What’s next? This is a question we often ask at Nature Electronics. It arises when thinking about the directions of different research fields; when thinking about the applications of different devices; and when thinking about the implications of different technologies. It is also the question at the heart of discussions about our technology of the year.

Now in its eighth edition, our technology of the year is intended to highlight an area that has achieved a key breakthrough or reached an important moment of development. Previous choices include edge computing in 2019 and 5G, the fifth generation of wireless communications technology, in 2020. In 2021, we highlighted the impact of the coronavirus pandemic on digital technology, and in 2022, explored the future of transport. We then chose brain–computer interfaces in 2023, three-dimensional electronics in 2024, and quantum computing in 2025. For 2026, we have chosen robotics.

Robotics has a detailed history in both academia and industry, not to mention a wider cultural impact — in books, in movies — unmatched by few other leading research fields. In recent years, and like many technologies, it has been overshadowed by advances in machine learning and artificial intelligence (AI). So why now?

Here we note the increasing capabilities of various robotic systems, driven by those recent advances in machine learning and AI but accompanied by an increasing focus on the importance of embodied AI. We note the increasing presence of robotics in daily life, from delivery drones to humanoid robots, and a potential shift in the mindset of many people about the place robots may have in society. We note the increasing use of autonomous drones and other autonomous weaponry in warfare, and the urgent ethical and legal questions this raises. We have, in short, reached a critical juncture in the detailed history of robotics, and a critical moment to reflect on the direction — and consequences — of the technology.

In this issue, and throughout the year, we will consider what’s next for robotics. This will include an exploration of advances in the underlying (electronic) technology, across the different length scales and platforms the field offers. But it will also involve an exploration of the potential applications and implications — good and bad — of the technology. We begin with some of the smallest robotic devices, where Oliver Schmidt, Vineeth Bandari and John McCaskill discuss in a Comment article the challenges involved in building microscopic robots with onboard intelligent control.

Such microrobots, which rely on integrated silicon chips and have recently become mass-producible, could be used to navigate biological fluids or explore confined or hazardous spaces. There are, however, two distinct routes to fabricating them: a body-first approach and a brain-first approach. The researchers — who are based at Chemnitz University of Technology — examine the difficulties and potential of each of these approaches, and also how much onboard intelligence is actually required for robots to function effectively at the microscale.

Moving to a slightly larger scale, and in a further Comment article in this issue, Giovanni Traverso, Paul Sheehan, Ahmad Bahai, Robert Langer and Anantha Chandrakasan consider the challenges involved in building ingestible electronic devices. These devices can combine diagnostic and therapeutic functions into a single miniature device, and could help to transform medicine and health monitoring. But as the researchers — who are based at the Massachusetts Institute of Technology, the Broad Institute of MIT and Harvard, Brigham and Women’s Hospital in Boston, the Advanced Research Projects Agency for Health in Washington DC, and Texas Instruments in Dallas — argue, problems related to device miniaturization, power-efficient integrated circuit design and data security remain to be addressed.

Robots are typically made from hard, rigid materials. This can make it difficult for them to adapt to certain environments or to interact with people. One potential solution is biohybrid robots, which rely on living muscles to drive force generation. However, to create untethered and autonomous machines, onboard electronics need to be integrated into such systems. In a Comment article elsewhere in this issue, Inkyu Lee, Arielle Berman and Ritu Raman address the challenge of using electronics to build biohybrid robots with physical intelligence.

Creating such biohybrid robots is no easy task, and the researchers — who are based at the Massachusetts Institute of Technology — highlight that it will require the integration of biological tissue with multimodal sensors, the development of local processing circuits for closed-loop locomotion control and the addition of onboard power sources. This could though, they explain, lead to “applications ranging from millimetre-scale systems for robotic surgery to metre-scale systems for environmental monitoring and exploration.”

Then, in the final Comment article for this issue, Shiyu Zhao explores the future of multi-robot systems. Work on multi-robot systems can be traced back to the 1980s, but such systems remain restricted to specialized tasks that can be accomplished by pre-programming. Zhao — who is based at Westlake University in Hangzhou — argues that in order for multi-robot systems to find practical relevancy, and to be deployed in open-world applications, the generality of the systems needs to be improved.

A shift from specialization to generality is central to the recent growth in AI, with the advance of large language models providing generality across a broad spectrum of tasks. For multi-robot systems, what is needed now, Zhao argues, is the development of general collective intelligence. This general collective intelligence can be viewed in terms of three capabilities: multiple tasks, new situations and natural interaction. But creating such collective brains will likely require the field to re-examine and refocus its research priorities.