As AI becomes more integrated into daily work, companies are faced with a new challenge—how to ensure AI-powered tools are used ethically and responsibly across the organization.
Just as we created robust frameworks for security and privacy, AI needs to be monitored because it can be running in any application or system in your electronic infrastructure. Before you read on, check out our last blog to learn why your organization should care about AI governance.
This guide will walk you through the essential steps to build a governance framework that aligns with your company’s core values and enables safe, ethical, and impactful AI use.
What is AI governance?
AI governance is the framework that ensures artificial intelligence is used ethically, responsibly, and effectively. This policy, established by an organization, outlines when the use of AI is appropriate and provides guidelines on how to utilize it safely and responsibly.
AI governance starts with documenting your AI principles and values as a company. These principles will encapsulate a high water mark that should guide the ethical, responsible, and effective use of AI across the organization.
AI governance policies focus on:
- Protecting your company’s reputation by preventing bias, discrimination, or misuse in AI systems.
- Building customer trust through transparency and accountability.
- Balancing rapid AI innovation with regulatory compliance and organizational values.
Read on to learn the steps to create an AI governance framework for your organization.
Step 1: Assemble a cross-functional team
Begin by bringing together cross-functional stakeholders from across your organization. Teams from marketing, product development, finance, HR, and client-facing roles each offer valuable insights into how AI can impact their workflows. Collaborating with individuals who have technical, legal, and policy backgrounds is equally critical for staying ahead of regulatory developments.
Step 2: Align AI principles with organizational values
Define AI principles that align with your company’s mission, vision, and strategic goals. Ask your team:
- How does responsible AI use reflect our identity as a business?
- Do our principles balance innovation with responsibility?
- What sets our company apart and how can AI enhance those qualities?
- What kind of company do we want to become?
It's especially important to consider your business model and determine how the use of AI will impact your customer base. Some questions to ask are:
- How can we utilize AI while being mindful of our ethical obligations to customers?
- Will customers consider us a responsible partner in their interactions with us?
- What would happen if customers found out there was bias or discrimination in our AI models?
As your team works through these questions, document how these ethical foundations will bring value to both your organization and its customers.
Step 3: Document ethical AI guidelines
Now that you have a baseline to work from, translate your values into actionable guidelines. Be sure to cover these areas:
- Existing company policies: Cross-check with existing policies on security, data privacy, and intellectual property. Ensure these standards align with your new guidelines.
- AI use cases: Create flexible guidelines that address existing AI use cases while remaining adaptable for future innovations. The policies should act as a foundation for evaluating new AI applications.
- Legal and regulatory requirements: Stay informed about existing and upcoming AI-specific laws and company standards, such as profiling, automated processing, false claims, intellectual property, personal and sensitive information usage, and data-use regulations. The IAPP and various legal organizations conduct regulatory scanning to offer valuable public resources to help navigate emerging AI laws.
- Validation and oversight: Include general rules for quality assurance, impact assessments, and disclosure to end users on all AI use cases.
- Include rules for impact assessments to identify risks and mitigating measures before deploying AI solutions. Impact assessments involve documenting the data being used, evaluating the potential business risks if the AI application fails to perform as expected, and outlining the measures in place to mitigate these risks.
- Incorporate human oversight to validate model accuracy and ensure the reliability of shared information. Involve your technical team in reviewing outputs for precision—some organizations use model cards to guide engineers and data scientists in building effectively.
- Include clear disclosure rules that state how to differentiate between human and AI interactions and outputs for customers. A good example of a disclosure is the notice customers receive when they are interacting with a virtual bot instead of a human being. Another example is watermarking or allowing metadata to be seen in the background of an AI-generated image.
Step 4: Evaluate and compare
Once your framework is drafted, compare it against those of industry leaders like Google, Microsoft, and Meta. Consider questions like:
- Are we addressing customer and stakeholder concerns as comprehensively as these companies?
- Do we incorporate adequate measures around transparency and accountability?
Additionally, seek legal review to ensure compliance and involve internal stakeholders for feedback and final approvals.
Step 5: Rollout and onboarding
A governance framework is only useful when employees understand its purpose and how to implement it.
- Educate your teams: Offer training during the rollout to clarify what the framework means for day-to-day roles.
- Set review timelines: Plan to revisit and revise the framework regularly (at least annually). Your AI use cases and external laws will evolve over time—your framework should, too.
- Designate leadership: Assign an AI governance owner in your organization to monitor changes in AI laws and lead updates to the framework.
Tackling AI governance with confidence
Developing an AI governance framework may sound restrictive—but it's the exact opposite. It empowers your organization to innovate fearlessly because guardrails are in place for ethical, responsible AI use.
Are you ready to take the lead in AI governance? Don’t hesitate to reach out to the experts at OneMagnify for advice or partnership.
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