Artificial intelligence is everywhere around us: from the chatbots that promptly respond to an inquiry to the algorithms that help manage a trade better. Cryptocurrency is also on the rise in terms of financial acceptance, given Bitcoin’s near-adoption level of use worldwide.
But mixing AI with cryptocurrency is a less explored sector. Together, these technologies could drive massive evolution in transactions, exchanges, and trade automation. However, innovation might be hindered by inadequate regulation, leaving companies unsure of the limits within which they can operate.
More and more businesses leverage BTC, ETH USD, and BNB for various operations and accept them for transactions, so the opportunity to contribute to a revolutionary AI approach would have user support.
Let’s explore the current state of crypto and AI, and analyze their potential to improve the world.
How could AI improve crypto?
The AI addition to the cryptocurrency industry paves the way for a safer, more efficient sector. One of the most important use cases starts with trading, where advanced algorithms can analyze vast amounts of data from endless sources, identify trends and opportunities, and predict future market movements.
This operation can greatly help traders make the right decision, based on data analysis rather than emotions or FOMO (fear of missing out).
Some platforms have already adopted AI to enable automated trading, eliminating the risk of errors. AI-based trading also reduces the risk of losses, as trades can be set to occur during the best market moments, balancing opportunities and risks.
Other use cases of AI in crypto include the following:
- Fraud detection. By analyzing data from relevant sources, AI can identify fraud and prevent money laundering;
- Security. AI can detect vulnerabilities in systems and suspicious activities to flag them as concerning;
- Governance. AI can support regulators in identifying risks and taking action regarding policies;
What are the AI technologies offering advantageous growth?
When we think of artificial intelligence, we might have a limited view of the range of technologies it encompasses. That’s why AI is ideal for optimizing an industry with few regulations, as it can adapt to a wide range of demands and requirements.
For example, deep learning models are best for market prediction, as they identify patterns in historical price data and technical indicators that offer a thorough perspective on the future. These solutions can now help identify the correlation between Bitcoin’s volume spikes and altcoin price changes, among other market movements.
On the other hand, reinforcement learning meets the need to adapt to the market in real time. These agents are not as popular at the moment, but they offer the opportunity to learn optimal trading behavior, which is useful for managing the limitations of traditional rule-based crypto trading algorithms.
Finally, LLMs (large language models) are best for analyzing user sentiment across multiple sources, such as social media and the news, to gauge public opinion on the power of crypto. This is especially useful, since many investors make their decisions driven by FOMO or crypto biases.
What are the most possible challenges of implementing AI in crypto?
Unfortunately, combining AI and crypto successfully is not that easy, given their current levels of development. Numerous challenges must be tackled by professionals and companies, most of which rely on limited training data.
AI must have access to a lot of high-quality information in order to perform well and deliver useful insights, but this level of functionality isn’t easily achievable. Selecting the right type of data takes time and resources, and there is a chance the final result will be flawed.
Another issue is cybersecurity risks. AI is still in its infancy, somehow, as the tooling is rather expanded across multiple sectors rather than focusing on strengthening the security of their approaches.
Therefore, vulnerabilities might be present in more areas than previously believed, with hackers finding ways to exploit them. Exploiting AI algorithms can be possible, leading to the loss of funds and trust in crypto.
Finally, algorithmic bias is another pressing issue. The data on which AI is trained is also biased, which affects the algorithm’s ability to produce completely objective insights. For example, if traders leverage AI for predictions, the results might be biased or incorrect, leading to losses.
Can AI and crypto work together efficiently?
While it’s almost impossible to predict the future of these two sectors, it’s clear we need a solid security foundation for both. This includes a robust regulatory framework that addresses artificial intelligence from a privacy and data protection perspective.
AI-based systems must respect user privacy and handle and process information adequately. This is also true of the cryptocurrency industry, and we’re seeing progress from the US and Europe.
They have developed a basic yet important foundation for crypto regulations, offering support for AML (anti-money laundering) and KYC (know-your-customer) policies for stablecoins and similar assets. However, progress is needed towards all types of coins and their underlying blockchains.
In addition, we need more talented people who can navigate the challenges in both industries to collaborate and implement the right tools for the future. Hopefully, both sectors will remain in demand in the future, driving the rise of a new field of work.
Hence, even AI can trigger the creation of new jobs while helping settle ones in industries where talent is much-needed, such as blockchain.
Until then, experts, startups, and small businesses from both industries are carrying an important task on their shoulders: to develop the means for a better future.
Conclusion
Artificial Intelligence is everywhere we look, but where its use is needed most: in technology and finance. AI has the potential to improve industries like cryptocurrency through automation, enhanced security, and governance by eliminating risks, predicting trends, and supporting decentralization.
However, this can be challenged by the lack of a proper legal framework, as well as AI’s known bias stemming from the databases it feeds on and learns from.
Hence, navigating these issues, along with the need for improvement in the crypto industry, is crucial to taking the industry to the next level.
