Implications of Artificial Intelligence Not Seeing the Whole You

Some may argue that governance slows innovation, but strong AI governance enables responsible innovation. It ensures ethical AI usage, reduces risks and aligns AI investments with long-term business success. Organizations that embed governance into AI from the start will move faster, scale smarter and build trust with stakeholders.

So, what does effective AI governance look like? The following CyBear Essentials that can foster AI governance: 

CyBear Essential #1 - Build a Culture of AI Accountability

AI governance isn’t just about policies – it’s about people. Employees at all levels must understand their role in AI’s responsible use and development. A strong culture of accountability includes:

• Training and Awareness: AI is not just an IT responsibility – it’s an enterprise-wide concern. Everyone needs to understand its risks and opportunities.
• Cross-Functional AI Governance Committee: Governance should not sit in a silo. Representatives from business, legal, security and AI teams should collaborate to ensure AI aligns with enterprise objectives.
• Transparent Communication: Regular updates on AI policies, risk assessments and governance practices keep teams aligned and engaged.

CyBear Essential #2 - Establish AI Model and Data Governance

AI systems are only as good as the data and models they rely on. Governance must ensure quality, security and lifecycle management of AI assets. Key areas to focus on:

• AI Inventory Management: Maintain an inventory of all AI models in use, track their versions and ensure outdated models don’t introduce risk.
• Model Testing and Updates: AI models should never be left to auto-update without validation. Testing against predefined evaluation metrics ensures reliability and security.
• Data Integrity and Privacy: Bias, data quality issues, and privacy risks can derail AI outcomes. Implement strong data governance policies to maintain trust and compliance.

CyBear Essential #3 - Align AI Governance with Business and Security Priorities

AI governance should not be an afterthought or compliance checkbox – it must be integrated into an organization's risk and security strategy. To achieve this:

• Integrate AI Governance into IT and Security Frameworks: AI risk management, access controls and incident response must be extensions of existing security policies.
• Measure and Monitor AI Risks: Establish KPIs for AI reliability, security incidents, bias and compliance. Governance is an ongoing process – not a one-time effort.
• Prepare for AI Regulations: Governments worldwide are shaping AI policies, but businesses shouldn’t wait. Proactively align governance frameworks with industry best practices (e.g., NIST AI RMF, ISO standards).

CyBear Essential #4 - AI for Accessibility: Why Governance Matters

One of AI’s most impactful applications is enhancing accessibility for people with disabilities. From speech-to-text transcription for the hearing impaired to computer vision tools that assist the visually impaired, AI is transforming lives. However, without governance, these innovations can unintentionally create new barriers.

Key risks and governance solutions:

• Bias in AI Models: AI-powered accessibility tools must be trained on diverse datasets to prevent biases that exclude certain users. Governance ensures rigorous testing to catch these issues early.
• Privacy and Security: AI-driven assistive technologies often process sensitive personal data (e.g., facial recognition for navigation tools). Strong governance policies safeguard user data and prevent misuse.
• Reliability and Fair Access: AI tools must be reliable and universally accessible. Governance mandates regular testing and transparent update policies to prevent tools from becoming obsolete or malfunctioning.

Governance isn’t just about compliance – it’s about ensuring AI works for everyone. By embedding responsible AI principles, businesses can create inclusive technologies that empower all users while mitigating risks.

To dive further into this topic, we reached out to Tiffani Martin, future Baylor OMBA Graduate and founder/CEO of VisioTech. Tiffani is a disability advocate and the creator of the Accessible AI Quotient Framework, driving AI governance and inclusive innovation.  When asked about AI for Accessibility, she shared the following, "Imagine being locked out of your bank account during an emergency, not because you forgot your password, but because the AI security system wasn’t built to recognize you. For millions of people with disabilities – many of whom are also people of color – this isn’t hypothetical; it’s an everyday struggle. AI is transforming cybersecurity, but there’s a blind spot: accessibility. Marginalized communities face barriers with AI-driven security features like facial recognition and CAPTCHAs, which often exclude them due to systemic biases. Businesses must adopt inclusive authentication methods, train AI on diverse datasets, and make accessibility a security standard. Ignoring accessibility is not just a risk but a missed opportunity, as the disability community controls $13 trillion in global purchasing power. Companies that prioritize accessible AI security reduce cyber risks, build trust, and expand their market reach. AI should be a force for security, not a barrier to access."

Tiffani advised the following measures for businesses to implement without compromising security:

• Rethink Authentication Methods:
  • Adopt flexible, inclusive authentication methods that meet diverse needs. Passkeys, FIDO2 authentication, and adaptive verification can provide the same level of protection without excluding users.
  • Replace CAPTCHAs with AI-driven bot detection that doesn’t require users to solve puzzles or identify blurry traffic lights – especially when AI struggles with darker skin tones or screen readers.
• Train AI to Recognize Diverse Users:
  • AI security models must be trained on datasets that reflect disability-related variations and racial diversity to prevent bias.
  • Conduct comprehensive bias audits that assess both accessibility and racial disparities before deploying new security features.
• Make Accessibility a Security Standard, Not an Afterthought:
  • Ensure compliance with ADA (Americans with Disabilities Act), WCAG (Web Content Accessibility Guidelines), and NIST SP 800-63 (Digital Identity Guidelines), considering broader algorithmic fairness regulations that address bias in security protocols.
  • Ensure security tools are tested with diverse users, including marginalized racial groups and people with disabilities, before deployment – real-world usability is just as vital as theoretical security.

Final Takeaway: Governance Is Action

The significance of governance aligned to business goals is a recurring theme in our CyBear Essentials articles. AI governance isn’t just about setting rules; it’s about taking action to ensure AI is safe, transparent, and aligned with business goals. Effective governance requires purpose and intent, applicable to organizations of all sizes. Organizations that proactively implement AI governance will not only reduce risks but also gain a competitive edge in responsible AI adoption. The bottom line? Act now on AI governance – your business will thrive later.