Abstract
As we approach the end of 2025, the artificial intelligence landscape has shifted dramatically from the passive generative models of the early 2020s to autonomous “Agentic AI.” This paper argues that the next decade of global competition will not be defined merely by who possesses the most powerful models, but by which nations can successfully integrate autonomous agents into their economic infrastructure. While the United States currently maintains a hegemony in computing power and model generation, the proliferation of specialized, efficient Chinese models, combined with regulatory friction in Europe, suggests a fracturing of the global market. The implications for the next decade point toward a radical reorganization of labor, where economic supremacy will belong to nations that transition from “using” tools to “managing” synthetic workforces. There are, of course, many concerns that accompany this autonomous AI age, such as misalignment and the risk of AI favoring its own goals ahead of ours, thereby rendering us obsolete. If you’d like to read more on the topic of AI/human misalignment, please see my previous article on that topic here: https://mistykmedia.com/the-ai-misalignment-dilemna-and-the-need-for-global-regulations/.
1. The Technological Pivot: The Rise of Agentic and Multimodal Systems
The most significant trend of late 2025 is the graduation of AI from “chatbot” to “agent.” Unlike the Large Language Models (LLMs) of 2023, which required constant human prompting, the emerging class of Agentic AI possesses the capacity for autonomous reasoning, planning, and execution of complex workflows [ref:21, 22]. These systems do not simply answer questions; they perform labor. They are capable of navigating software environments, managing supply chains, and executing code with minimal human oversight [ref:27].
Parallel to this is the standardization of Multimodal AI, where models natively process text, image, audio, and sensory data simultaneously. This capability has been crucial for the deployment of AI in physical industries, such as manufacturing and robotics, allowing systems to “see” and “hear” their environments rather than just processing text descriptions of them [ref:26, 29]. This shift marks the beginning of the “actionable” phase of AI, where the value proposition moves from information retrieval to tangible economic output [ref:24].
2. The Geopolitical Chessboard: Hegemony vs. Asymmetry
The international market has calcified into a high-stakes competition primarily between the United States and China, with other regions struggling to carve out influence.
United States: The U.S. retains a distinct advantage in high-end compute and foundational innovation. In 2024 alone, U.S. institutions produced 40 notable AI models compared to China’s 15, and the U.S. controls an estimated 74% of global high-end AI compute capacity [ref:1, 2]. Private investment in the U.S. continues to dwarf competitors, reaching nearly $110 billion annually—over ten times that of China [ref:10]. The U.S. strategy relies on “brute force” superiority in hardware and the scaling of massive, generalized models.
China: Facing export controls and hardware restrictions, China has pivoted toward an asymmetric strategy. Rather than competing solely on model size, Chinese firms are dominating the market for specialized, low-cost, and efficient models that run on restricted hardware [ref:8]. China is also aggressively integrating AI into manufacturing, with estimates suggesting over 60% of large manufacturers will be AI-integrated by late 2025 [ref:7]. Furthermore, China is projected to capture the largest share of the global software market (13%) by 2033, leveraging these efficiencies [ref:3].
Europe: The European Union finds itself in a precarious position, leading in ethics and regulation but lagging significantly in adoption and production. As of 2024, only 13.5% of EU enterprises had deployed AI technologies, highlighting a gap between regulatory ambition and industrial reality [ref:9, 6].
3. Implications for the Next Decade (2025–2035)
The transition to Agentic AI will trigger profound economic and societal shifts over the next ten years.
The Productivity Boom and the Inequality Trap
Economists forecast that the widespread adoption of Agentic AI could boost global GDP by 5–7% and increase annual labor productivity by 1.5% [ref:13, 16]. By 2035, AI is projected to increase GDP by 1.5% solely through productivity gains, a figure that rises to nearly 3% by 2055 [ref:11]. However, this growth will likely be uneven. The benefits of automation tend to accrue to capital owners and highly skilled workers who can leverage AI agents, potentially deepening inequality within developed nations [ref:18].
The Great Labor Reorganization
We are entering the “Great Labor Market Reorganization.” The World Economic Forum predicts that while AI will create jobs equivalent to 14% of today’s employment, it will simultaneously displace 92 million roles [ref:20]. The disruption will not be limited to blue-collar work; the “agentic” nature of new models means they can replicate core tasks in white-collar professions, including analysis, coding, and administration [ref:14, 19]. The primary skill of the next decade will not be *doing* the work, but *orchestrating* the agents that do it.
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