Data-fuelled applications could make the metaverse an $8 trillion to $13 trillion addressable market by 2030, using computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning. This definition of the metaverse includes smart manufacturing, tourism value chains, NFTs, and digital forms of money. The digital competitiveness of small states like New Zealand, and others like South Korea, which are not members of economic unions, but which display high mobility in data flows, will rely on creating cavernous and labyrinth-like data trusts. This new Gross Data Product (GDP) will not depend solely upon the volume of broadband consumption per capita or usage behaviours alone.

Rather, it will turn on whether the data produced permits wider usability and accessibility by bureaucracies, innovators, SMEs, and cross-border agencies. In an Artificial Intelligence (AI) Frontier discussion paper, McKinsey (2018) outlined that late adopters will lag in both developing capabilities and talent management while front-runners would have engaged in rapid adoption and absorption. Micro factors, like the speed of adoption of AI, and macro factors, like the global connectedness or labour-market structure of an economy will both contribute to the magnitude of the change.

The changes would have the effect of shifting about thirteen per cent of the wage bill to futures of work that require nonrepetitive and high-digital-skill sets. These workers will experience oversized compensation and benefits, while workers in the repetitive and low-digital-skills categories, would experience a plateau. Leading AI economies that display a high Gross Data Product (GDP) would capture about 20 to 25 per cent in net economic benefits, while developing economies might capture just about 5 to 15 per cent.

Large water states, and countries outside of outsized customs unions, but which display high openness, may overcome the limitations of low broadband consumption and fewer active content producers, by crafting Data Free Trade Agreements with mega data producers.  Differences across countries in how private data is shared across agencies and whether sovereign identity frameworks exist that can help the cosmopolitan citizen of small states to link to their digital activities, will affect these New Data Agreements.

A new data economy driven by consent, insight, and data flows has led to the emergence of data representatives, agents, and custodians that serve as trusted hubs for users’ personal data. Data Trusts and Data Cooperatives will act as agents of insights in global marketspaces. Inside these new “walled gardens” the role of the Chief Insight Officer (CIO) or “corporate shaman” is gradually taking shape. CIOs garner insights from highly-valued but deeply-sensitive personal mobility data, and then turn that data into insights that the CIO is able to take to market without selling or transferring the data itself. In cooperative or public data trusts, privacy is protected, public services are enhanced, and groups that are underserved can benefit.

Data trusts are still evolving but they represent a promising alternative to surveillance capitalism. In the UK, the government has signalled that the Information Commissioner’s Office (ICO), will explore a post-Brexit divergence from the European Union’s data protection regime, or the General Data Protection Regulation (GDPR) that goes even further than benchmark US privacy laws governing health care, educational records, health insurance portability and accountability.

The UK intends to reframe the GDPR to use the power of data to drive growth, improve trade and remove bureaucratic red tape. However, the intended reforms will have to achieve a judicious equilibrium of divergence from the EU’s GDPR while still allowing the free flow of data across international borders.

This involves the balancing of sovereignty, privilege, and privacy. The ICO will have to strengthen links with data regulators in other jurisdictions on matters that range from digital health records to the talent attractiveness of jobs in other jurisdictions, while working with domestic stakeholders. The reforms must empower digital citizens to influence how they want their data to be used, and to point to remedies if things go awry. There are differences across countries in terms of how personal data is shared across agencies, and how digital identity frameworks connect individuals to their digital activities.

The global accessibility of country data is essential for creating successful AI applications in the future. In this “New” Data-Driven World Order, countries with high broadband consumption per capita and institutionally open states are clear winners, as this coincides with where the major data producers are located. Data is the fuel of future economies, much as oil and gas production has played in creating economic power brokers, in the preceding century.

The possibility that personal data generated by the users of electric vehicles (EVs) using infotainment platforms inside connected cars, may be streamed across borders has heightened the privacy concerns of EV owners. EVs are software-centric, and as Software-as-a-Service Subscriptions proliferate, and connected cars evolve into customizable digital platforms, the EU is exploring how connected cars manage personal data.  While EU member states can rival the U.S. as large data producers, BRIC nations, Brazil, India, and Russia, could emerge as powerful players based largely on the strengths of the gross data product they produce, according to Bhaskar Chakravorti at Tufts University.