Standing at the starting point of 2026, looking ahead to the development of global artificial intelligence (AI), multiple variables such as technology, industry, energy, and governance are intertwined, which will jointly shape this crucial year.

Relevant institutions predict that an increasing number of top AI enterprises will focus on enhancing the reasoning capabilities of large models and the task execution abilities of intelligent agents, driving AI to evolve from "being able to generate" to "being able to plan and act". A large number of enterprise applications will incorporate task-oriented AI intelligent agents.

Accompanying technological breakthroughs is energy pressure, with global data center electricity consumption expected to remain high. At the governance level, it is anticipated that national governance measures will be implemented at an accelerated pace.

Technology: Large model competitions drive the application of intelligent agents

In 2026, the trend of intense competition among large AI models will continue. Companies such as OpenAI, Google, and Deep Search will release the latest versions of larger or more efficient large models.

Li Feifei, a renowned AI researcher and professor at Stanford University in the United States, recently wrote that spatial intelligence is the next frontier of AI. Based on successfully handling text data and multimodal data, large models are making progress in spatial comprehension, with the goal of developing models capable of complex semantic, physical, geometric, and dynamic interactions.

Meanwhile, intelligent agents are likely to become increasingly prevalent, and artificial intelligence will integrate more closely with people's lives. Traditional AI systems operate on a question-and-answer basis, whereas intelligent agents, equipped with deep goal orientation, multi-step planning capabilities, and proficiency in specific tasks, will be increasingly applied to various work scenarios. According to the US-based consulting firm Gartner, by 2026, 40% of enterprise applications will incorporate task-oriented AI intelligent agents, compared to less than 5% in 2025.

Some intelligent agents can already automatically click buttons, fill out forms, and switch between different software. For example, Microsoft Office intelligent agents can automatically create spreadsheets and documents after conversing with operators, and quickly produce presentations. This means that AI is no longer an auxiliary tool, but rather possesses certain attributes of a digital employee to a certain extent.

In an interview with reporters, Hu Yanping, a distinguished professor at Shanghai University of Finance and Economics, said that the superficial value of AI to enterprises is to reduce costs and improve efficiency, while the deep value is to drive paradigm shifts with bursting capabilities. Three types of transformations are taking place: in terms of cost structure, intelligent agent systems not only break through the limitations of traditional labor in time and space, management cost efficiency, but also break through the bottleneck of creative output capacity; in terms of organizational form, enterprises can use AI to provide capabilities such as dynamic perception, real-time interaction, intelligent creation, behavior achievement, and organizational collaboration, thus evolving into human-intelligence collaboration in the era of intelligent economy; in terms of competition logic, it shifts from scale standardization to the integration of scale and individuality, from industrial division and cooperation to ecological connection and collaboration, and from traditional factor competition to intelligent-dominated capability factor competition.

Industry: "Smart Manufacturing" Ushers in an Opportunity Period

In the industrial sector, the integration of digital twins and AI agents is reshaping the product design process, ushering in a period of strategic opportunities for "smart manufacturing".

According to the prediction of IDC, by 2026, 40% of manufacturers equipped with production scheduling systems will upgrade to AI-driven production scheduling, achieving autonomous operation of production resource management; by 2028, 65% of the world's top 1000 manufacturing enterprises will combine intelligent agents with design and simulation tools to continuously verify design changes and configuration schemes.

Ramin Hasanian, co-founder and CEO of Liquid AI, a US-based company, believes that this year will be the year of "active agents". He said that most AI assistants and the like are currently "reactive agents", but when AI runs quickly on devices and is always online, it can actively work for humans, and tasks can be completed in the background.

Some experts predict that this trend may be significantly reflected in China's manufacturing industry. Factory production plans will be increasingly optimized in real-time by AI agents based on changes in orders, equipment status, and supply chain fluctuations.

