.pp-multiple-authors-boxes-wrapper {display:none;}
img {width:100%;}
Artificial Intelligence and its associated innovations have revamped the global technological landscape, with recent data released by the US government predicting 13% growth in IT-related opportunities over the next six years – potentially adding 667,600 new jobs to the sector.
Researchers have stated that by 2034, the AI sector’s cumulative valuation may reach $3.6 trillion across industry. The healthcare sector has already integrated AI-based diagnostic tools, with 38% of today’s major medical providers using the technology.
The financial sector is also expecting AI to contribute approximately $15.7 trillion to the global economy by 2030, and the retail industry anticipates anywhere between $400 billion and $660 billion through AI-driven customer experiences annually.
It is estimated that approximately 83% of companies now have AI exploration as an agenda item for continued technical growth, especially given its capacity to drive innovation, enhance efficiency, and create sustainable competitive advantage.
Decentralising AI’s foundations
While AI’s potential is seemingly limitless, its rapid growth has brought a challenge – the centralisation of AI development and data management.
As AI systems become more sophisticated, risks like dataset manipulation, biased training models, and opaque decision-making processes threaten to undermine their potential.
Different blockchain tech providers have taken steps to decentralise the sector, offering infrastructure frameworks that change how AI systems are developed, trained, and deployed.
Space and Time (SXT) has devised a verifiable database that aims to bridge the gap between disparate areas, providing users with transparent, secure development tools that mean AI agents can execute transactions with greater levels data integrity.
The platform’s innovation lies in its ability to provide contextual data which AI agents can use for executing trades and purchases in ways that end-users can validate.
Another project of note is Chromia. It takes a similar approach, with a focus on creating a decentralised architecture to handle complex, data-intensive AI applications. Speaking about the platform’s capabilities, Yeou Jie Goh, Head of Business Development at Chromia, said:
“Our relational blockchain is specifically designed to support AI applications, performing hundreds of read-write operations per transaction and indexing data in real-time. We’re not just building a blockchain; we’re creating the infrastructure for the next generation of AI development.”
Chromia wants to lower the barriers to entry for data scientists and machine learning engineers.
By providing a SQL-based relational blockchain, the platform makes it easier for technical professionals to build and deploy AI applications on decentralised infrastructure. “Our mission is to position Chromia as the transparency layer of Web3, providing a robust backbone for data integrity across applications,” Goh said.
Chromia has already formed partnerships with Elfa AI, Chasm Network, and Stork.
Establishing a roadmap for technological sovereignty
The synergy between AI and blockchain is more than a fad, rather, a reimagining of AI’s infrastructure. Space and Time, for instance, is working to expand its ecosystem in multiple domains, including AI, DeFi, gaming, and decentralised physical infrastructure networks (DePIN).
Its strategy focuses on onboarding developers and building a mainnet that delivers verifiable data to smart contracts and AI agents.
Chromia is ambitious, launching a $20 million Data and AI Ecosystem Fund earlier this year. The project’s ‘Asgard Mainnet Upgrade’ with an ‘Extensions’ feature offers users adaptable application use.
The implications of AI’s shift toward decentralisation is of significant interest to Nate Holiday, CEO of Space and Time. He predicts that blockchain-based transactions associated with AI agents could grow from the current 3% of the market to 30% in the near future. He said:
“Ushering in this inevitable, near-term future is going to require data infrastructure like SXT that provides AI agents with the context that they need to execute trades and purchases in a way that the end user can verify.”
Chromia’s Yeou Jie Goh sees the transition not just as a technological innovation but as a means of creating a more transparent, secure, and democratised technological ecosystem. By using blockchain’s inherent strengths – immutability, transparency, and decentralisation – the two companies are working to create intelligent systems that are powerful, accountable, ethical, and aligned with human values.