WEF's 2026 Tech List Has a Clear Dual Theme

The World Economic Forum and Frontiers published the Top 10 Emerging Technologies of 2026 on June 23, and the signal is unusually clear: the tech race has moved off screens. After years of software-first AI development, the institutions that move real capital are now orienting toward physical infrastructure, energy systems, and deployment-ready deep tech. This is not a trend report from a consultancy padding its retainer. It is the highest-signal institutional benchmark in the game, used by LPs, sovereign funds, and corporate R&D budget committees as a primary reference for multi-year capital allocation.

Photo by Rafael Minguet Delgado via Pexels

The list was co-produced with Frontiers, which brings editorial rigour and data-driven methodology to the selection process, identifying technologies most likely to shape industry, policy, and society over the next five years. That five-year lens matters. This is not a list of what is exciting today. It is a forecast of what will be commercially essential by 2031, which is precisely the horizon that Series B and C investors and infrastructure-focused sovereign vehicles are underwriting right now. The dual themes running through this edition, energy convergence and AI-era physical infrastructure, make it a rare roadmap that speaks to both deep-tech and climate-tech allocators simultaneously.

The headline technology is everything-to-grid energy, which transforms buildings, vehicles, factories, and data centres from passive electricity consumers into active, real-time grid resources. New battery chemistries and smarter coordination software sit at the core of this shift. Paired with direct lithium extraction, which pulls lithium from brine using specialised materials with significantly greater efficiency than conventional mining, the list signals a hard infrastructure supercycle forming around energy storage and grid resilience. Lattice-based cryptography also features, a direct response to quantum computing risk that enterprise and government security buyers can no longer defer.

The AI entries on this year's list are telling in what they emphasise. The focus has shifted away from model capability and toward real-world deployment readiness. That is a critical recalibration for founders still pitching foundation model differentiation as a moat. The institutional consensus, reflected here, is that the value-creation layer has moved to integration, inference infrastructure, and sector-specific applications. For investors, this confirms that Series B capital will increasingly chase AI companies with measurable operational deployment rather than benchmark scores.

Over the next twelve months, expect everything-to-grid to move from pilot programmes to regulatory frameworks in the EU and select US states, unlocking project finance at scale. Direct lithium extraction will attract strategic investment from battery manufacturers and automakers nervous about conventional supply chains. Founders building in either of these verticals now have the most valuable thing a deep-tech startup can carry into an LP meeting: explicit institutional validation from the organisation that sets the agenda at Davos. The window to position before that capital concentrates is measured in quarters, not years.