Emerging Information Technologies: A Dual Taxonomy By Paradigm And Application Domain

Emerging information technologies are digital innovations in early development or adoption stages that can reshape economic and social structures. This paper synthesizes a pragmatic taxonomy of these technologies by combining two complementary perspectives: technological paradigms (how they work) and primary application domains (where they impact). Six technological paradigms are identified and characterized: network-centered (connectivity and 5G/6G-enabled IoT), data-driven (AI, big data, digital twins), sensor-based cyber-physical systems (IIoT, advanced robotics, medical wearables), interaction- centered interfaces (AR/VR/XR, voice, BCI), distributioncentered architectures (cloud, edge, blockchain, decentralized systems) and emerging computational models (quantum, neuromorphic, DNA computing). For each paradigm the paper highlights representative technologies, typical uses and main technical or adoption challenges. The second axis reviews major economic and social sectors—healthcare, industry, education, transport and public governance—and shows how combinations of paradigms produce domain-specific value: AI and IoMT in healthcare; IIoT, digital twins and edge computing in Industry 4.0; AR/VR and adaptive learning systems in education; V2X, autonomous systems and edge analytics in transport; and cloud, data analytics and smart-city sensor networks in public administration. The paper concludes that maturity and adoption vary widely: some technologies (cloud, applied AI, 5G, IoT) are already mainstream while others (quantum computing, large-scale AR/VR, fully decentralized ecosystems, 6G) remain nascent. Understanding both paradigm and domain perspectives helps researchers and decision-makers prioritize investments, anticipate regulatory needs and design targeted adoption strategies.