Protecting Your Business and Financial Data Against AI Risks

Business person using artificial intelligence tools on laptop

Artificial Intelligence (AI) has revolutionized business operations. With rich automation that improves day-to-day tasks and aids decision-making, businesses can operate in a more streamlined fashion. But, with the power of AI comes certain risks that businesses must address to protect their data and maintain operational integrity.

At Fusion CPA, we understand the importance of safeguarding against AI risks. Our CPAs keep this front of mind when implementing accounting software for various business industries. We take a look at some of the ways in which to protect your financial data as the popularity of AI increases.

How to safeguard against data breach risks in Artificial Intelligence 

It is absolutely vital that businesses take every precaution when it comes to ensuring the security and confidentiality of sensitive information in the current climate of technology advancements.

1. Implement encryption for data security

AI relies heavily on data to train algorithms and make accurate predictions. Data encryption converts sensitive data into a code that cannot be easily read or understood by unauthorized individuals or bots. This is crucial in prioritizing data security and privacy. It helps to prevent unauthorized access, data breaches, and misuse of sensitive information. Data encryption adds an extra layer of protection to your business data.

2. Implement multi-factor authentication:

Multi-factor authentication (MFA) is an effective security measure for protecting business data in today’s digital landscape. Unlike traditional username and password combinations, MFA requires users to provide multiple verification forms. This adds an extra layer of protection against unauthorized access. It can significantly reduce the risk of data breaches and unauthorized account access. With MFA in place, even if one factor is compromised, the additional authentication requirements make it more difficult for cybercriminals to access sensitive business data.

3. Implement employee awareness of data security

Educate your employees about the risks associated with AI and the importance of responsible AI usage. Offer training programs to enhance their understanding of AI systems, privacy considerations, and security protocols. Foster a culture of awareness and vigilance when handling AI technology and data.

Can businesses be too reliant on technology?

Automation reduces the risk of human error and makes for smoother business operations, but the two cannot exist without each other. Human expertise is valuable when it comes to overseeing automation reliability. Our CPAs look into some of the risks that may come from relying too heavily on technology. We also explore how businesses can safeguard against these risks.

Carlos Cortes, a lead CPA at Fusion explains that one of the greatest risks when it comes to AI and automation software is data integrity. It is important for businesses to test AI systems for data accuracy in the following ways:

  • Ensure accurate synchronization between systems

When relying on tech to automate workflows between systems, it is important to make sure data flowing through the different systems doesn’t change or become corrupt. You can do this by creating checks and balances, such as performing regular reconciliations at different checkpoints. Thorough testing and validation are essential to ensure the accuracy, reliability, and robustness of AI systems.

  • Diverse dataset testing

Use a diverse range of datasets relevant to your business to ensure that the AI system performs well across various scenarios. This will help to ensure accuracy in the system’s performance and that it is not limited to recording certain types of data only. This is especially important when dealing with automation between different accounting software systems – do checks to verify that the integrations are working as they should when it comes to all the different types of data they should be capturing.

  • Error analysis and debugging

It is also important to conduct debugging tests to help you assess the types of errors your AI or automation systems are prone to making. This involves examining whether errors exist and then determining the reason for that error. Your CPA can easily do this by conducting monthly recons. By pinpointing the sources of errors, you can introduce additional features to enhance the reliability of your integrations.

  • Ensure regulatory compliance with your software

Businesses must use apps and software that complies with the required regulatory bodies for both safety and privacy. Examples of these include GDPR (when dealing with customer data), Privacy Shields under US-EU, and Encryption when transporting data. Businesses also need to consider if the software they make use of uses Transport Layer Security (TLS, also referred to as Secure Socket Layer, HTTPS, or SSL), and if it is SOC2 compliant. Does the software offer backup or do you need to create an additional backup of all business app data? These are important technical considerations for safety and compliance.

Safeguarding against risks in AI is an ongoing process that requires a comprehensive approach encompassing technology, policies, and people. By partnering with experienced professionals you can harness the benefits of AI and protect your financial data from potential threats.

At Fusion CPA, we are committed to helping businesses navigate the complexities of AI. Our CPAs provide the expertise and resources to ensure the secure integration and effective management of AI technology within your financial operations. Consult with us to look into additional controls when it comes to protecting your business in the climate of AI.

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This blog article is not intended to be the rendering of legal, accounting, tax advice or other professional services. Articles are based on current or proposed tax rules at the time they are written and older posts are not updated for tax rule changes. We expressly disclaim all liability in regard to actions taken or not taken based on the contents of this blog as well as the use or interpretation of this information. Information provided on this website is not all-inclusive and such information should not be relied upon as being all-inclusive.

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