AI Leads Mass Adoption while Blockchain Maintains Unique Niche Value
As the technological landscape evolves, the competition between AI and blockchain intensifies for mainstream adoption. While Artificial Intelligence has surged with its transformative capabilities, blockchain remains relevant with its unique offerings. Both technologies hold promise, but long-term demand, accessibility, functionality, etc., play pivotal roles in their trajectories.
AI’s remarkable evolution has led to its integration across various sectors, while blockchain’s potential for secure, transparent, and tamper-proof records has also made it a contender. Blockchain technology, once in the spotlight due to its association with cryptocurrencies, has taken a backseat to the rapid advancement of artificial intelligence (AI). Recently, AI has surged ahead, disrupting various sectors and captivating consumers, businesses, governments, and developers alike. Instead of viewing them as opposing forces, developers should explore AI-driven blockchain, seeking synergies that could yield even better results. Here are 8 factors considering which technology will go mainstream first: AI vs. Blockchain
1. Long-Term Demand
The potential of AI is far from being fully realized. The industry has witnessed a transformative shift with modern AI models, enabling natural language imitation, lifelike visual generation, and human-like vocal mimicry. These developments have unlocked new possibilities across sectors. The abundance of data available for AI training ensures continuous growth in sophistication and applicability, suggesting that AI could find its way into virtually any industry.
Similarly, blockchain’s potential for long-term usability is promising, but its success depends on fostering a larger community. Without sufficient growth, it might struggle to outperform mainstream digital storage and payment solutions, limiting its broader adoption.
AI holds an accessibility advantage over blockchain. AI systems were already used before modern large language models (LLMs) emerged. These systems power everyday applications such as virtual assistants, facial recognition, chatbots, and self-driving cars. Moreover, user-friendly interfaces make AI-driven platforms accessible to many users, irrespective of their technical expertise. The example of ChatGPT illustrates how intuitive prompts can empower users for technical tasks.
In contrast, blockchain systems have steeper learning curves, hampering their potential to replace existing digital solutions until more user-friendly interfaces are developed.
The breadth of AI’s capabilities gives it a more diverse range of functions than blockchain. AI executes programmed tasks, comprehends natural language, and draws logical conclusions. As AI advances toward artificial general intelligence (AGI), it promises to revolutionize industries by autonomously performing tasks requiring human cognitive functions.
Meanwhile, blockchain-primarily finds application in data sharing/storage and financial platforms. Although industries use blockchain to execute smart contracts, store confidential data, and conduct decentralized crypto transactions, its functionality scope is narrower than AI.
4. Public Perception
AI enjoys a more positive public perception due to its accessibility and potential for broad impact. A survey indicates that consumers hold higher expectations for AI’s societal impact than blockchain. However, misconceptions persist regarding both technologies. For instance, some erroneously equate blockchain with cryptocurrencies, overlooking its broader applications. Similarly, AI myths, including the fear of machines taking over the world, create uncertainty.
5. Environmental Sustainability
Both AI and blockchain come with environmental concerns related to energy consumption. As evidenced by models like ChatGPT, AI can require substantial operations power. Similarly, running blockchain systems, especially for cryptocurrencies like Bitcoin, demands significant energy resources, resulting in carbon emissions.
Addressing these ecological effects requires proactive efforts from tech companies. AI can contribute through weather monitoring for climate change, while blockchain can offset its carbon footprint.
AI and blockchain are accessible through pre-built apps or SaaS products, with AI often being more affordable and widespread. However, AI systems’ deployment costs, including training and maintenance, can be higher than custom blockchain systems. The cost factor varies based on specific requirements.
Both AI and blockchain need regulation to address risks. Malicious actors can exploit unregulated, decentralized systems. Some form of governance is essential to manage these technologies’ potential for misuse while balancing security and decentralization.
8. Support and Development
AI’s continuous evolution draws significant attention and support from developers, tech companies, and end-users. Integrating modern language models into various applications ensures its popularity continues. In contrast, blockchain’s growth has been somewhat overshadowed by AI’s rapid expansion and instances of crypto scams.