Artificial Intelligence (AI), heralded as a silver bullet solution, has rapidly permeated diverse sectors and the blockchain realm is no exception. Given the Asia-Pacific region’s concurrent leadership in AI development, it comes as no surprise that APAC will become a hotbed for innovative AI-blockchain hybrid solutions.
Despite widespread blockchain adoption in APAC, the level of engagement differs significantly. Vietnam stands out, particularly in fintech — with almost 90 per cent of Vietnamese individuals involved in decentralised finance. However, expertise in one technology does not translate to the mastery of another.
Blockchain enthusiasts may struggle with AI, and AI experts could find blockchain complex. In fact, despite Vietnam’s strong blockchain adoption, only 27 per cent of its organisations are fully prepared to deploy AI.
The varying stages of blockchain and AI development across APAC countries present a unique landscape for collaboration. These synergistic technologies are poised to drive transformative advancements, fostering greater efficiency, security, and transparency across various industries — from finance to supply chain management. As of now, the combined market for these technologies is projected to exceed US$703 million by 2025.
The cloud plays a pivotal role in this evolution, enabling businesses to develop decentralised, resilient blockchain networks capable of scaling to meet the demands of an expanding user base. Yet, challenges around scalability, regulatory compliance, and sustainability must be addressed to fully realise the potential AI-blockchain innovations.
AI’s transformative influence on blockchain
The decentralised nature of blockchain aligns seamlessly with AI’s growing need for autonomy. AI applications – especially those in collaborative industries like logistics, finance and manufacturing – benefit from distributed systems that enable real-time, secure data sharing across multiple entities.
Blockchain’s decentralised architecture enables seamless, secure data sharing between organisations without relying on a central authority, reducing the risk of single points of failure and ensuring AI systems remain resilient in multi-stakeholder environments.
The financial industry, which handles vast quantities of data, is a prime example of how AI and blockchain can be effectively combined. For instance, AI algorithms can detect fraud and money laundering on blockchain data, while blockchain ensures data security.
For startups, this integration presents an opportunity to compete with larger firms on a more level playing field. As startups leverage blockchain to enhance supply chains, they have begun to recognise the limitations of centralised systems. Although these systems initially offered cost efficiency and better visibility, challenges such as decision-making bottlenecks and reduced flexibility were also faced.
The result? Many are now seeking decentralised solutions that can provide greater adaptability and responsiveness. Blockchain’s decentralised, transparent structure empowers startups to streamline their supply chain management, ensuring improved quality control, traceability, and transparency through smart contracts.
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With that, businesses are moving towards a future characterised by automation, transparency, and decentralised decision-making, reshaping traditional paradigms and fostering a more collaborative and innovative environment.
Potential pitfalls with AI-Blockchain integration
Despite the excitement around AI within the blockchain ecosystem, the path forward is riddled with challenges that must be addressed.
One of the most significant barriers to AI-blockchain integration is scalability. Blockchain networks, designed with security and decentralisation as their core features, are not optimised for high transaction throughput. When AI is introduced, particularly resource-intensive machine learning models and real-time data processing, the demands placed on the network increase exponentially. Blockchains are not optimised for frequent data writes and reads, a necessity for AI model training, updates, and optimisation.
Moreover, storing large datasets required by AI systems on blockchain can be inefficient and costly. These can lead to slower processing speeds, higher latency, and escalated operational costs, particularly in cloud-based environments where services are billed based on resource consumption.
Furthermore, with the regulatory landscape surrounding AI and blockchain still evolving, organisations struggle to ensure compliance with data protection laws and industry standards. This uncertainty can lead to reluctance in adopting these technologies, hindering innovation and slowing implementation. This is especially acute for startups operating in multiple countries and managing operations across different regions.
Sustainability concerns also loom large over the future of both AI and blockchain technologies, largely due to the substantial energy and data centre resources needed for their operation. In fact, by 2026, the combined energy usage of AI and blockchain-powered cryptocurrencies could double to over 1,000 terawatt-hours (Twh), roughly equivalent to the annual electricity consumption of Japan. Addressing these sustainability issues is critical, not only to mitigate environmental impact but also to ensure the long-term viability of both technologies.
Building a strong foundation
Cloud-based blockchain solutions merge the decentralised, transparent, and immutable qualities of blockchain with the scalability and accessibility of cloud computing.
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The availability of hybrid and multi-cloud options play a critical role in developing blockchain infrastructure, enabling interoperability and decentralisation. They also address data residency concerns for organisations operating across multiple jurisdictions by storing sensitive data within designated geographic regions, minimising the risk of data breaches and regulatory non-compliance.
This must be complemented with high-performance, purpose-built, dedicated servers like bare-metal servers. Unlike virtualised or shared cloud environments, bare-metal servers provide the raw power and memory capacity to ensure optimal performance — crucial for blockchain’s heavy transaction loads, large-scale data storage, and complex consensus mechanisms. For instance, bare-metal servers can be tailored to optimise Graphics Processing Units (GPUs) for AI algorithms used in conjunction with blockchain for predictive analytics and fraud detection.
Given the data-heavy nature of blockchain networks, cost transparency will be vital for the long-term sustainability of blockchain-based cloud services. Businesses which prioritise maximising uptime and cost-efficiency need more transparent pricing models to manage costs effectively. By adopting affordable and fair cloud services, startups can effectively maintain their exchange infrastructure and focus on core business activities.
Lastly, businesses should also prioritise selecting cloud vendors that integrate sustainability into their operations. Choosing cloud vendors with green data centres which balance power efficiency and scalability while reducing environmental impact will be essential.
As AI-blockchain technologies gain traction in APAC, it will be crucial for blockchain businesses to implement robust strategies to scale their networks and deliver reliable, secure services. Fortifying transparent partnerships between blockchain businesses and cloud service providers will be instrumental in propelling the region towards innovation, transparency and trust.
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