of-generative-AI-800x450.png" class="attachment-large size-large wp-post-image" alt="Rethinking content governance in the era of generative AI" style="margin-bottom: 15px" />Marketing has traditionally served as the “guardian of the brand,” ensuring organizational consistency across all channels. AI creates brand assets at scale, offering speed and efficiency. However, it also introduces new risks. Here’s how it changes guardrails and governance and what to do about it.
Guardrails vs. governance
While closely related, guardrails and governance serve different but complementary functions in AI-powered marketing organizations.
Guardrails are the parameters, principles and rules guiding the daily creation of marketing materials. Think of editorial style guides and brand guidelines. They help maintain consistency, giving materials developed by different groups of individuals a similar grounding. Guardrails provide a “single source of truth” to arbitrate subjective decisions about creativity.
A fashion brand editorial guide might state the tone is chic and aspirational vs. casual or humorous.
Governance refers to formal rules, frameworks and oversight systems that are applied to marketing efforts. It ensures marketing is ethical, compliant and aligned with broader organizational goals. In marketing, governance can include data privacy policies, legal compliance, risk management and ethical considerations like truth in advertising.
How AI does and doesn’t change the game
AI offers marketers the ability to produce creative materials at an unprecedented scale. Instead of A/B testing, marketers can programmatically test from A to infinity. With that scale comes the risk the AI will drift away from the established brand — including making up things out of whole cloth.
Dig deeper: U.S. state data privacy laws: What you need to know
Some rules — like color palette, fonts and spacing — can be hard-coded into AI’s parameters. But other rules, like tone-of-voice are more subjective and open to interpretation.
For example, AI used for a luxury automotive brand must learn technical specifications and the brand’s specific language. It would have to understand the difference between “powerful” and “dominant” or “sleek” vs. “sophisticated.”
In some ways, however, the game doesn’t change. AI needs time to learn a brand, just like a new marketing writer would. It needs to be trained on voice, tone, nuance and what to say and not to say.
Setting up guardrails for AI marketing
AI evolves, so it isn’t enough to set guardrails once and forget about them. Outputs must be monitored and refined. This means regular audits, feedback loops and fine-tuning to ensure brand alignment and correcting deviations.
Instead of creating content exclusively, marketing writers may also spend some time reviewing and refining AI output.
It’s not that different from a senior copywriter reviewing a junior copywriter’s work. In this case, the junior copywriter is AI, and the fix may be editing the copy or adjusting the output parameters.
One parameter is “temperature,” which controls the randomness of the output. Lower temperatures produce more predictable, conservative content, while a higher temperature delivers more creative but riskier content.
Many marketers have yet to master training AI on tone of voice. Organizations need to upskill marketers in this area if they want to get the most from their AI investment.
Templates for scalable content creation
As AI allows more people to create content, marketers will take on the role of “keepers of the master templates.” These templates, along with AI guardrails, can be used across various departments or teams to create content that stays within brand guidelines.
This can keep departments like HR or finance from needing to hire outside help to create materials because marketing is overloaded. AI-guided templates reduce the amount of repetitive work marketers need to do, allowing them to focus on improving quality for higher-value work.
Protecting the brand with bovernance
AI governance involves creating formal structures and policies that address issues related to AI use in marketing, including:
- Data privacy and security: Ensuring AI tools do not mishandle customer data.
- Ethical considerations: Preventing AI from perpetuating bias or promoting harmful content.
- Transparency: Ensuring customers know when AI is used in marketing content.
Consider developing an AI Council to oversee AI marketing practices. This cross-functional group of key stakeholders will ideally include representatives from legal, data teams, marketing, ethics and technology.
Challenges in forming an AI council
The AI Council defines AI usage policies, ensures compliance with privacy laws and tracks copyright and other legal implications.
Because AI evolves so rapidly, decisions about its use need to be made quickly. AI Councils must operate fluidly to keep up with AI’s rate of change. They must understand that guardrails or policies are “for now” and be able to update them regularly.
Practical steps to set up an AI council
First, see if an AI Council exists in another part of the company. If so, join that council as appropriate. Because these councils are cross-functional in nature, there’s no point in creating a new one and inviting many of the same people.
If a council doesn’t exist, identify potential members. You will need a mix of expertise, including legal, marketing, data, ethics and technology. Look for people interested in AI who can execute fast and collaborative decision-making.
Next, form a charter to determine the scope of the council — including what is beyond its purview. AI is a big space. You don’t want to get bogged down in something like a machine learning tech stack if another part of the organization can handle it.
Activities for the council should include:
- Conducting regular audits of AI tools and outputs.
- Developing policies on data usage, privacy and security.
- Setting standards for transparency and ethical AI usage in marketing.
AI governance isn’t a one-time exercise. Councils should meet at least monthly — and be able to act quickly. They should be responsible for reviewing new AI developments and ensuring the organization’s practices remain up-to-date.
Proactive governance
As AI becomes better integrated into marketing, marketing teams’ role as “keepers of the brand” will evolve. AI can create content faster and at a bigger scale. This requires strong guardrails and governance to protect brand integrity and ensure ethical, compliant AI usage. Marketers will play a bigger role in creating systems that let AI be used safely and effectively.
The key to success is continual training, monitoring and refinement of AI outputs to ensure the guardrails hold true, as well as an agile governance system that keeps up with the pace of AI development.
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