30 technologies are racing towards 2030: Which ones could emerge as the big winners?

That is the broad picture from the Institute of Electrical and Electronics Engineers (IEEE) Future Directions Megatrends 2030 report, which assesses 30 technologies across five areas: AI, energy, health, space technology and physical AI. The assessment draws on views from 166 members of the IEEE Santa Clara Valley Section/Future Directions Industry Advisory Board Committee.

The report evaluates the technologies on factors including their expected success, maturity, market adoption, impact on humanity and estimated time to adoption.

Its central argument is that these technologies should not be viewed as isolated developments. AI needs computing power and energy, robotics depends on AI and advanced sensing, healthcare can use AI to develop personalized treatments, while space technologies require advances in materials, computing and autonomous systems.

“The next decade will be shaped not by isolated breakthroughs, but by interdependencies among AI, energy, and physical systems,” the report states.

That makes the technology race more complicated than simply asking which technology will be the most powerful by 2030. Some technologies could become important because they reach consumers quickly, while others could become critical infrastructure or deliver significant benefits to healthcare and other sectors.

Which technologies could move fastest?

AI has one of the strongest positions in the IEEE assessment, with several technologies expected to make significant progress before 2030.

The AI category includes energy-efficient AI accelerators, new types of computing, agentic and multimodal AI, explainable AI, data privacy and safety systems, and public-domain or synthetic training data.

AI accelerators could see some of the fastest progress. The report expects them to become more energy efficient within two years as demand for computing power continues to grow.

However, greater efficiency does not necessarily mean lower overall energy consumption. The report points to the Jevons paradox, under which efficiency improvements can encourage greater use. If AI becomes cheaper and more efficient to run, companies could deploy more systems and consume the additional available computing capacity.

New forms of computing are another technology to watch. The report groups quantum, analogue, in-memory and neuromorphic computing under this category and expects one or more of these approaches to gain ground within five years.

Agentic and multimodal AI also receive a relatively short adoption timeline. The report expects multimodal AI to produce important scientific and practical applications in less than two years. These systems can work across text, images, audio and video rather than relying only on text.

Explainable AI could become increasingly important as businesses and governments use AI for more consequential decisions. IEEE expects AI systems to become more transparent, controllable and explainable within five years.

The report also sees growing importance for data privacy, safety and guardrails, particularly as sovereign AI systems and enterprise and consumer data centres take greater responsibility for local data and regulatory requirements.

Public-domain and synthetic training data form another part of the AI outlook. IEEE expects guidelines covering intellectual property, privacy and data quality to emerge within two years.

Among the 30 technologies, human-AI interaction stands out for its combination of expected success and short adoption timeline. The report expects AI interaction to move beyond predominantly text-based systems towards greater use of audio and video within two to three years.

Why could physical AI be another major winner?

The report gives physical AI an especially strong position for technical advancement over the next four years, putting it close to AI in the overall assessment.

Physical AI refers to systems that allow intelligence to operate in the physical world, including robots, autonomous machines and systems capable of sensing and responding to their surroundings.

Energy-efficient intelligence is one part of this trend. IEEE expects edge AI and hybrid computing architectures to improve energy efficiency within two years.

Robotics could also move closer to wider deployment. The report expects autonomous and collaborative robots to work together in areas such as transportation.

Advances in robotic materials could allow machines to interact more effectively with people. The report expects progress in materials for robotic skins, tissue and sensors that more closely replicate aspects of human perception.

Tactile and advanced edge sensing could further improve robotic capabilities. IEEE expects factory humanoids with tactile and haptic feedback within two to five years.

Cybersecurity will also become increasingly important as AI-powered machines and systems become connected to wider networks. The report expects cybersecurity to extend across the software development and deployment chain, from edge devices to enterprise IT systems.

This makes physical AI more than a robotics story. Its development depends on advances in AI, computing, sensing, materials and cybersecurity.

Which energy technologies could support the AI boom?

Energy is a critical part of the technology race because increasingly powerful AI systems and data centres require large amounts of electricity.

The IEEE report assesses six energy technologies: distributed energy resources and microgrids, energy storage, carbon capture, fusion, clean mining, and energy safety and guardrails.

Energy storage has one of the strongest positions in the entire assessment and is described as the most mature of the 30 technologies. IEEE expects storage capacity in developed countries to double within two to three years and become a meaningful additional source of power.

Microgrids could also see relatively rapid adoption. The report expects them to become widespread for IT and city infrastructure within two to five years. Their ability to manage electricity locally could become increasingly relevant as power demand from computing infrastructure grows.

Carbon capture has a longer path. IEEE expects greater attention to greenhouse-gas removal technologies within five years.

Fusion is further away. The report puts its likely arrival at around 10 to 15 years, meaning it may remain a longer-term technology rather than becoming a major commercial energy source by 2030.

