AI, robotics, and quantum tech drive new business models
The World Economic Forum (WEF) has released a groundbreaking report that explores how converging emerging technologies are reshaping global industries — and how business leaders and policy-makers can strategically respond.
Titled The Technology Convergence Report, the study was developed in collaboration with consulting firm Capgemini. It introduces the '3C Framework' — Combination, Convergence, and Compounding — to help decision-makers pinpoint high-impact intersections between technologies that are giving rise to new business models and systemic transformations.
The report identifies 23 high-potential technology combinations from a field of more than 230 subcomponents across eight critical technology domains:
Artificial intelligence (AI)
, omni computing, engineering biology, spatial intelligence, robotics, advanced materials, next-generation energy, and quantum technologies.
The World Economic Forum (WEF) is the international organization for public-private cooperation
Read: Sheikh Hamdan bin Mohammed announces opening of the Dubai Centre for Artificial Intelligence
Unlike conventional analyses that focus on individual breakthroughs, the report emphasizes synergistic effects. Notably, AI emerges as a pivotal enabler, making many of these powerful combinations commercially viable and scalable.
'Rapid advances across multiple technology domains are creating an undeniable shift in industries. The Technology Convergence report gives leaders a clear model to harness what is coming next,' said Jeremy Jurgens, Managing Director at World Economic Forum (WEF).
Jeremy Jurgens, managing director, World Economic Forum (WEF)
Highlights of the key convergence areas
Cognitive robotics:
Combining agentic AI, spatial intelligence, and advanced robotics is enabling machines to navigate and make decisions in complex, real-world environments. This is already transforming automotive production and smart manufacturing.
Digital twin ecosystems:
Enhanced by
AI
and real-time sensor networks, digital twins are becoming more integrated, offering end-to-end visibility and optimization across industries such as aerospace, healthcare, and logistics.
Hybrid quantum-classical computing:
Blending quantum algorithms with classical computing infrastructure is accelerating breakthroughs in finance, molecular modeling, and large-scale optimization problems.
Materials informatics:
AI-driven predictive modeling and transformer-based systems are drastically reducing R&D timelines in materials science, allowing virtual testing of compounds before laboratory synthesis — a leap forward for sectors like chemicals and manufacturing.
The report calls on leaders to adopt a systems-thinking approach, advocating for balanced investments across technology maturity levels, repositioning within value chains, and readiness across ecosystems. It also encourages regulators to rethink siloed frameworks and anticipate the broader societal impact of intertwined technologies.
'The question is not about whether technology convergence will reshape industries. That journey has already begun. The real challenge is how companies can position themselves to be champions of convergence,' said Aiman Ezzat, CEO of Capgemini.
Aiman Ezzat, CEO of Capgemini
A global evidence-based report
The findings are informed by qualitative and quantitative insights from the World Economic Forum's Technology Convergence Community, composed of global experts from industry, academia, civil society, and government. Their expertise was further supported by a Capgemini-led global survey of 2,000 senior executives across 18 countries and 10 industries.
About the initiative
The Technology Convergence Initiative is part of the World Economic Forum's broader effort to map and make sense of the fast-evolving tech landscape. It spans AI, quantum computing, robotics, biotechnology, spatial computing, and more — aiming to provide tools and frameworks that guide action across industries and sectors, unlocking societal value beyond the impact of any single technology.
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