It’s fair to say that AI without governance is negligence. Organizations cannot realize the benefits of AI unless they can manage the attendant risk exposure.

Yet according to the World Economic Forum’s Centre for AI Excellence, fewer than 1% of organizations have fully operationalized responsible AI practices. Riskonnect similarly reports: “While 93% of companies recognize the risks associated with using generative AI inside the enterprise, only 9% say they’re prepared to manage the threat.”

Is your business ready to responsibly govern AI? This article clarifies what to look for on both sides of the question.

Key takeaways

• AI governance is a structured framework of controls, policies, and standards that helps ensure responsible, safe, secure, compliant, predictable, and ethical AI use in alignment with business goals.

• Top signs you need AI governance include shadow AI sprawl, compliance uncertainty, lack of centralized AI oversight, insufficient AI guardrails, no AI incident response plan, and no AI vendor risk management.

• Key building blocks for successful AI governance include a current inventory of AI systems, clear AI use cases and goals, a documented AI accountability chain, AI user training, AI-centric cybersecurity controls, a robust IT infrastructure, and properly managed data stores.

• Capabilities pointing to mature AI governance include having an AI incident response plan, vetting third-party AI vendors, explainability of AI outcomes, conducting bias testing, monitoring AI outcomes, and requiring “human in the loop” procedures to backstop high-risk automated AI decisions.

What is AI governance?

AI governance is a structured framework of technical controls, policies, and standards that ensures your AI systems are developed and used in a responsible, safe, secure, predictable, and ethical manner while supporting innovation, accountability, regulatory compliance, and alignment with business strategy and stakeholder demands.

An AI governance program regulates how a business creates, deploys, uses, and monitors its AI systems. Without robust governance, there is no viable way to address prevalent AI impacts like cyberattacks, unauthorized use, privacy violations, biased decisions, model hallucinations, and rogue/unexpected behavior.

Indispensable elements of AI governance include:

• A foundation in the principles of transparency, fairness, and safety.

• Alignment with evolving AI standards and best practices like ISO 42001 and the NIST AI Risk Management Framework (AI RMF).

• Documented accountability, decision-making authority, and audit trails to provide oversight across the AI lifecycle from inception to sunsetting.

• Risk identification, assessment, and prioritization to drive optimal mitigation strategies across all AI risk vectors (financial, operational, reputational, technical, ethical, legal, regulatory, etc.).

• Engagement, oversight, and contributions from AI developers, users, IT, cybersecurity, legal/compliance, and especially business leadership.

What are signs my business needs AI governance now?

Problems a business would need to solve before it can succeed with AI governance include centralizing or integrated fragmented/siloed data, obtaining missing AI skills, developing an AI strategy, creating a formal process for evaluating AI use cases, and building an inventory of current AI system usage.

Perhaps most importantly, AI governance will go nowhere without support from senior leadership. Otherwise, AI is likely to remain a tactical tool that creates disproportionate risk.

Among the top indicators that your organization needs AI governance:

• Shadow AI and unapproved AI tool usage is rampant and involves sensitive company data.

• You are unsure of your legal, regulatory, and contractual AI compliance requirements and/or have no way to track compliance.

• You have no central role or team that “owns” AI oversight or strategy, making it difficult to face overarching AI challenges like accountability, predictability, and explainability in AI outputs.

• You lack guardrails to protect against data leakage and other cybersecurity and privacy risks associated with AI prompts.

• You lack guardrails to validate AI outputs, leaving you open to impacts from inaccurate results, hallucinations, biased/discriminatory decisions, or model drift.

• You have no AI incident response plan or playbook to help your firm handle AI-related data breaches, ethics violations, model errors, etc.

• You do not currently evaluate or manage the business risk associated with your AI system vendors, such as whether the tools or APIs you are using are secure.

When is a business ready to implement successful AI governance?

To responsibly govern AI, a business must move beyond treating AI in an ad hoc manner or as a strictly technical/IT effort to establish AI oversight, education/training, and proactive risk assessment.

Among the prerequisite steps for AI governance are:

• Clearly articulated and agreed business use cases and goals for all your AI tools.

• A current, dynamic inventory of all AI systems your business is using—including unsanctioned or “shadow” AI—each rated by risk level.

• A clear chain of accountability for AI system outcomes, including specific roles.

• A multidisciplinary team to evaluate AI tools and use cases, including representation from IT, business, legal, finance, HR, etc.

• A commitment to ongoing training and education for AI users that supports responsible AI use and reduces AI risks, such as AI literacy, ethics, and prompt engineering.

• An active plan to help your teams prepare for the changes that AI brings so they can work effectively and comfortably with AI rather than seeing it as a threat.

• Best-practice cybersecurity controls to proactively block attacks on your AI systems and data as well as other common threats, including network segmentation, encryption of data at rest and in transit, multifactor authentication for sensitive applications, strong identity management, and robust guardrails to protect against prompt injection, jailbreaking, model theft, and other AI-specific attacks.

• An IT infrastructure that can withstand the added demands of AI workloads, such as more storage and processing, wider network bandwidth, increased monitoring and compliance overhead, and zero trust cybersecurity investments.

• Clean, accurate data that is securely accessible to AI systems rather than siloed or “dark.”

How will we know when we’ve governing AI successfully?

For many organizations, compliant AI adoption and scalable value creation come less from turbulent transformation than from building business maturity through fundamentals like C-suite engagement, solid IT systems, effective monitoring, and access to essential AI skills.

Capabilities and processes that relate directly to mature AI governance include:

• You have a comprehensive database of all the AI systems your business is currently using, including all the AI-enabled SaaS application components.

• You have policy that spells out what AI tools are approved and what data they are authorized to process.

• You can explain the outcomes of AI-assisted decisions, such as HR or financial decisions.

• You regularly conduct bias testing on AI systems where discrimination or unfair outcomes might be an issue, or to ensure compliance with any applicable regulations (e.g., the NYC AI Act).

• Your AI policies support alignment with emerging regulatory direction like the EU AI Act, even if compliance is not yet mandatory for you.

• You have guardrails in place to reduce the risk of AI misuse or unexpected behavior.

• You continuously monitor the output quality of all production AI systems.

• You have a documented chain of accountability for AI actions and outcomes.

• You have a “human in the loop” to review, support, or override high-risk automated decisions.

• You practice responsible AI data usage, including streamlining the data volume your AI ingests.

• You have created and regularly test an AI incident response plan.

• You have a program to evaluate AI vendor risk and risk from third-party AI tools.

• You actively educate and train staff on how to use approved AI tools, including awareness of AI system accountability and human-in-the-loop procedures.

Next steps

CBIZ Pivot Point Security is a trusted advisor in AI governance and advisory. We can help you establish the foundational controls that will position your business for future advancement and growth, leveraging only the services and skills you need.

Contact our experts today to schedule a consultation.