Risks Of Investing In Artificial Intelligence

Artificial intelligence (AI) is now one of the strongest trend in the equity markets, and I wanted to share with you some research about the risk of this kind of companies so you can check carefully some key aspects before investing on these companies:

1.       Legal risk related to data protection and privacy: AI uses large datasets to train, test, and enhance models and algorithms. Nevertheless, those datasets might have sensitive information such as personal details subject to data protection and privacy laws. These laws require several restrictions and obligations on the collection, processing, sharing, and transferring of personal data, as well as grant various rights. If you invest in a company that fails to comply with these laws, this can result in considerable lawsuits, fines, worsened reputation, and even loss of trust and customers.

2.       Threat of piracy and cybersecurity attacks: Given the nature of the business, AI systems can also pose security and cybersecurity risks, such as theft or destruction of data, algorithms or models, unauthorised access, manipulation, as well as hacking, malicious attacks, or sabotage of the AI systems. These risks can not only cause harm or damage to the users, customers or third parties, but also compromise the confidentiality, integrity and availability of the AI systems.

3.       Accountability and transparency: you can also find issues of accountability and transparency, especially when they involve complex, opaque or autonomous algorithms or models. These issues can affect the trustworthiness, reliability and legitimacy of the AI systems, as well as the rights, interests and welfare of the users, customers or even third parties. As an investor you must check if AI companies have clear and consistent policies, procedures and practices to ensure the accountability and transparency of their AI systems.

To mitigate the legal regulatory risks when investing in AI companies, investors need to approach legal regulatory risk management and due diligence, both before and after making their investments. For example, you must also review and verify the legal regulatory contracts and agreements of the AI companies, such as their data processing and sharing agreements, security and cybersecurity agreements. Besides I recommend you review and verify the legal regulatory incidents and breaches of the AI companies, such as their past data protection and privacy incidents, security and cybersecurity breaches, bias and discrimination incidents.

Investing in AI companies can offer significant opportunities and benefits for investors. However, investing in AI companies also entails significant challenges and risks, especially from a legal regulatory perspective. Therefore, investors need to be diligent in managing the legal regulatory risks by conducting a comprehensive legal regulatory risk management and due diligence process, both before and after making their investments.

In any case, the rapid pace of technology change can render today’s breakthrough obsolete tomorrow. Companies might fail to turn their tech prowess into sustainable profit margins due to intense competition or regulatory pressures and changes.

Given the specific-firm risk of adaptation to the environment, I would prefer to approach it by benefitting from the industry growth and diversify the risk through AI funds or ETFs with dozens of AI stocks and no concentrated positions. In case you might want to bet on a specific one you know better, the safest way to go is by not giving it a bigger weight than 10-15% compared to the fund weight.

If you do not have any specific stock in mind, it might be useful for you to know the AI businesses focused on healthcare are one small segment that is outperforming other kinds of AI. One longevity trend for the next few decades is going to be machine learning algorithms assist doctors with diagnosis by accurately interpreting medical images while predictive analytics helps identify patients at risk for certain diseases ahead of time. To sum it up, you might not need to go to the doctor's office as he can keep track of your biomarkers on live (unless you might have a big issue that needs to be treated in person, of course).

Another one with big growth potential is the financial industry given the potential of lowering operating costs on many areas and achieve better profitability margins. The biggest financial institutions are now making big investments on AI to lower workloads on many administrative tasks and enhance their productivity in the long term.