Hu Yanping believes that for China's manufacturing industry, the opportunities presented by the wave of industrial intelligence outweigh the challenges. The transition from manufacturing to "smart manufacturing" will greatly enhance Chinese enterprises' market perception, product innovation, and international competitiveness. It also signifies the gradual emergence of a modern industrial cluster based on emerging and future industries, empowered, driven, and catalyzed by AI. "Smart Manufacturing in China" is expected to drive China's economy towards the next long-term development cycle.

Energy: Data center power consumption remains high

In 2026, the energy pressure brought about by the large-scale application of AI will continue to be high, and the demand for green energy transformation will also increase. According to a report released by the International Energy Agency in April 2025, by 2030, the electricity demand of global data centers is expected to more than double, reaching approximately 945 terawatt-hours, with artificial intelligence becoming the main driving force behind this surge in electricity consumption.

In her keynote speech at the Consumer Electronics Show (CES) in Las Vegas, Lisa Su, CEO of American semiconductor company Advanced Micro Devices (AMD), stated that the number of active AI users worldwide has now exceeded 1 billion and is expected to surpass 5 billion in the future. The current computing power is far from sufficient to support the vision of AI being everywhere, and to achieve this, global computing power must be increased by 100 times in the next few years.

Driven by factors such as the continuous increase in AI computing power load, increasingly stringent energy efficiency control regulations, and the rapid implementation of low-carbon digital infrastructure, the global green AI data center market is poised for robust expansion. According to a report by Canada's Priority Research Corporation, the global green AI data center market is expected to reach $67.6 billion in 2026 and could grow to approximately $123 billion by 2035.

Industry insiders believe that China's efforts to strengthen its industrial foundation in terms of supply capacity, layout optimization, and green and low-carbon development will provide sustainable resources and engineering system support for AI development.

Liu Wei, director of the Human-Computer Interaction and Cognitive Engineering Laboratory at Beijing University of Posts and Telecommunications, said that to advance the construction of AI infrastructure under the constraints of the "dual carbon" goals, on the one hand, it is necessary to accelerate the research and development of high-energy efficiency chips and ensure the stable supply of new energy electricity; on the other hand, there is an urgent need to break through the large-scale application of new-generation cooling technology and enhance the level of intelligent energy management. China will continue to explore a sustainable path for the coordinated development of computing power and green energy.

Governance: AI institutional supply is beginning to accelerate

2026 is also seen as a crucial year for the accelerated implementation of global AI governance measures, with the focus of relevant industries potentially shifting from ideological debates to compliance capabilities, industrial adaptability, and cross-border collaboration.

The "Artificial Intelligence Act" passed by the European Union in 2024 is the world's first law to comprehensively regulate AI. The relevant rules will be implemented in stages, with most of them taking effect from August 2026. In December 2025, the US federal government called for unified regulatory rules at the federal level in the field of artificial intelligence, and it is expected that more corresponding measures will be introduced in 2026.

In China, the path for AI governance is becoming increasingly clear. The "Opinions on Further Implementing the 'Artificial Intelligence Plus' Initiative," issued by the State Council in August 2025, not only promotes the extensive and deep integration of artificial intelligence with various industries and fields of economic and social development, but also points out the need to improve laws, regulations, and ethical norms related to artificial intelligence, and to advance legislative work related to the healthy development of artificial intelligence.

The international community's attention to China's AI development path has shifted from "scale expansion" to "institutional supply and governance practices". An article published on the World Economic Forum's website stated that China's long-term AI development strategy, supported by an adaptable regulatory system and solid infrastructure, sets a global example and demonstrates how to strike a balance between innovation and safety. An editorial in the British journal "Nature" said, "China is leading global AI governance" and called on other countries to participate in addressing the common challenges brought by AI development.

Looking ahead to 2026, the global development of AI will not only be about competing to see whose model is stronger, but also about who can integrate safety, compliance, energy consumption, and industrial implementation into a single system, and form higher capabilities for rule compatibility and mutual recognition in international collaboration.