Not long ago, I was supporting an organization in rolling out an artificial intelligence (AI) assistant for their employees’ open enrollment website. During testing, someone asked the AI assistant a straightforward question about where to go to enroll, and then asked it again using slightly different wording. The result? Two different answers.
At first, it seemed that the AI assistant needed more back-end tuning. But when we traced the responses back to their sources, the issue became clear: The AI assistant was pulling information from two documents that said different things.
This moment was a familiar lesson, one that many of us experienced long before AI entered the picture. When content is unclear or inconsistent, even the smartest technology struggles to deliver clear answers.
Even if your organization isn’t planning to implement AI this year, the quality of your content today will determine whether it succeeds tomorrow. AI relies on high‑quality fuel. In the world of HR and benefits, that fuel includes your guides, policies, intranet pages, FAQ, and vendor materials, and it must be refined before AI can use it effectively. Think about your car: It doesn’t use crude oil straight from the ground. That raw material is processed before it becomes usable fuel. The same is true for AI.
AI systems learn from the information they’re trained on. When content is outdated or inconsistent, AI reflects those issues right back to your people. That’s why it’s important to start with an AI content-readiness assessment if you want to be sure your AI tool will deliver a successful user experience. Your content-readiness assessment should evaluate the source content that feeds your AI tools to ensure that it is:
You should also have an ongoing content governance plan in place that continues to meet the criteria above. These elements form the foundation for content that you can trust and that AI can use reliably. Let’s take a closer look at why they matter.
Achieving strong AI performance starts with identifying the right source material. These are the documents your AI assistant will be trained on—and the same materials your people should trust as the source of truth for their benefits information.
Before content is used to train an AI assistant, it should be reviewed to ensure that it clearly explains what a benefit is, who’s eligible, how to enroll or register, and how to use it, with simple language and up-to-date examples. In our AI content-readiness work, we often find that this information exists but is scattered across multiple documents and, sometimes, with contradicting details.
Take medical plan enrollment as an example. If your benefits guide says new employees can enroll on day one, and your website says it takes a week for your benefits administrator to receive the new-hire records needed for enrollment, your AI won’t know which is correct. The result? The AI assistant may provide different answers depending on how a question is asked.
Inconsistent answers can erode your people’s trust in your benefits information. Training your AI assistant on clearly defined sources of information helps your people get accurate, reliable answers.
AI relies on structure to understand relationships between concepts, much like we do. When content is well organized, AI can identify what’s important, how ideas connect to one another, and which information answers a specific question. When content lacks structure, AI is forced to guess. AI-ready content is intentionally designed for clarity. It uses:
One of the highest-impact improvements we can do to make AI better is transforming dense, unstructured content into modular sections with clear, engaging headings.
This simple shift dramatically improves performance and makes information easier for AI to interpret. The bonus is that it also makes it easier for humans to read and understand!
AI looks for patterns to determine meaning. When multiple terms are used to describe the same concept, such as “HSA,” “health savings account,” “savings account,” or “spending and savings accounts,” AI can’t always tell whether those terms are interchangeable or represent different things. That ambiguity makes it harder for AI to present reliable answers.
For that reason, consistency in terminology, tone, and phrasing isn’t just a best practice; it’s a requirement for AI accuracy. The more standardized your language is, the more reliably AI can produce responses that reflect your intent.
To reduce confusion and improve outcomes, establish a style guide with unified content standards, and share it with others who create your content. This guide should define preferred terms, set expectations for tone and reading level, and clarify how benefits, programs, and policies should be referenced across all content, regardless of the author or source.
When consistency is built into your content model, AI can find the right information every time, using the right words, in the right voice, with the right level of detail.
AI readiness isn’t a one‑time project—it’s an ongoing one. Even the highest‑quality content and the best AI tool will lose effectiveness if it isn’t actively maintained. Policies change. Vendors update materials. Programs evolve. Your people’s needs shift. Without a plan to manage those changes, content and AI performance deteriorate.
A strong content-governance model verifies that your content stays current, compliant, and consistent over the years. Without a strong governance model in place, content can quickly become fragmented. Outdated PDFs and version-control issues will become an issue again. These small inconsistencies will compound. And before long, your AI assistant is pulling from materials that no longer reflect reality. Effective governance puts the right guard rails in place, so content stays accurate and usable long after the initial AI implementation.
Here are a few things to consider when creating your content governance model:
When I think back to that early benefits AI testing experience, I realize how it allowed me to look at content for AI through a new lens. Even with no changes to the underlying technology, a few content tweaks greatly improved the AI performance. Once a clear content foundation was in place, the AI assistant began delivering the kind of experience employees trust.
AI doesn’t create clarity from confusing sources, it amplifies whatever you give it. When you invest in strong, well-governed content today, you’re not just preparing for AI tomorrow. You’re building a better experience for your people right now.
Sarah Frick, VP Communications, and Phil Wolf, VP Communications, were instrumental in developing the content of this blog post.