The World Economic Forum’s Top 10 Emerging Technologies of 2026 identifies technologies that are moving from scientific promise toward practical deployment. The report identifies a pattern of technologies that are more personal, more distributed, and more materially efficient: cancer treatments designed for one patient, energy systems built from many small assets, food and materials produced closer to need, and AI systems that can model physical and biological complexity before expensive real-world trials begin.
- Everything-to-grid energy turns buildings, vehicles, factories and devices into active energy resources that can store power, return it to the grid and help balance supply and demand in real time.
- Direct lithium extraction uses engineered systems to pull lithium directly from brines, geothermal fluids or other liquid sources faster and with less land and water use than traditional evaporation ponds.
- Passive radiative cooling materials release heat into space while reflecting sunlight, allowing roofs, walls, windows and infrastructure to cool without electricity.
- PFAS destruction breaks down “forever chemicals” rather than merely capturing or relocating them, creating a path to more permanent remediation of contaminated water, soil and industrial waste.
- Precision fermentation uses genetically instructed microbes as production systems for proteins, fats, medicines and materials that would otherwise come from animals, plants or fossil-based chemistry.
- Exosome drug delivery uses the body’s own cellular messaging particles to carry therapeutic cargo across biological barriers and deliver medicines more precisely to diseased cells.
- Personalized mRNA cancer vaccines are designed from a patient’s own tumour mutations, training the immune system to recognize and attack cancer cells with a treatment specific to that person.
- Quantum simulation for drug discovery uses quantum computing principles to model molecular interactions more accurately, helping researchers identify stronger drug candidates earlier in development.
- World models are AI systems that learn from multimodal physical data, such as video, sensors and movement, so they can reason about real-world environments rather than only language or static data.
- Lattice-based cryptography provides quantum-resistant encryption and enables privacy-preserving computation, helping protect today’s data against future quantum computers.
A notable methodological shift in this year’s report is that the expert survey used in previous years was replaced by an AI-based nomination workflow that used multiple large language models to generate, classify, and validate technology nominations at scale, before human experts and the Advisory Council refined the final selection. We aim to explore a similar methodology here in the Siemens Xcelerator Community.
Taken together, the 2026 list points to a frontier where technology is becoming less centralized, less standardized and more context-specific. The promise is greater resilience, efficiency and personalization, but the practical challenge is governance: these technologies will only scale well if institutions can build trust, widen access and make policy, infrastructure and market choices before adoption outruns the systems meant to guide it.
