
What happened
The IEEE's Technology Megatrends 2030 report identifies physical AI and robotics as one of five core breakthrough areas expected to reshape industries and daily life by 2030, alongside AI, energy, health and biotechnology, and space technology. The report examines 30 breakthrough technologies overall. Dejan Milojicic, chair of the IEEE Future Directions Committee Industry Advisory Board and an HPE Fellow, highlights human-AI interaction—moving beyond text toward speech, video, perception, and cognitive capabilities—as a key enabler of physical AI advancement.
Why it matters
Physical AI systems that perceive, interact with, and act in the physical world could make industrial robots and autonomous machines easier to supervise, teach, and collaborate with, with potential applications in manufacturing, healthcare, transportation, and agriculture. However, deploying intelligent machines in physical environments raises critical questions around reliability, cybersecurity, safety, and trust—particularly when AI systems make decisions affecting people, equipment, and infrastructure. Milojicic notes that power delivery remains the largest hurdle for broader commercial robot deployment, except in manufacturing where robots can stay continuously connected to a power source.
What to watch
Constrained use cases in manufacturing, healthcare, and agriculture are expected to advance first, followed by expansion as behaviors, risks, and opportunities become better understood. Military applications are already advancing rapidly, driven by substantial funding and demand. The industry's biggest cybersecurity vulnerability, according to Milojicic, lies in security exploits and power supply systems; backup solutions will be required given the growing power demand and dependency of AI factories.
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The IEEE's positioning of physical AI as a top megatrend reflects a fundamental shift in AI research and deployment. While generative AI has dominated technology discourse in recent years, the report signals that the next major phase will focus on systems that interact with and act in physical environments—a transition made possible by advances in AI itself. According to Milojicic, AI has been the primary driver enabling many other breakthroughs, from improving cybersecurity and energy efficiency to enabling new collaborative robotics algorithms. Importantly, non-AI advances in materials and sensors continue, but AI accelerates design exploration in these areas as well.
The emphasis on human-AI interaction as a critical enabler reflects a pragmatic understanding that robots and autonomous systems must work alongside humans, not replace them entirely—at least initially. Video recognition coupled with cognitive capabilities like anticipation will be particularly important for industrial robots. Milojicic notes that constrained environments—manufacturing with continuous power, healthcare, and agriculture—offer the safest proving grounds for early deployment, a strategy echoing how autonomous robots first appeared at airports and in tightly controlled factory spaces before expanding to less predictable settings.
The report's focus on trustworthy AI, cybersecurity, and safety acknowledges real vulnerabilities. Milojicic identifies security exploits and power supply integrity as the industry's most pressing concerns, particularly as AI factories' power dependency outpaces precedent. The challenge of balancing AI flexibility with industrial safety and regulatory compliance—a question Milojicic describes as "extremely well-posed"—will likely define how quickly deployment accelerates. He suggests trust will grow incrementally through deployment experience, allowing more autonomous operations as developers and operators build confidence and remove low-hanging safety hazards.
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