IEEE 发布 2030 技术大趋势报告：AI 融合五大领域重塑产业

By 2028, genetic engineering and gene therapy will be used frequently to treat a variety of diseases, thanks to advances in artificial intelligence, according to the recently released 2030 Technology Megatrends Report from IEEE. “We are seeing a fundamental shift in how technology evolves,” says IEEE Fellow Dejan Milojicic , chair of the IEEE Future Directions Committee ’s Industry Advisory Board, the group responsible for the report. “ Artificial intelligence is no longer operating in a vacuum; it is now deeply connected to our energy, infrastructure, and physical systems.” Milojicic, a Hewlett Packard Enterprise Fellow, is a vice president at HPE Labs in Milpitas, Calif. AI underpins many of the report’s 30 technologies and five “megatrends,” which are technology shifts with the potential to reshape industries and everyday life for decades. A megatrend isn’t a single breakthrough but a collection of related technologies. For the 2030 report, 166 experts—from 38 countries across six continents—drawn from industry, academia, and government identified 30 breakthrough technologies across the five megatrends: AI, energy, health, space, and physical AI. The experts graded the trends against five criteria: likelihood of success, impact to humanity, maturity, market adoption, and horizon to adoption. AI as a common thread Interconnected systems drive the megatrends, and the connection among them is AI. The report notes that AI technology is advancing faster than any previous revolution, including industrial, electrical, and digital. The pace has turned the technology into general-purpose infrastructure, Milojicic says. That evolution carries risks, though, the experts say. The report cites the lack of computing infrastructure and energy sources as constraints on the ability to scale up AI, and it says the technology’s growth will require reshaping the workforce. Workers have always needed to adapt to stay competitive, Milojicic says, adding that AI adoption isn’t an all-or-nothing approach. Businesses should decide when and how to apply it, he says. The experts say long-term success will require both technical capabilities and attention to the human-AI relationship. Conditions including trust, security, explainability, and policymaking will determine which AI-supported technologies are most likely to scale, they say. “This report shifts the conversation to something far more important: how these advances will intersect with one another to shape human lives,” Mary Ellen Randall , 2026 IEEE president and CEO, said in a news release about the report. “The data makes clear that trust, safety, and human connection must guide every major breakthrough in the decade ahead.” Health care is a high-impact bet The experts scored personalized medicine as the study’s highest-impact technology, at 4.93 out of 5, for its potential to improve human life. The report credits AI-driven breakthroughs in personalized diagnostics and therapeutic treatments, driven by innovative biotech startups. Within two years, the experts predict, genetic engineering and gene therapy will be used in therapeutic areas. Within five years, earlier disease diagnoses will move out of the lab and into day-to-day medical practice, the report predicts. Meanwhile, it says, researchers likely will be able to manufacture simple synthetic proteins—molecules engineered from scratch, rather than found in nature—to perform a specific job in the body, such as targeting a tumor or supplying a missing enzyme. Energy wakes up for AI Increased power demand by AI is outpacing the energy sector’s ability to keep up. Tech infrastructure—data centers, networks, and computing hardware—already uses an estimated 10 percent of electricity globally, according to the news release. The experts predict that within two to three years, energy storage will double in developed countries. The energy industry has been relatively dormant for years, Milojicic says, with little breakthrough innovation since the times of Thomas Edison and Nikola Tesla. “Data centers can ramp up within milliseconds, yet it takes months for the power and energy sector to ramp up,” he says. “The governments of various countries will have to rethink their approach to power generation to stay ahead of demand.” The experts cite the Jevons paradox —the idea that efficiency gains tend to increase overall consumption. As AI chip efficiency improves, organizations will run more hardware to build ever-larger frontier models—those advanced AI systems currently in development—the experts say. Data centers will draw as much power as grids can supply, leaving no surplus, the experts predict. Physical AI moves the fastest Physical AI refers to systems embedded within machines that sense and act in the world, including robots and autonomous vehicles. In the report, the category originally was called “hyper-automation and robotics,” a broad, software-driven process automation paired with physical machines. The Industry Advis