Establishing AI Guardrails For Content: How To Protect Your Brand’s Voice

What are AI guardrails for content?

AI guardrails are technology that’s used to make sure your LLM and its output are compliant with rules and standards. Depending on the type and use case, these can be regulatory requirements as well as ethical principles or corporate standards. 

For successful AI content creation, enterprises need AI guardrails for writing standards. AI guardrails for writing standards are a set of capabilities that make sure that AI-generated enterprise content is safe and compliant with both regulations and company standards. They’re basically content governance for AI-generated content in action.

In this blog, we’ll find out how your company can implement AI guardrails to improve and maintain content quality and compliance. 

Why it’s essential for enterprises to guardrail AI content creation

Looking at numbers around generative AI usage, our first impression is that many enterprises are adopting generative AI successfully and see benefits:

• 79% of businesses report an increase in content quality thanks to AI, according to Semrush.
• 75% of global knowledge workers already use generative AI, Microsoft reports. 
• 90% of these knowledge workers state that AI helps them save time, followed by 85% who use AI to be able to “focus on their most important work”, and 84% who value AI for the creativity improvement it provides.

While those numbers look great, there are still downsides to generative AI that you want to protect your company from. And here’s where guardrailing your content comes in. Let’s see which benefits guardrailing your content has and which generative AI challenges these benefits address.

Guardrails promote responsible AI usage

By guardrailing your content, you help the content creators use AI responsibly. What does that mean from an end-user perspective? Using AI responsibly means supporting AI solutions that “address ethical concerns – particularly with regard to bias, transparency and privacy.” (Source)

Remove inherent bias

Generative AI is trained on content that was created and curated by humans. As humans are prone to bias, bias can find its way into the models we use for AI content generation.. This opens the door to your  Large Language Model (LLM) output ending up being biased, too. But don’t panic: There are AI guardrails to catch biased content before it’s used by your model. And in case biased or non inclusive legacy content made it into your model before applying input guardrails, there are other AI guardrails that make sure generated content is free from bias, though.

If your content speaks to a diverse audience, you want it to be as inclusive as possible, so guardrailing your AI to remove or prevent bias is essential for you. There are multiple approaches to less biased AI content.

Here’s an example: You can use software like Acrolinx to guardrail which content is used for training your LLM. This means you can check your whole content inventory for inclusive language, and just the pieces that comply with your inclusive language goals become your LLM’s training data. Thus, you drastically reduce bias in AI.

Create factual content

Similar to bias, non-factual content and so-called “AI hallucinations” are a threat to great enterprise content. Your readers — hopefully your future customers — rely on factual content to build trust in your brand. Content that’s intransparent or simply a bit “off” impairs brand trust. So you need AI guardrails in place to avoid non-factual AI-generated content and provide transparency instead.

Ensure privacy

Another type of guardrails for AI focuses on privacy and security. LLMs process data in various ways. As content is data, responsible AI makes sure your confidential data stays confidential and your enterprise data remains yours. If you use technologies like Azure AI in your AI applications, you can benefit from built-in privacy guardrails.

Why enterprises should care about responsible AI usage

For sure, there are several reasons why enterprises should care about responsible AI usage, with two central aspects being the following:

1. Regulations: With generative technologies being here to stay, regulations are built out around responsible AI usage, the EU Artificial Intelligence Act being just one example. As an enterprise, it makes sense to consider such regulations before they become binding for organizations like yours. By keeping up with the regulatory landscape, you maintain an overview of what’s coming, which can even be a competitive benefit. It demonstrates thoughtfulness and awareness for topics that matter for enterprises and their customers as well.
2. Trust-building: Besides regulatory compliance, responsible AI usage helps you build trust with your customers. In “Trust in AI: Combining AI & the Human Experience,” Luke Soon writes: “In an era where artificial intelligence (AI) systems are becoming increasingly interwoven in our daily lives, or embedded into our life-journeys, the emphasis on responsible AI obviously underpinned by trust in AI has never been more crucial.”

