AI Cyber Risk Assessments

By: Greg Johnson and Ben Card

Given the numerous opportunities to apply artificial intelligence in different ways, many organizations are taking a moment to conduct AI Cyber Risk Assessments to comprehend the potential vulnerabilities they may introduce into their businesses.

This is a strategic decision for organizations aiming to leverage A.I.'s capabilities while reducing risks. Below are 7 primary risk factors that highlight the importance of conducting an assessment. The bullets below represent details of the areas included in our assessments.

7 AI Risk Considerations

1. Legal and Regulatory Compliance.  Governments and regulators worldwide are evolving their legal frameworks around A.I.. Organizations need to ensure their A.I. solutions comply with data privacy laws (e.g., GDPR, CCPA) and include Intellectual property protections.  

• A.I. ethics guidelines also come into play. Consulting firms help navigate complex legal landscapes to avoid liabilities and fines.

2. Security Threats and Vulnerabilities.  A.I. systems can be vulnerable to cyber threats, model manipulation, and data poisoning. A consulting firm can identify such potential A.I.-specific security risks.  They can assesses vulnerabilities in A.I. models and infrastructure, and recommend mitigation strategies to protect against adversarial attacks.

3. Maximizing A.I. Opportunities.  An A.I. assessment isn’t just about mitigating risks—it’s also about identifying untapped opportunities.

Consultants can:  

• Provide insights on emerging A.I. trends

• recommend strategic A.I. investments

• and evaluate ROI and efficiency improvements through A.I. adoption.

4. Ethical Risk and Reputation Management.  A.I. can create unintended biases, unethical decisions, or brand-damaging incidents.

Consultants assess whether:  

• A.I. algorithms produce fair and unbiased outcomes and whether A.I. decisions align with corporate values.  

• A consultant can also opine on whether the organization has sufficient A.I. governance structures.

5. Compliance With Industry-Specific Standards.  Some industries require A.I. to meet sector-specific regulations, such as:  Financial services (A.I.-driven trading, fraud detection); healthcare (A.I. diagnosis, patient privacy), or manufacturing (A.I.-powered automation safety).  

• Consultants ensure A.I. aligns with best practices for compliance in highly regulated environments.

6. Risk Quantification and Long-Term Strategy.  A.I. exposure isn’t just about immediate risks—it’s about long-term sustainability.

Consultants help organizations:  

• Quantify financial and operational risks linked to A.I. models

• develop risk management frameworks and

• create policies for A.I. model lifecycle management.

7. Third-Party Risk Management  Many organizations rely on external A.I. tools, vendors, and cloud services.

Consulting firms evaluate third-party A.I. risks to ensure: 

• Vendor security and reliability

• A.I. supply chain integrity and

• compliance with service agreements and regulations.

These are critical elements. You can see why an objective and independent review of such can be essential in reducing risks introduced by AI adoption.

For more information or to initiate an AI cyber risk assessment in your organization, reach out to Webcheck Security at getintouch@webchecksecurity.com.