We live in a world where blockchain is looking to disrupt traditional finance and data systems and a world where Artificial Intelligence (AI) is becoming commonplace — arguably two advancements that are the biggest disrupters of our time.
Blockchain hits differently due to the potential for decentralized and immutable design, while AI, still in its early days, is already beginning to alter the way we absorb information and arrive at decisions.
When merged, do the duo complement each other or contradict? And do they work together or stay in their lanes?
We look at five industries where AI and blockchain are making an impact.
The Industries Impacted by Both AI and Blockchain
1. Supply Chain
Supply Chain Management is one of the areas where the convergence of AI and blockchain can be applied, primarily around supply chain optimization.
Blockchain, for instance, can be used to track deliveries, creating a transparent and secure supply chain. This will also aid in maintaining immutable records of deliveries and inventories, enabling all investors to be on the same page about all relevant statistics and payments.
Conversely, AI helps empower the analytics systems being used in the field. The technology can provide real-time insights into the entire supply chain, optimizing inventory management, predicting demand, and improving logistics.
With this, companies can receive more meaningful insights into their operations and make more data-driven decisions that will minimize costs and increase profits.
This can have knock-on effects in other domains, such as disaster relief.
During natural disasters, humanitarian organizations could benefit from the optimization of resource allocation through the combination of blockchain-based supply chain tracking and AI-driven analytics.
Emergency relief efforts can be enhanced by giving real-time data on the location and availability of vital supplies, allowing supplies to be distributed to the best possible place based on factors such as reach and need.
Similarly, AI and blockchain are the two most cutting-edge technologies flaunted as the drivers of more data-driven decisions, backed by AI’s analytics and blockchain’s data storage.
The global healthcare industry will benefit from the secure and safe data storage offered by blockchain, which maintains decentralized data while (when handled correctly) ensuring privacy.
AI’s application in healthcare is more vast, including the powerful analytics it can offer, the prediction of the progression of illnesses and epidemics, using existing data to derive diagnoses, and creating of custom treatment plans to fit a patient’s specific health status.
Currently, developers and doctors are collaborating in building AI models to identify abnormalities in patient images more rapidly and precisely than ever before, diagnosing a variety of diseases, including cancer and heart disease,
The duo is expected to accelerate research in medical research, given its ability to understand a lot of information from large data tracks in short periods.
The data management provided by the technologies will also enable healthcare and longevity experts to work more effectively from different physical locations while maintaining the highest data security standards.
3. Data Analytics and Security
Data is a strength for both AI and blockchain. As such, every sphere centered around data is experiencing a fundamental shift due to the introducing of the two technologies. Provenance is among its most helpful features when applying blockchain to data, particularly its capacity to offer unmatched data.
Using a decentralized and highly secure blockchain network to store data aids in realizing long-term data integrity protection. This provides substantial support for large-scale data analytics — a strength of AI.
The massive amounts of data created on-chain can be fed into advanced machine learning models that employ large-scale analytics as blockchain technology continues to underpin essential facets of human economic and social activity.
By doing this, these models may spot broad patterns and provide helpful information via predictive analytics, helping people and companies decide which opportunities arise from the on-chain economy.
On the data security front, AI algorithms can be employed to strengthen blockchain, which is already well known for having robust security features. AI can also improve data privacy by facilitating access limits, anomaly detection, and sophisticated encryption.
4. Decentralized and Transparent AI
The decentralized structure of blockchain makes it suitable for democratizing and decentralizing AI. The synergy between AI and blockchain creates the possibility of a marketplace for decentralized AI models, driving the mass adoption of AI due to availability.
First, blockchain makes tokenizing ideas, intellectual property, and AI services easier. AI developers can use Blockchain-based tokens to tokenize their services, generating digital assets that can be purchased, sold, or licensed. This tokenization strategy encourages innovation in the AI field and guarantees just rewards for producers.
At the same time, the technology can also store intellectual property rights to some of the AI creations, continually attributing a model or innovation to its creator. This prevents the theft of transformational ideas and ensures the right people are always compensated for their work.
