The line between smart, agentic AI and old-school systems with intelligence is quite thick. The same can be said about the difference between a modern investment bot powered by contemporary technology and somewhat outdated algorithmic automated trading systems (ATS).
Just like a poet weaves lyrics out of thin air, LLMs can whip out all sorts of outputs by analyzing massive swaths of data. Results are called generative by PR specialists and synthetic by experts who deal with training data and know how it defines the quality and content of outputs produced by “generative” systems.
In the world of finance, the room for creativity is smaller, preventing many autonomous agents from straying away from objectives. In many senses, this limitation causes higher consistency and better outcomes for capital holders who often expect reliable returns and do not need to have six-fingered hands on their charts.
AI in investment strategies
Autonomy is a dream of any fintech developer. The idea of an investment robot that can outperform humans and deliver an excellent performance is often seen in movies, fiction, and comics. While we are still far away from having something that can work without any human supervision, the quality of contemporary tools is already quite impressive.
The use of artificial intelligence in modern advisory systems can be fruitful. There are several ways in which this technology can improve investment outcomes:
● Pattern recognition is incredibly useful when it comes to using technical analysis. It is the only viable method of analyzing highly speculative markets where many tricks from the arsenal of a traditional, fundamental analyst do not work. Modern smart systems can easily spot patterns in trader behavior.
● Social sentiment is often more important than macroeconomic indicators and other factors. Large language models are already quite good at processing textual information and extracting relevant bits or creating summaries. By providing insights for investors, these expert systems can be very useful!
● Immense data processing capacity. The clear advantage often mentioned by people pushing technological frontiers is the ability of these autonomous systems to chomp massive swaths of data with ease. Millions of interactions with digital assets produce enormous amounts of information that can be effectively analyzed only by machines.
● Quick learning. The biggest breakthrough in contemporary tech is the ability of modern systems to learn. With so much data available to humanity, it is impossible for any individual to absorb and memorize it. However, robots can do that effortlessly. Large language models based on neural networks improve with incredible speed.
The rate of technological improvement, resources invested in new technologies, and the rapid adaptation of neural networks to new sorts of data make it apparent that the future is already here. In the fintech sector, nothing is clearer.
Automated investment signals
A useful area where these expert systems can be used effectively is finance. While humans still outperform machines when it comes to large-scale decision-making or capital allocation based on fundamental analysis, a typical signal bot following sophisticated technical analysis strategies can do much better than an average trader.
Many crypto enthusiasts often contemplate the difference between trading and investment signal bots. The simplest answer can be derived from descriptions:
- An automated trading system (ATS) is a software that relies on algorithms to place orders on your behalf on centralized and decentralized exchanges. An ATS can be fully autonomous, as users can use signals generated by platforms like TradingView or receive them from reliable third-party vendors.
- An automated portfolio management system is a different beast. It is focused primarily on decision-making, adjusting asset compositions, and otherwise managing your finances. It should be noted that such products are still relatively underbaked and must be used with caution.
The latter has a variety of weaknesses. While apparent advantages include convenience for capital holders, faster operation, and quick reaction time, the downsides are still more pronounced and worrying.
Here are some of them:
● Poor data sources. It is possible to collect data from multiple sources. For instance, TradingView is capable of pulling information from several centralized exchanges and liquidity providers. However, the necessity to use a variety of DeFi assets means that machines also must analyze on-chain metrics and other information. Sourcing it can be very difficult.
● Underperforming analytical systems. An AI agents are still trained on data sets and rules provided by biased developers. We are still years away from a system that has been training without any human intervention using raw market data. Currently, fundamental data analysis by investment bots is unrefined, full of errors, and does not meet the high standards for effective portfolio management.
● Security risks. Technology can have weaknesses and vulnerabilities. Hackers and social engineers still represent a huge threat to many users. Given the popularity of self-custody in the cryptocurrency sector, the prevalence of various cyberattacks is not a surprise. However, using bots hosted on a third-party platform can be risky if service providers do not take security issues seriously.
● Unreliable testing. The problem with trying to evaluate the performance of different strategies is that past results do not indicate similar future profitability. Patterns that work well when applied to market history may not be useful under other circumstances. While using tools like backtesting is still incredibly important, results can be misleading.