Maintain brand voice

Another type of AI guardrails is what we at Acrolinx call “AI guardrails for writing standards.” These guardrails make sure all LLM outputs are aligned with your corporate writing standards. That helps maintain your brand voice and consistency across your company and the various types of content assets your teams create. AI guardrails for writing standards are implemented at different stages of your content supply chain. An example are import guardrails that make sure only great content is used for training and grounding your corporate LLM.

Benefits of LLM guardrails for writing standards

Guardrailing your AI-generated content helps create AI content that’s true to your corporate writing standards. Now, we’re having a closer look at the associated benefits. We’ll examine both process-related and output-related benefits of LLM guardrails for your corporate content.

Process-related: Where do LLM guardrails for writing standards help

Ensuring high-quality content for fine-tuning your AI models

The saying “quality in, quality out” holds especially true for AI. By implementing content quality assurance measures, businesses can make sure that the data used to fine-tune LLMs meets their organizational standards. This step significantly improves the output generated by your models, leading to better performance and accuracy.

Improving generated AI output quality

The quality of AI-generated content is crucial and catching errors early can save time and effort later. Acrolinx integrates with your generative AI processes, checking the quality of generated content before it reaches your writers. This automation makes sure the content aligns with your company’s writing guidelines, maintaining consistency with your brand’s voice and style.

Real-time content quality assurance for writers

Enable your writers with instant editorial feedback directly within the tools they use every day. The Acrolinx sidebar allows both human and AI-generated content to be checked instantly for adherence to your company’s style and quality standards. This helps your team produce content that aligns with enterprise goals without disrupting their workflow.

Automated content governance

Integrating Acrolinx into your content creation workflows allows for automatic quality checks and scoring, so only top-tier content gets published. This automated system acts as a gatekeeper, holding content back for review if it doesn’t meet the required quality standards. This way, content that’s not great yet doesn’t go live.

Continuous monitoring of published content

As industries evolve, so do content standards. Often propelled by regulatory changes, product updates, or business shifts. Acrolinx helps you stay on top of these changes by continually checking your published content for adherence to current writing guidelines. This ongoing assessment saves time and effort, preventing the need for manual reviews while making sure your content remains compliant and relevant.

Output-related: How content benefits from LLM guardrails for writing standards

With guardrails used to make any LLM output high-quality and true to your brand, you can subsequently experience various content-related benefits. Here are some examples:

Consistency in brand voice and tone

One of the biggest challenges for organizations is maintaining a consistent brand voice across all content. By setting clear guardrails for writing standards, an LLM can align every piece of content with your brand’s personality, tone, and values. The LLM produces content that feels authentic and reflective of your brand, reinforcing identity and driving recognition. Whether it’s documentation, a formal whitepaper, or a social media post.

Enhanced regulatory compliance

Guardrails allow organizations to achieve compliance with industry-specific regulations and standards. This is especially crucial for sectors like finance, healthcare, and legal, where inaccurate or non-compliant content can result in hefty fines or legal liabilities. By fueling your LLM with compliant terminology and implementing guidelines that foster understanding and minimize confusion, you actively lower regulatory risk. This helps your organization avoid costly errors and preserve its credibility.

Improved clarity and readability

Guardrails also improve clarity by making sure content is easy to understand. This includes avoiding jargon, simplifying complex ideas, and ensuring sentences are concise and coherent. Clarity not only makes your content more accessible but also boosts engagement, as readers are more likely to stay invested in content that’s easy to follow and free of ambiguity.

Strengthened customer trust

High-quality content that consistently delivers accurate, reliable, and brand-aligned information fosters trust. When customers receive content that is always clear, truthful, and in line with their expectations, it builds a sense of reliability. Guardrails help avoid misinformation, over-promising, or deviating from your brand’s core values, creating a positive relationship with your audience. In turn, this trust fuels customer loyalty and brand advocacy.

Adaptability across channels

With the right guardrails in place, LLM-generated content is easily adaptable to different formats and channels, whether it’s for blogs, email newsletters, social media, or presentations. With set writing standards, your content remains engaging, consistent, and high-quality, regardless of the medium. This level of consistency unifies your brand experience across all touchpoints, improving the overall customer journey.

