000 per unit. However, considering future economies of scale and Tesla's cooperation with efficient suppliers in Asia (including China), the manufacturing cost is expected to be reduced to a target of $20,000 per unit, thereby achieving a broader scale effect: we calculate that by 2040, humanoid robots in the US market will be applied to 8 million job positions, generating revenues exceeding $300 billion. By 2050, this number will further reach 63 million positions, generating revenues of $3 trillion.
In summary, the massive trillion-dollar investment in AI in the coming years inevitably comes with concerns about its returns, which is a common phenomenon at the beginning of each technology cycle. The widespread adoption of AI will still take a long time, but we remain optimistic about its ultimate ability to drive a significant increase in productivity as a result of the technological revolution.
Finally, the technological revolution also pays great attention to humanity itself: the new round of medical revolution is intensifying, bringing about a longevity economy. Three factors drive this transformation: 1. Changes in the healthcare system, 2. Advances in life sciences; 3. Transformations in pharmaceutical technology. The shift in the healthcare system stems from the challenges that aging issues in developed countries bring to medical services. ILC research shows that preventable diseases alone caused up to $1 trillion in personal and property losses in G20 countries in 2019. Among them, cardiovascular diseases, diabetes, and kidney diseases accounted for more than half. Therefore, drawing on the experience of the pioneers of aging—Japan, healthcare systems around the world are gradually transitioning from a past model dominated by post-treatment to one focused on prevention, health care, and early screening and diagnosis. Advances in life sciences and breakthroughs in pharmaceutical technology have formed a new ecosystem, focusing on addressing the causes behind diseases and aging.
Firstly, obesity-related kidney and diabetes diseases are one of the four major health killers of humanity, but there have been significant treatment advancements in the past two years, which will have a substantial economic impact on humanity in the future. There are over 1 billion people with obesity worldwide, and the number of overweight people is close to half, with a higher proportion in developed countries like the United States. However, GLP-1 drugs have emerged in recent years and have rapidly iterated, effectively helping people control their weight by reducing appetite. We predict that by 2030, the global weight loss drug market will reach $105 billion, and at that time, 20 million people in the United States alone will use highly effective anti-obesity drugs.
More importantly, the prevention of obesity will have a ripple effect on the overall economy. People's living habits will greatly improve. Our AlphaWise survey shows that once people start taking highly effective weight loss drugs, they will pay more attention to a healthy diet and balanced nutrition. This primarily affects the food and beverage industry. The reason is that anti-obesity drugs suppress appetite, leading to people consuming fewer calories. The latest research data shows that with Mounjaro drugs, the total calories consumed at lunch and dinner are half of the previous average of 1872. In contrast, the proportion of healthy foods in the diet has significantly increased, such as fruits, vegetables, poultry, and fish. Consumption of all other categories of food has decreased, especially snacks and candy. We have assessed the potential impact of weight loss drugs on various categories of consumption and expect that by 2035, the total consumption of ice cream, cakes, cookies, candy, chocolate, frozen pizza, fries, and carbonated beverages will be reduced by 4-5% compared to today.
In addition to preventing obesity and its related diseases, another major health killer: cancer, is also facing breakthroughs in medical technology, namely smart chemotherapy. This has become an effective method for treating various types of cancer, and we expect it to grow into a market worth at least $140 billion. Currently, there are more than 1567 ADC (Antibody-Drug Conjugates) drugs under development, and future ADCs are expected to be used to treat cancer types including breast cancer, lung cancer, gastric cancer, ovarian cancer, and pancreatic cancer. The transformation of the healthcare system into one focused on prevention, health care, and early screening and diagnosis, combined with advances in life sciences and breakthroughs in pharmaceutical technology, will enable people from this generation onwards to live not only longer but also healthier.This is my exploration of three global trends. Despite the current severe turmoil in overseas financial markets, concerns about the downward trend of the US economy, and the prospects of AI technology, it is important not to let fleeting clouds obscure our vision. After the capital market overshoots, adjustments are inevitable, but this does not negate that the world is still at the beginning of a new round of technological revolution. Over the next 5-10 years, the promotion of AI artificial intelligence, the rise of robots, and the longevity brought about by medical revolutions will be the main themes of industrial opportunities and the progress of social productivity.