The AI Security Gap: What Every Business Needs to Know

Imagine a marketing team effortlessly crafting compelling ad copy with AI-powered tools, or a financial analyst predicting market trends with remarkable accuracy using generative AI models.

The possibilities seem limitless, and the allure of this revolutionary technology is undeniable. But what happens when the very tools designed to propel businesses forward also expose them to unprecedented data privacy risks?

This is the double-edged sword of generative AI.

While it offers incredible potential for innovation and efficiency, its rapid adoption has outpaced many organizations' ability to implement robust security measures.

To understand the complexities of this landscape, we sat down with Jason Dallas, a cybersecurity expert at iCorps, a leading provider of managed IT services. Jason provides valuable insights into the challenges and opportunities presented by AI, emphasizing the need for a proactive and strategic approach to data privacy.

The Double-Edged Sword of AI Adoption

The ease of access to AI tools is both a blessing and a curse. While businesses of all sizes can now leverage powerful AI capabilities, this accessibility has led to widespread adoption, often without proper oversight or security protocols.

"People are often just signing up for AI," cautions Jason. The disconnect between authorized access and actual usage highlights a significant risk. Employees eager to harness AI's benefits, might not fully grasp the implications of feeding sensitive company data into these systems.

It's like giving someone a powerful sports car without any driving lessons, " Jason explains. "They might get from point A to point B faster, but the risk of an accident is much higher." Similarly, employees using AI tools without proper training or security awareness can unintentionally expose their company to data breaches, compliance violations, and reputational damage.

The perceived simplicity of AI tools can also lead to complacency. Many businesses assume that popular platforms are inherently secure, but this is a dangerous misconception. This reliance on external providers demands a careful evaluation of vendor practices and security measures.

The Critical Need for Vendor Due Diligence

The reliance on third-party AI providers adds another layer of complexity to the data privacy equation. As Jason points out, "No one is really running AI themselves; it's always through a third party."

This means businesses must be extra vigilant when selecting and managing AI vendors. "So that's where that vendor due diligence [comes in]," Jason emphasizes, "but most people would just sign the contract and just be like, 'Oh, they’re going to help us again.'"

Blindly trusting vendor promises without proper scrutiny can have dire consequences, especially when sensitive data is involved. Jason recounts a situation with a CMMC-compliant client — a company bound by stringent cybersecurity regulations for handling controlled unclassified information.

"They’re CMMC," he explains, "which means they have to be NIST 800-171 CMMC compliant, and they wanted to use a tool to help them. And this company [the AI vendor] was in business for 3 months. There was no way they could have the proper reports yet." Jason's thorough questioning revealed potential vulnerabilities that the client might have missed had they not conducted proper due diligence.

The risks aren't limited to fledgling companies. Even well-established AI providers might not have adequate security measures in place for every integration. Jason describes a hedge fund salesperson who wanted to use an AI email reader. This seemingly innocuous tool, however, required access to the client's entire email
tenant, raising serious concerns about the security of sensitive client communications.

These real-world scenarios underscore the importance of a robust vendor due diligence process. Before integrating any AI solution, businesses must:

• Thoroughly vet the vendor's security practices: Perform due diligence, such as reviewing any third-party independent assessments and audits, such as an SOC report. Additionally, evaluate them through the lens of maintaining your own compliance, such as SEC, HIPAA, FFIEC, and GDPR.
  
  
• Scrutinize the vendor's data usage policies: Demand transparency around how data is collected, stored, processed, and shared. Understand where your data resides and who has access to it.
  
  
• Don't be afraid to ask tough questions: Challenge the vendor's security claims and ask for evidence to support their assertions. Remember, it's your data on the line, and you have a right to know how it's being protected.

Establishing a Framework for Responsible AI Use

Conducting thorough vendor due diligence is a crucial step, but it's only part of the equation. Businesses also need to establish clear internal policies and procedures to govern the use of AI within their organization.

"We have mobile device policies," Jason points out, "but we don’t have anything about AI in general.” This absence of AI-specific guidelines leaves employees in a gray area, forced to make their own judgments about what data is acceptable to input, which tools to use, and how to manage potential risks.

Just as companies have rules for using company phones and computers, they need a similar framework for AI tools. This includes:

• Acceptable Use Guidelines: Define the specific purposes for which AI tools can be used within the company. Clearly outline any prohibited uses, such as processing sensitive customer data without authorization or utilizing AI for personal gain.
  
  
• Data Input Protocols: Establish strict rules about what types of data can be inputted into AI systems. Prioritize anonymization or de-identification of data whenever possible. Provide training on how to recognize and handle sensitive information responsibly.
  
  
• Access Permissions: Implement a system of tiered access, limiting access to certain AI tools and data sets based on job roles and responsibilities. Regularly review and update permissions to ensure that only authorized personnel have access to sensitive information.
  
  

For businesses looking to ensure comprehensive security oversight, a virtual Chief Information Security Officer (vCISO) can provide expert guidance at a fraction of the cost of an in-house executive. A vCISO helps develop and implement robust cybersecurity frameworks that align with both regulatory requirements and
business goals.

By partnering with a vCISO, businesses can proactively address compliance challenges, reduce their cyber risk, and ensure that security best practices are integrated into every aspect of their operations—especially when managing complex tools like AI. This external oversight ensures that your company remains agile, secure, and compliant as technology evolves.

The Human Element: Training and Awareness

Even with the most robust security measures and well-defined policies in place, the human element remains the most critical factor in ensuring data privacy in the age of AI. "People need to know what they’re doing," Jason stresses. "It’s like setting up a new ERP or accounting system. Those are usually rolled out. People have training. But, people are just often signing up for AI." This lack of training and awareness is a major vulnerability.

Employees need to be educated on how to use AI tools effectively and the implications of their usage from a data privacy perspective. Training programs should cover:

• Understanding AI and Data Privacy Risks: Explain the basics of generative AI, its potential benefits, and the inherent risks associated with processing data, especially sensitive information. Use real-world examples of data breaches and the consequences for individuals and organizations.
  
  
• Identifying Sensitive Information: Provide clear guidelines on what constitutes sensitive data within the company and how to handle it responsibly. Emphasize the importance of data minimization,
  anonymization, and secure storage practices.
  
  
• Recognizing Phishing and Social Engineering Attacks: Cybercriminals often exploit AI to create highly convincing phishing emails and social engineering scams. Train employees to identify suspicious messages, verify requests for information, and report potential threats.
  
  
• Applying Company Policies: Reinforce the importance of adhering to company policies regarding AI usage, data handling, and security protocols. Provide clear examples of acceptable and unacceptable practices.
  
  

Ongoing education and awareness campaigns are crucial to keep employees informed about evolving threats and best practices. Regular security reminders, newsletters, and interactive training modules can help maintain a culture of vigilance and responsibility.

Conclusion: Embracing AI with Confidence

The transformative power of generative AI is undeniable. It has the potential to revolutionize industries, streamline operations, and unlock new levels of innovation. But this potential comes with a responsibility to prioritize data privacy and security.

As Jason Dallas's insights make clear, a proactive and strategic approach is essential. Businesses must understand the unique risks associated with AI adoption, conduct thorough vendor due diligence, establish clear internal policies, and invest in employee training and awareness.

By partnering with experienced cybersecurity experts like iCorps, businesses can confidently mitigate risks and ensure that their AI initiatives drive progress without compromising sensitive data.