Three Steps to Build an AI Governance Framework for Your Ad Operations

During our Ad Age webinar on how to build a digital workforce using AI agents, 33% of polled attendees said they don’t have AI governance in place for their advertising operations. 

AI governance is critical for your advertising business to safeguard data—both yours and your clients—while still getting maximum value from your AI tools. Without the right guardrails in place to ensure proper data security, you risk running non-compliant ads or the integrity of your organization. 

If you still need to establish AI governance at your company or if you’re looking to revise your practices for additional security measures, this framework can ensure your agency manages AI usage responsibly to support (and not jeopardize) your business goals.

Step 1: Mapping AI opportunities, needs, and tools to your company goals

Before implementing AI tools, take the time to understand the role AI currently plays at your company and what you need it to do. Auditing existing practices and aligning AI tools with customer goals will help you create a strategic roadmap for AI implementation that maximizes ROI while enforcing data safety.

This foundational step helps you identify what's already working, where the gaps are, and how AI can best help your human teams hit client goals. 

1. Audit your company’s current AI usage. Before you can set up proper AI governance, you need to know how teams use AI today. Conducting an internal audit is beneficial for two reasons: understanding which AI tools your team finds useful and identifying any unauthorized tools (employee transparency is important!). Once your audit is complete, it’s easier to identify gaps in AI capabilities or misalignments with your company’s policies.
2. Clarify and document customers’ objectives. Knowing your customers’ goals can help you focus on integrating AI tools to help your team successfully hit those goals. For example, are they looking to improve conversion rates across multiple channels? Do they want to test a variety of new marketing messages? Are they expanding into new markets? Documenting these goals will enable your team to build performance benchmarks so you can measure AI’s effectiveness in helping you achieve them. 
3. Evaluate your current capabilities. AI can be a powerful tool in your tech toolbox or it can sit unused. Yes, an AI audit can help you see what tools your teams use the most. However, you should also look at which workflows, processes, or tasks take up most of your team’s time. Typically, the four biggest time-sucks for advertisers are campaign management, reporting, budgeting, and campaign launches. (Fortunately, these are also four workflows where advertising AI agents can impact operational efficiency the most.) 
4. Vet new AI tools to fill in the gaps. Ensure your AI strategy aligns with your business strategy, proprietary data, and value prop. AI as a standalone solution won't help you scale (in other words, you can’t do it all with just ChatGPT). To be both effective and governed correctly, AI needs to be used within a closed system that can access your primary data sets. Pay particular attention to a tool’s interoperability (the ability to integrate with your existing tools/systems) and data egress policies (where, when, and how data leaves the company’s infrastructure). The sweet spot will be tools that simultaneously help you achieve your customers’ goals while giving your team more capacity.  

Step 2: Designing your AI governance framework: human oversight, AI usage boundaries, and compliance protocols

Creating clear guidelines for AI usage is essential for both control and accountability. In this step, you’ll define boundaries between AI and human responsibilities via effective oversight protocols. Diligently documenting AI’s boundaries and clarifying who's responsible for what ensures that AI remains a tool that enhances human capabilities rather than a black box of potential vulnerabilities where data security may be compromised.

This step makes up the bulk of your AI governance framework: it builds off your AI audit in step 1 and informs the feedback loop in step 3. 

1. Outline what safe AI use looks like for your business. As your AdOps teams start using AI tools in their daily workflows, establish clear boundaries for what AI can and cannot do. This is particularly important when it comes to creative ideation or task execution. For example, maybe AI can generate ideas or new ad copy, but all AI-generated materials must pass through a human gatekeeper before going live. Or, instead of pushing this work back on your teams, can you enforce compliance by using automation to flag non-compliant content before publishing? Think about what makes sense for your company at the intersection of efficiency and compliance.
2. Codify AI governance standards. Be sure to document essential rules that all your AI tools must follow. This includes specific customer guidelines, brand standards for each customer, and any relevant industry regulations (e.g. HIPAA, Equal Housing laws, etc.). Once complete, use this structured list of requirements to inform all the LLMs that create content or make decisions for your company. 
3. Assign ownership of AI tasks to human team members. The best way to enforce AI checks and balances is to designate roles and responsibilities for your team members clearly. Clarify who is in charge of overseeing AI usage for specific workflows. For instance, you may have one team member manage ad copy compliance checks and another oversee brand compliance for media assets. (Automation can make these compliance checks faster by automatically flagging any issues and bringing them right to the responsible team member.) 

Step 3: Evolving your AI governance with ongoing feedback and process iteration

AI governance isn’t a one-time task. You must establish ongoing monitoring and improvement checkpoints to continuously align AI with evolving needs, compliance changes, and new tools. 

Building structured feedback loops and regular reviews into your AI governance practices means your AI system can dynamically learn, adapt, and evolve alongside your organization. As a result, you can make sure AI continues delivering value without putting your advertising business at risk. 

1. Establish feedback loops that keep AI on track. Create a structured process that captures feedback from both internal teams and customers about AI workflows. Checking in on AI performance, sharing examples of outputs that need to be tweaked, and promoting any major AI-powered wins are easy ways to assess if your AI tools are working as intended to help your customers reach their goals. 
2. Regularly review AI and automation outputs. You should also take the time to evaluate AI’s performance against your company’s governance standards. For example, is AI optimizing budgets efficiently without overspending? Are AI-generated ad assets aligned with current brand messaging requirements? Don’t forget to check that your human AI liaisons are performing their oversight tasks, too. At a minimum, you should schedule quarterly reviews of AI outcomes and governance policies. This can ensure that your AI tools remain aligned with evolving client priorities and industry standards.
3. Iterate governance rules to align with changing goals, messaging, and strategies. Take the time to integrate any “lessons learned” into your governance frameworks. For instance, if AI tools frequently produce off-brand content, refine your inputs and prompts to help AI learn what you want to see. You’ll also need to expand your company’s governance protocols to account for new AI capabilities as they’re introduced into the market (or into your company).

Setting AI guardrails for reduced risk and greater success

No other technology has taken over our world as rapidly as AI. Recent studies show that generative AI has “been adopted more quickly” than both the Internet and computers. 

As Peter Parker knows, though, with great power comes great responsibility. AI can help your advertising team achieve incredible things, but there are just as many ways that AI can jeopardize your business. 

Our society is collectively learning what AI can do, what it shouldn’t do, and how best to utilize its capabilities beneficially. Establishing clear AI governance parameters and usage boundaries is the best way to ensure AI works safely within its wheelhouse. You’ll be able to gain all the positive advantages of AI—time savings, advanced computation, content generation, and more—without the risk of exposing customer data.  

If you want to learn more about best practices for AI governance in advertising, check out our Ultimate Guide to AI and Automation in Advertising. You can also learn about practical applications for AI and automation in advertising operations and how to determine where AI can make the biggest impact at your ad agency. 

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