Clean mining is another area where AI could play a supporting role, with the report expecting AI systems to contribute to safer and cleaner mining operations.

Energy safety and guardrails complete the category, reflecting the need for systems and controls that can manage the risks associated with increasingly complex energy infrastructure.

Which technologies could have the biggest impact on people?

Healthcare contains some of the technologies that IEEE believes could have the greatest impact on humanity. Personalised medicine has the highest potential impact on humanity among the 30 technologies assessed by the report.

The technology could allow doctors to tailor diagnostics and treatments to individual patients. IEEE expects startups to continue developing personalised diagnostic and therapeutic technologies over the next five years.

Genetic engineering and gene therapy could also move into more areas of healthcare. The report expects some applications to approach mainstream care within two years.

Early disease diagnostics and biomarkers could move from laboratories into wider use within five years, according to the assessment.

AI could also accelerate molecular therapeutics by helping researchers develop more precise and personalised treatments for specific diseases.

Protein synthesis is another technology expected to make progress, with IEEE forecasting deterministic methods for manufacturing simple proteins within five years.

The sixth health technology, described as “understanding life,” has a much longer horizon. It focuses on deeper scientific questions about life and consciousness, with the report expecting new theories in this area within seven years.

The contrast within healthcare is significant. Some technologies could move towards practical applications within a few years, while others may primarily produce scientific advances before becoming commercially useful.

Why are space technologies mostly longer-term bets?

Space technology occupies a different position in the IEEE assessment. Compared with AI, physical AI and health technologies, several space technologies have longer adoption timelines because they require significant infrastructure, investment and technological development.

The six technologies include new materials, clean energy generation in space, cheaper mass transportation, space agriculture, semiconductor manufacturing in space and orbital debris removal.

New materials could eventually be produced in space that are difficult to manufacture on Earth. Space-based clean energy has a longer horizon, with IEEE placing it at around 10 years.

Reusable rockets could reduce the cost of reaching space, with the report expecting reusable launch systems to become an order of magnitude more affordable.

Space agriculture could gain momentum as space activity expands, although the report does not suggest immediate mass adoption.

Semiconductor manufacturing could eventually use space-based production for some stages of the manufacturing process.

Orbital debris removal could also become a commercial activity, with IEEE expecting space-based garbage collection to develop within 10 years.

These technologies therefore represent longer-term opportunities rather than the fastest-moving technologies in the 2030 assessment.

So which technologies could be the big winners?

The IEEE report does not identify a single technology as the winner. Instead, its assessment points towards different types of potential winners.

Physical AI and AI have strong near-term momentum. Human-AI interaction could reach users quickly. Energy storage is already relatively mature, while personalised medicine has the highest potential impact on humanity.

Other technologies could become important because they enable these developments. Explainable AI, cybersecurity, data privacy and energy efficiency may not attract as much attention as generative AI or humanoid robots, but they could determine whether those technologies can scale safely and reliably.

The report also expects AI adoption to accelerate workforce changes, with workers needing to reskill as automation expands across different parts of the economy.

At the same time, IEEE cautions against treating the predictions as guaranteed outcomes. The authors acknowledge that technology experts can have a natural bias towards technological progress. The report therefore also considers risk and reward, including technologies that could deliver substantial benefits despite higher risks.

A separate survey of about 300 IEEE members produced some differences from the main assessment. Survey participants showed greater confidence in health technologies but lower confidence in AI. They also viewed “understanding life” more positively while expressing less confidence in guaranteed data privacy, safety and guardrails.

The differences show why the technology race cannot be reduced to a simple ranking.

Some technologies may succeed because they reach consumers quickly. Others may become essential infrastructure. Some could take years to mature but eventually produce major scientific or economic benefits.

The strongest theme running through the report is convergence.

AI requires energy and computing infrastructure. Robots require AI, sensors and advanced materials. Healthcare can use AI to accelerate diagnostics and treatments. Space systems require autonomous machines, better computing and new materials.

The report’s technology map also groups the 30 technologies according to their relationships across fundamentals, core technologies, management and governance, applied technologies, and tools and data. IEEE cautions that these clusters show correlations rather than an architectural system.

That means the biggest opportunity may not come from one technology operating alone. It could emerge where several technologies meet.

AI and robotics could create more capable autonomous machines. AI and healthcare could accelerate personalized treatments. AI and energy could improve the management of power systems. Advances in computing could support all of them.

By 2030, therefore, the technology winners may be the systems that can move beyond laboratories and pilot projects, solve real-world problems, scale at reasonable cost and gain enough trust for widespread adoption.

The IEEE assessment points to a strong near-term group — physical AI, AI, human-AI interaction, energy storage and personalised medicine — while technologies such as fusion, space-based energy and deeper research into life remain longer-term bets.

The race to 2030 is ultimately not just about which technology becomes the most powerful. It is about which technologies can become reliable, affordable and widely used, and which supporting technologies allow them to scale.