Artificial intelligence (AI) and blockchain are the most transformative and disruptive technologies of our times. As transversal technologies, they can potentially disrupt a wide range of sectors. They will likely play central roles in the success of the world’s green and digital transitions and strengthen its technological sovereignty.
Algorithms are becoming increasingly open-sourced and deployed by users across industries, which increases their disruptive potential. Blockchain technologies provide a remarkably transparent and decentralized way to record transactions, facilitating anything from the sharing economy to supply chain management and smart contracts.
Therefore, all major economies are racing to take the lead in developing and deploying AI and blockchain technologies. Blockchain is forecast to have a wide-reaching impact on global GDP by 2025.
Blockchain has been primarily associated with financial services and cryptocurrencies since its inception in 2008; however, it is now expanding into other fields. The potential of blockchain technologies extends far beyond cryptocurrencies and finance, with an increasing number of applications outside of the financial sector. While the fintech sector continues to be at the forefront of blockchain developments, other industries such as telecommunications, healthcare, and government services are expanding and diversifying their blockchain initiatives.
Key features of blockchain technologies include the following:
- A decentralized consensus mechanism is used to validate transactions and guarantee the authenticity of data.
- Data are represented as blocks in a sequence, making new data (e.g., new transactions). Each data point added is a new block that references its predecessor. A change is, therefore, impossible as all blocks are connected.
- Data are stored in a chain of blocks in several locations. As long as each block has access to its predecessor, all other data can be stored in different locations, i.e., in a decentralized manner.
Companies that embrace blockchain technologies can benefit from several improvements
- Stronger trust and security through decentralized storage and common acceptance by all participants of the security of stored data. This supports combating fraud, proving the quality and origin of goods, and tracing faulty materials in supply chains.
- Verified information, which includes the possibility to confirm the authenticity of a document, diploma, or other information stored by blockchain enterprises.
- Reduced complexity and increased reliability, as using decentralized storage decreases the probability that a server shutdown will make data inaccessible.
Companies that adopt AI solutions, on the other hand, benefit from increased productivity and efficiency. According to researches, artificial intelligence (AI) could double economic growth rates by 2035 and increase labor productivity by 40%. In particular, companies can benefit from:
- Increased productivity, typically achieved via better decision-making processes. For example, AI can accelerate decision-making, enabling early pattern detection. In healthcare, for instance, this translates into the possibility of using natural language processing to detect early symptoms of a heart attack during a call to emergency services by analyzing speech patterns and unconscious signals. AI can also enable more accurate decision-making by spotting anomalies or longer-term trends that other methods cannot easily detect. Again in healthcare, computer vision technology can support doctors in identifying specific signs of disease in X-ray and MRI scans.
- Higher efficiency, typically achieved via automating manual processes. For example, AI can facilitate the automatic generation of machine-readable legal and compliance documentation, reducing the time needed for drafting and analyzing such documents. AI can also enable automated language and speech recognition. In practice, enterprises can use this function to deploy chatbots, thus decreasing employees’ time on calls.
Convergence of AI and blockchain
The possibilities presented by AI and blockchain technologies are likely to be combined, resulting in new platforms, products, and services. Their integration with internet connectivity across devices (IoT) systems may open up even more possibilities. IoT can be considered the “sensing” part of this technological convergence, AI the “thinking” part, and blockchain the “remembering” part. Converged technologies can be used in infrastructure to manage critical systems and improve residents’ quality of life through safer and better-designed urban environments for large-scale emerging use cases like smart cities.
By providing the large data sets required for AI learning, both IoT and blockchain can be key enablers for developing and implementing AI. The Internet of Things (IoT) is a critical component for data generation and collection; as IoT devices become more affordable and widely used, they will provide increasingly large amounts of data. Blockchain can be used to create a large database of verified records, which could aid AI learning. When used together, IoT and blockchain can significantly reduce the cost of data collection, preventing AI from being concentrated in the hands of a few large stakeholders.
In the context of AI and IoT, the decentralized network system of blockchain may provide ways to address the security, privacy, and resilience needs of businesses and individuals. As the Internet of Things becomes more widely used, more consumer data will be collected, necessitating greater security and data protection in society. By providing a trusted, common communications layer, blockchain could make IoT infrastructure more scalable and robust, provide secure audit trails of information, and increase the interoperability of IoT devices. The establishment of open, decentralized markets in which data producers can sell, rent or share their data, AI models, and resources could also be facilitated by blockchain.
The combination of AI, blockchain, and IoT can open new operational and commercial opportunities.
Potential future examples of combined applications include:
- Retail: AI can help predict actions based on data collected from IoT devices (for example, ordering food), and blockchain can help secure transaction processing
- Healthcare: AI can help with medical data monitoring, early detection of abnormalities, and appointment scheduling, while blockchain can help with a secure, accurate medical history.
- Cybersecurity: Fast, accurate data analysis, logical decision-making, and autonomous actions are possible with AI, while blockchain can store a secure record of potential evidence.
- Manufacturing: AI and blockchain can enable comprehensive remote status and performance monitoring of machines worldwide, machine learning-powered proactive maintenance, and the assignment of the most suitable technician with replacement parts, while AI and blockchain can provide a secure way to buy.
The combined application of these technologies poses risks and challenges that must be considered and mitigated. From a technological standpoint, this convergence will make protecting billions of IoT entry points more difficult. It will also exacerbate legal and regulatory complexities, such as data protection, while also posing governance, privacy, and data ethics compliance challenges. Individual technologies advance at different rates in different industries, so convergence is a long-term process.
