Bain & Company: By 2027, the AI software and hardware market size will reach $780 billion to $990 billion.

Currently, the global technology industry has steadily entered the AI calculation stage. Cloud service providers, enterprises, and technology suppliers have reached unprecedented new heights in their investments in artificial intelligence. According to the "2024 Global High-Tech Industry Report" released by Bain & Company, the AI software and hardware market is expected to continue growing at a rate of 40% to 55% per year, reaching a market size of $780 billion to $990 billion by 2027. Technology leaders lead disruptive trends, strengthen resource advantages, and win lasting competitive advantage Bain found that top technology companies are showing greater resilience, not only leading the industry but also continuously expanding their market share. Their key to success lies in accurately identifying disruptive technology trends and successfully achieving scalability and commercialization, ultimately gaining a richer profit pool. The realization of large-scale innovation relies on strong computing power, network, and data resources, which further solidifies the industry giants' leading position thanks to their own advantages. Xin Cheng, Global Partner at Bain and Chairman of the High-Tech Business in Greater China, stated that in recent years, the most valuable technology companies have demonstrated extraordinary resilience, maintaining their market leadership position for a long time and continuously capturing market share. These successful companies all have a common winning strategy, which is to accurately identify disruptive technology trends, focus on achieving scalability and commercialization, and make the leap from "industry leader" to "change leader." At present, whoever can fully unleash the disruptive potential of AI will become the ultimate winner. Valuation Focus on the 40 Rule, Scope Investment and Operational Optimization Driving the Future Bain believes that in an environment of high interest rates and growth uncertainty, the heat of investment transactions in the technology field has decreased, and valuation standards have shifted from purely pursuing growth to paying more attention to the balance between revenue and cash flow. Investors need to optimize operations, increase profit margins and growth to respond to market challenges. In addition, scope acquisitions remain an important strategy, but due to the high difficulty of product portfolio integration, companies must carefully preserve key core capabilities while pursuing revenue and cost synergies to ensure long-term competitiveness. Terry Cheng, Global Partner at Bain and Chairman of the Mergers and Acquisitions Business in Greater China, stated that as the driving factors of technology industry transactions gradually change, investment strategies need to be adjusted accordingly. Currently, transaction valuation tends to follow the "40 Rule," emphasizing a balance between growth rates and profit margins. In recent years, technology companies have begun to shift their merger and acquisition activities towards scope transactions, aiming to acquire new capabilities, products, or markets through acquisitions. This change is so significant that in the past six years, scope transactions accounted for nearly 80% of all technology industry mergers and acquisitions. Generative AI Accelerates Rise, Unlocking Business Potential, Efficiency Soaring with the Market Bain found that the potential market growth rate of generative AI has exceeded the development speed of the software and hardware industries over the past decades. Enterprises are increasing their investment in generative AI in areas such as software development and customer support, leading to significant efficiency gains. Meanwhile, Bain's rich practical experience in enterprise AI transformation further drives the practical application of AI technology. According to Bain's estimation, systematic transformation will unleash huge potential in five key areas: 1) new products/features; 2) customer service/contact centers; 3) sales and marketing; 4) software/product development; 5) back-office/other department efficiency improvements. In China, the disruptive impact and enormous potential of generative AI have become the focus of investors, especially in strategic layouts within investment portfolios. The key drivers for the rapid development of the domestic AI industry come from two aspects: the extensive expansion of multi-scenario application and the continuous improvement of computing capabilities. Based on this, Bain has observed six main areas that, driven by dual promotion of actual demand and technological progress, are becoming important engines for accelerating the development of AI in China: 1) E-commerce: Massive user base and multi-category demand are driving the acceleration of AI in personalized recommendations, intelligent inventory, and automated customer service, laying a solid foundation for the full-process intelligence upgrade from consumer insights to supply chain management. 2) Intelligent transportation: Driven by the needs for transportation efficiency, safety, policy support, China has rapidly realized the implementation of autonomous driving, vehicle-road collaboration, and smart transportation systems, promoting the rapid iteration of AI in perception, decision-making, and city management, and providing diverse scenarios for algorithm testing. 3) Medical and health: Due to the uneven distribution of the population and medical resources, the demand for efficient diagnosis and precise treatment has emerged. This has driven the deep application of AI in medical imaging, intelligent diagnosis, drug development, personal health management, accelerating the construction of the "Internet + medical" and digital medical ecology. 4) Cloud computing driving large-scale AI implementations: The rapid growth of the cloud computing market and the massive computing power provided by tech giants have provided core support for the training, deployment, and inference of AI. Efficient and elastic cloud services effectively lower the innovation threshold for enterprises, accelerating the popularization and commercialization of AI in various industries. 5) Edge computing meets real-time needs in multiple scenarios: Driven by industries such as intelligent manufacturing, smart cities, and the Internet of Vehicles, edge computing processes data through local or nearby nodes, providing AI algorithms with low-latency, real-time decision-making environments, further expanding the space for distributed terminal applications and industrial upgrades. 6) AI supercomputing centers accelerate industrial upgrading: World-class AI supercomputing centers built in Guangzhou, Shenzhen, Wuxi, and other places provide unprecedented computing power for large-scale deep learning models. With the support of these supercomputing resources, technologies such as natural language processing achieve rapid breakthroughs and application landing, significantly shortening the cycle from research and development to commercialization.