With many tokenized AI services, blockchain has the potential to facilitate the development of decentralized marketplaces for AI models, allowing model developers to sell or license their models directly to consumers.
Blockchain integration will also ensure model developers are pretty compensated due to smart contracts, which enable automated and transparent transactions. These markets stimulate creativity and support various AI models and applications available to customers.
The safety and security of all systems across the globe remain a challenge that can constantly be attacked and improved on. But blockchain and AI, together or separately, can serve a role in security.
In addition to data privacy concerns, AI systems face the possibility of adversarial manipulation that could see the AI being used to harm the associated party or organization.
Blockchain can serve as AI systems’ encryption-backed safety nets in this case. Based on this approach, AI systems can be implemented with built-in guardrails that lessen the possibility of being abused or exploited in hostile ways.
AI developers can specify the constraints that AI must adhere to to access different vital systems, and private keys, in conjunction with tamper-proof decentralized infrastructure like blockchains, smart contracts, and oracles, can impose these constraints.
On the other hand, AI can be used to protect blockchain and its users from scams and other recurrent concerns. With its ability to learn patterns and detect anomalies, AI helps identify fraud before users become victims. It can also see projects lacking substantial backing, warning users to be careful.
Challenges Facing the Convergence of AI and Blockchain
Despite seeing the benefits the world stands to gain from merging the two technologies, the process of doing so is inhibited by various challenges.
Interoperability: Integrating AI into blockchain requires the interoperability of the two technologies and the various blockchain networks. However, the newness of the technologies acts as a barrier to this, given that standards are yet to be established to govern the structure of systems built using the technologies.
This results in a challenge in creating models and blockchain systems compatible with other models and blockchain systems, preventing them from realizing their potential.
Scalability: A big problem facing blockchain is its ability to scale and perform adequately in large-scale production. This limitation mainly compromises blockchain security because most nodes must agree on the transaction data to guarantee the network’s security.
Any attempts to aid blockchain solutions in scaling up have been limited by the time it takes for data to travel between nodes in the network, mainly due to its decentralized nature, resulting in longer delays.
This leads to an additional concern with performance, creating a dilemma where one can only be solved at the expense of the other.
Employing AI at scale is also not a cheap endeavor.
Ethical, Legal, and Social Concerns: Using blockchain and AI has led to ethical concerns, including questions about accountability for the actions and outcomes of AI agents and systems. Ensuring these AI entities align with human values and morals is crucial.
Additionally, there is a pressing need to address and mitigate potential harms and risks associated with the combined use of AI and crypto or blockchain.
In the legal domain, combining AI and crypto or blockchain introduces challenges surrounding regulation and governance. Questions arise about effectively overseeing the joint use of these technologies and safeguarding the rights of users and stakeholders involved.
The amalgamation of AI and crypto or blockchain also raises social implications, such as ensuring fairness, inclusivity, and accessibility for everyone in their joint use. These issues underscore the importance of thoughtful planning and the implementation of strategies to navigate the complexities inherent in this technological convergence.
The Future of AI and Blockchain
In the next ten years, the blockchain-AI confluence is expected to become a billion-dollar market, according to an analysis by Spherical Insights.
Even with this projection, there is still an opportunity for more research as these two technology segments move closer to wider public use because the integration of these two has been relatively understudied thus far.
Further research will show the significant potential for reshaping diverse industries by integrating AI and blockchain.
As businesses aim to automate operations, increase efficiency, and enrich their services, the widespread influence of AI on a substantial portion of software products is anticipated to lead to the continued expansion of AI models across various sectors of the economy.
At the same time, if trust in institutions diminishes, individuals are increasingly drawn to applications supported by cryptographic assurances.
Both AI and blockchain can be said to be in their early stages of development. However, the disruption they have caused in various industries cannot go unnoticed.
For the proponents, the merging of these two significant technological changes is poised to fundamentally transform the functioning of our societies and economies, restoring trust, security, transparency, and reliability while improving performance and providing actionable insights for decision-making.
As more advancements are made and standards are established, joining the two technologies together will likely lead to new possibilities.