There are plenty of jobs designed to protect others. Think of a lifeguard! A lifeguard doesn’t just save lives in an emergency. They also help prevent emergencies from happening in the first place. 

Lifeguards make sure you can enjoy your time at the beach or pool without getting hurt. They help remind us to be responsible and sensible—like maybe you shouldn’t dive headfirst into the shallow end of the pool. They also let us know when you need to get out of the water. 

In the same way that lifeguards provide practical guidelines for our time in the water, AI governance programs provide that same guidance and oversight for businesses ready to invest in AI technologies. 

Strong AI governance programs provide real, tangible value to businesses that use AI tools and models. So what does that look like?

Emerging AI regulations and the intersection between AI, your business, and compliance

AI is growing and changing at a rapid rate, and regulations are striving to keep pace with them. It’s a tall order, but regions like the EU and the U.S. are at the forefront of these regulatory efforts, each with distinct approaches:

  • European Union: The EU’s AI Act is one of the world’s first comprehensive AI laws. The act classifies AI systems into four risk levels (unacceptable, high, limited, and minimal) and imposes strict regulations on high-risk applications, including critical infrastructure and law enforcement.  
  • United States: While the U.S. currently doesn’t have comprehensive federal AI regulation, it has issued guidelines such as the Blueprint for an AI Bill of Rights and the recent Executive Order on AI, which focuses on AI safety, security, and ethical use. At the same time, state-level regulations, like in California, Connecticut, and more, include provisions that, to varying degrees, address the US of AI.
    • Note that Utah recently was the first U.S. state to pass an AI-focused consumer protection law, and Colorado has recently passed one as well. 

The benefits of an AI governance program for your business

The key to seeing the full ROI is an intentional, organized build-out. With the right setup, your AI governance plan can:

  • Protect your company and stakeholders from unnecessary risk.
  • Establish frameworks that enforce the safe and reliable application of AI.
  • Create open dialogue between departments on the uses and detriments of AI.
  • Act as a resource for employees with questions about the use of AI in their roles.
  • Devise expedient, practical review mechanisms for new potential AI applications.
  • Increase trust between you and your consumers.
Downloadable Resource

AI Governance Roadmap: Business Guide


 
 
Our AI Governance Roadmap guides you to success in developing an AI governance program.

Learn More

How to build an AI governance program that actually works

No one wants to saddle themselves with a half-baked governance program without clear goals, structure, policies, or leadership. But you don’t have to! We’ve got six steps to come up with a sustainable, effective AI governance program.

1. Start with your “why”

You may (or may not) be required to establish an AI governance program to comply with various regulations. But the most impactful motivation rarely is just because of a legal requirement—it’s when you have a strong “why” backing it up.  

Why is an AI governance program important to your business, your consumers, employees, and other stakeholders? How will they benefit when the program is in place? 

Answers will depend on your specific company, clients, industry, geographical location, and more. Regardless of the specifics, though, when you clearly understand the “why” of your AI governance program, you’ll be better positioned to generate internal buy-in, create effective policy, and select the best team for the job. 

When in doubt, you can always revisit your “why” to get your governance program back on track. 

2. Choose your stakeholder group wisely

AI governance programs don’t run themselves! They’re powered by a team of experienced professionals who will ultimately oversee how AI is used in your business. 

Who should be involved in your AI governance program? Both AI and privacy impact many (if not all) areas of your business. As such, your team might include individuals from departments like:

  • Legal
  • Compliance
  • Risk
  • Information technology
  • Marketing
  • HR 
  • Customer service

When building your team, think realistically about who needs to be in every meeting. There’s a fine line between including the right stakeholders and having too many cooks in the proverbial kitchen. 

Identify core the activities of AI governance team

The best group projects have clear lines of responsibility and expectations established from the outset. To avoid getting bogged down, articulate how different activities will be approached: 

  • Data governance to ensure data is properly collected, prepared, of good quality, updated, without bias, etc.
  • Legal compliance to determine which laws apply to your business as it relates to AI.
  • Risk management and mitigation to assess risks associated with AI use and protect your business and consumer data. 
  • Accountability to maintain an auditable account of your AI governance program and its policies and procedures. 

Equip your AI governance team with the right information

Even for seasoned professionals, AI involves a lot of new lingo. Before you expect your team to take on AI governance, everyone should be on the same page. Decide how you’re defining AI-related terms like machine learning, generative AI, hallucinations, and more. This will keep conversions productive (and comprehensible). 

It’s also vital to train your AI governance team, both at the outset and on an ongoing basis. Not to be a broken record, but AI is rapidly evolving and it’s imperative to keep your team fully versed on AI risks, how data and AI intersect, acceptable uses, and its overall impact on your company.  

3. Map your systems

Now that you have a team in place, it’s time to figure out what you’re working with. 

You can start by creating an AI inventory to get a bird’s eye view of what AI tools your employees currently use, how they use them, and the implications related to risk, data privacy, and operational efficiency. Remember, your data is going into these tools and their training model, so it’s important to do a deep dive here to understand what they are doing with your data.. Overlooking tools or vendors could jeopardize your privacy program, your business, and consumer trust. 

This inventory can be a separate project or—if you want to be efficient about things—done alongside an ongoing data inventory. 

You should also identify what regulations you’re obligated to comply with. Because of the scope of AI, it’s possible you’ll also need to consider obligations for intellectual property, antitrust, and employment laws.

4. Define your governance framework 

You’ve got your why. You’ve got your team. You’ve mapped your systems. All ready to go? 

Not quite. You need to also define how you’re going to run the program. In other words, you’ve got to figure out your governance framework. 

If you already have a governance framework in place, you can apply those structures to your AI governance program. But if you don’t, reinventing the wheel isn’t necessary! See below.  

Starting from scratch? Consider the NIST RMF AI Risk Management Framework

The U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) published their Artificial Intelligence Risk Management Framework (RMF) in 2023. The RMF isn’t mandatory, but it is a great resource for organizations looking to design their own AI governance plan. 

The AI RMF Core provides four key areas of focus: 

  1. Govern
  2. Map
  3. Measure
  4. Manage

Each of the four focus areas have their own subcategories. For example, the Govern function includes seven subcategories to cover in your governance plan:

  1. Internal policies, processes, procedures, and processes
  2. Accountability structures
  3. Workforce diversity, equity, inclusion, and accessibility processes
  4. Organizational team structure
  5. Engagement processes
  6. Training on how data is processed, acceptable uses, and how everything works together
  7. Policies and procedures for third-party vendors that provide or use AI

You can access additional suggestions and resources through the AI RMF Playbook, which the NIST updates semiannually in response to any industry or legislative updates. 

5. Conduct an AI risk assessment

Not all businesses will face the same risk. List out your potential AI risks and assess which risks should be prioritized over others. 

Need some help? Use the AI RMF Generative AI Profile to identify and prioritize risks related to generative AI, and decide on actions that will align your operational procedures with your goals and priorities. 

Once you have clear priorities, you can create an actionable game plan that will make a positive impact for your business.

Ready to dive into AI technologies?

Red Clover Advisors helps businesses set up and maintain AI governance programs that balance risk mitigation with leveraging the power of AI technologies to grow your business. We help organizations establish AI programs for responsible AI use and development. 

Don’t get caught in the storm. Contact us or subscribe to our newsletter below to learn more about navigating AI and data privacy.