Nokia’s 2030 strategy heads towards tapping into the expansive opportunities presented by the metaverse, with a particular focus on Web3 and AI advancements. Anticipating a significant surge in network demand, the company aims to address this need through strategic investments in its network infrastructure by the end of the decade.
Outlined in Nokia’s Technology Strategy 2030 report, the company’s vision revolves around crafting a future-proof network architecture to cater to the evolving landscape of innovations. This includes projections of a substantial 22%–25% increase in network demand from 2022 to 2030, largely attributed to the mainstream adoption of generative AI and virtual reality technologies.
To realise its objectives, Nokia plans substantial investment in its portfolio of network equipment and services, with a particular emphasis on six key ecosystems. Among these, the Internet of Value stands out, focusing on decentralisation, blockchain, and smart contracts. Within the metaverse domain, Nokia’s strategic emphasis lies in human augmentation, spatial computing, and split processing technologies.
In pursuit of these goals, Nokia established two labs in 2022 dedicated to metaverse research and experimentation, with significant initiatives undertaken in 2023 to explore industrial and wide-scale applications. Leveraging network digital twin technology, Nokia envisions a future network architecture that can simulate physical objects, facilitating prototyping and testing across various industries.
In practical terms, Nokia has already demonstrated the potential of the metaverse, such as in South Australia, where it utilised augmented reality via 5G-connected Microsoft HoloLens to assist Cessna aircraft technicians at remote airports. Additionally, Finnish scientists experimented with digital twins known as “Metahumans,” exploring gamification possibilities for employee management within the metaverse.
The utilisation of digital twins in industrial simulations holds promise for enhancing work strategies, implementing new safety measures, and optimising performance and output based on real-time data insights garnered from these simulations.