Using any form of AI and machine learning in investment is a bet on a technology that still has so much room to grow. A capital holder interested in using it must understand that there are many risks associated with being the first at the starting line.
Examples of great products in this category
If you are interested in creating a portfolio that can perform well under a wide range of circumstances, it is a good idea to test some of the finest options offered by the fintech industry in 2025. We strongly believe that investors should do their due diligence, but it is unwise to avoid all novel instruments with potential.
Here are some great products that deserve your attention:
● Magnifi is a great example of a platform that utilizes the power and popularity of large language models. It is far from the cohort of top investment signal bots, but it is a great destination for newcomers who may lack the knowledge and confidence of a veteran. If you need a guiding hand and want to get started quickly, using the Magnifi virtual advisor can be a good idea. We recommend using it for educational purposes and double-checking all investment suggestions received from it.
● Incite AI is an interesting tool that works as a search engine. Users can ask questions about stocks, commodities, real estate, cryptocurrencies, and more. The system will tell you why it is a good or a bad investment. It also suggests optimal entry prices, technical analysis breakdowns, and prognoses for the future. The creators of this product warn users that any advice received from Incite should not be considered financial advice. In general, it is a good tool for people who need additional context when trying to make a difficult capital allocation decision.
● WunderTrading is a platform that offers a wide range of automation solutions. It is a respected vendor that has been around for ages. One of the latest additions to the roster of products is the AI trading bot that uses statistical arbitrage algorithms to identify the best way to manage a portfolio composed of several digital assets. Since it is tasked with making the most optimal adjustments, it does not take unnecessary risks and tries to reduce exposure. When it comes to portfolio management automation, this particular product stands out the most. It is fully autonomous and does not require much effort on the part of the capital holder.
Note that the vast majority of developers are swaying toward the implementation of large language models into existing financial platforms. However, other examples of utilizing advanced systems exist. For instance, DEFAI is focused on using AI agents for various financial products. It is one of the most intriguing services in the DeFi ecosystem, with a token that has been doing well in recent times.
Depending on your preferences and risk style, you may find the benefits of investment bots described above quite appealing. Whether you need to receive a piece of advice or offload a mundane managerial task to a capable ATS, it is possible to find a great option in the market. On the other hand, it is crucial to move forward with caution and implement these untested instruments slowly.
What about long-term portfolio growth?
Multiple surveys of crypto investors indicate that the vast majority of individuals are determined to hold on to their assets for the foreseeable future, some for decades. It is important to be flexible when it comes to building a long-lasting portfolio with digital assets. The landscape of the market is chaotic and may change dramatically.
AI systems in place right now are incapable of making large-scale financial decisions. Even if their creators claim that they can, we do not have any data that supports such claims. The rule of DYOR (doing your own research) is still the most important for all crypto enthusiasts. However, experimenting with novel instruments is useful and even recommended.
Many boring or overwhelmingly difficult tasks, such as market trends analysis, data processing, identifying social sentiment, and others, can be offloaded if you are willing to use some of the most advanced tools available to contemporary capital holders. Aforementioned Incite AI can be used to gather data about different types of assets. At the same time, you can allow a WunderTrading bot to do the trading on your behalf.
Many existing solutions are incomplete or require a very cautious approach from an investor. It is not as simple as setting up a DCA bot and waiting for it to deliver a consistent performance. Building passive income through investment bots is an uncharted territory. Even professionals still do not know how to use AI efficiently.
The main takeaway
While many tech enthusiasts continue to sing praises to artificial intelligence products that are flooding the market, it is crucial for potential end users to observe the market and search for practical solutions that can solve actual problems. Despite the best efforts from LLM creators, their products still have hallucinations, unexplained behaviors, incorrect outputs, and more. These problems prevent them from being taken seriously by those whose livelihoods may depend on outputs from something like ChatGPT or Incite AI.
However, it is possible to use some expert systems to produce useful outputs. For instance, various signals for ATS setups. You must test them diligently and put a limit on how you use them, but they can be handy in many scenarios. Be mindful of potential risks, do not overextend, and make sure to pick reliable service providers