Implementing LLM guardrails for writing standards isn’t just about enforcing rules; it’s about shaping content that consistently represents your brand while staying compliant with regulations and building trust with your audience. These benefits collectively improve brand reputation, drive engagement, and safeguard the integrity of your communications — for long-term success.

Challenges of implementing LLM guardrails for writing standards

Implementing guardrails for writing standards is necessary for successful enterprise content, but it’s not an easy thing to do. There are challenges you need to be aware of to be able to handle them successfully.

Challenges related to technical and resource aspects

First, we’ll have a look at technical and resource-related challenges, highlighting two exemplary challenges.

Integrating guardrails into applications across your organization

There are also complexities when it comes to integrating guardrails into existing systems. You need to make sure your LLM connects with your content tools, such as content management platforms. This kind of connection is needed to apply real-time guardrails across multiple applications and departments within the organization, so you want to make sure your LLM works well with all tools along your content supply chain.

How to tackle this challenge: When you’re searching for technology to guardrail your LLM content, its ability to support different content platforms and tools should be an important decision criterion. Acrolinx is an example of content governance software that applies guardrails to your AI brand content and integrates with dozens of content tools.

Enterprises change, and so do guardrails

As enterprises evolve, so must their guardrails. Adjusting the guardrails to reflect updates in brand strategy, tone, or messaging over time is essential. Also, staying up to date with changing regulatory standards—particularly in industries like finance or healthcare—requires organizations to continuously update their LLM guardrails accordingly to remain compliant.

To make sure AI-generated content consistently complies with the established guardrails, continuous oversight is necessary. But auditing and reviewing content at scale to identify any errors or lapses in adherence to writing standards, can be resource-intensive.

How to tackle this challenge: It’s crucial to always keep an overview of your content landscape to be able to successfully address change—be it continuous change or events such as mergers and acquisitions. Make sure you have automated content quality checking and comprehensive analytics in place, so the monitoring and quality assurance efforts don’t solely fall on human contributors.

Challenges related to writing standards

You need to make sure AI content sounds human-like

One major challenge is ensuring that LLM-generated content doesn’t become robotic or overly formulaic because of overly restrictive rules. It can be difficult to preserve natural language flow and creativity while still following the strict guardrails that maintain quality and brand alignment.

Inclusivity, bias, and cultural nuances

Eliminating bias from AI models while maintaining inclusivity and ethical content is another significant challenge. Despite the best intentions behind guardrails, there’s always the risk that the LLM may unintentionally reinforce harmful stereotypes or biased language, making it critical to constantly review and refine these safeguards.

A related challenge involves managing linguistic and cultural nuances when scaling LLM guardrails across global markets. Accounting for regional differences while still making sure that the AI-generated content follows the localized brand voice can be difficult, especially while maintaining overarching corporate standards.

Balancing Personalization with Standardization

Striking the right balance between personalization and standardization is crucial. There’s some tension between delivering personalized content for diverse audiences and maintaining a consistent brand voice and regulatory compliance. Also, creating adaptable guardrails that work for different content types or formats—such as blogs, social media, or formal reports—can be a complicated process.

How to tackle these challenges

The solution is content governance: “Enterprise content governance is a systematic approach to managing and overseeing your company’s content strategy. It includes capturing and organizing content, measuring its performance, guiding content creation to meet goals, and maintaining its quality and relevance over time.“

To achieve content governance for generated text and human-written content as well, content governance software like Acrolinx is your go-to solution.

Establishing digital brand guidelines with Acrolinx

AI guardrails for writing standards are content governance for AI-generated content in action. By integrating Acrolinx into your content supply chain, you’re guardrailing your content to make sure it’s always doing its best job for your brand and serves its intended purpose.

Whether your company has written 100,000 words or billions (like our customer Microsoft), Acrolinx makes sure each one reflects your style guide. Customers enjoy massive efficiency gains without sacrificing standards through AI-powered live writing assistance, automated reviews and quality gates, and analytics comparing content quality with performance.

Interested in learning how Acrolinx helps you not only establish digital brand guidelines, but also set up comprehensive content analytics in the age of AI? Don’t miss our eBook “Content Analytics For The Era of AI“!