Artificial intelligence (AI) is one of the biggest topics of discussion when it comes to technology, especially when it comes to company websites and e-commerce. Like it or not, society has accepted AI and is using it more and more. About 66% of people use AI, and 83% of people believe using AI will result in a variety of benefits, according to this report by KPMG.
AI is changing the way that companies do business, whether that’s how they interact with customers, collect data, or manage online experiences. This ranges from using AI chatbots to enhance customer service, building personalized content or product recommendations, or reshaping predictive search. For example, health and wellness brands are using AI to help with content ideation. This also includes building a website that is AI-ready — one that has optimized content to increase your online presence and audience engagement.
How do you do that? What does it truly mean to have an AI-ready website, and how does this affect your company overall? We’ll get into most of that further on, but what you need to understand now is that if you choose not to adapt an AI-ready content structure, you can expect reduced visibility. This is fewer potential customers finding your website, which means fewer eyes on your products and/or content. If you’re not building a website that can be easily read by AI search engines, you’re already falling behind.
Let’s take a deeper look at what it means to be AI-ready.
What Is an AI-Ready Content Structure?
An AI-ready content structure is a systematic approach to creating and managing content on your website, so that it is easier for AI systems to process the information and take action. It’s essentially breaking down your content into smaller, reusable, and consistent components, making it easier to manage, reuse, and publish across multiple platforms.
This differs from traditional content structures, which tend to be unstructured and lengthy, and created primarily for human readers rather than machine. It is also optimized for a single format. AI-ready content is highly structured, semantically rich, and, as mentioned, built to be processed by AI. That’s not to say that an AI-ready content structure is about replacing humans. It’s more about creating a cooperative workflow where AI can automate tedious tasks and allow for more creativity from your human workforce.
Some of the core components of an AI-ready content structure are schema, markup, structured data, content taxonomies, and metadata.
- Schema markup: This is using vocabulary to explicitly define entities and their relationships. It provides the framework that AI can draw from to build knowledge graphs.
- Structured data: Using logical and clear heading structures and breaking down content into focused, self-contained paragraphs so that it is easily machine-readable. This is using tables with defined rows and columns, following a fixed schema.
- Content taxonomies: A structured system to classify, categorize, and organize digital content. This divides information into modular, reusable components instead of large, undifferentiated blocks of text.
- Metadata: This is data about data, such as using tags and labels to provide essential context about the content’s purpose, audience, and relevance. It guides AI models to process the information correctly.
Benefits of an AI-Ready Content Structure
Adapting an AI-ready content structure will help your company in many ways. AI systems will be able to more accurately understand and process your structured content, which will lead to more relevant search results and a better understanding of your brand’s information. This, in turn, leads to enhanced SEO and search discoverability. The more you update your content and adhere to this structure, the more authority your brand will build, and the more likely your website is to be the top source for AI search results. Additionally, you can incorporate AI to analyze content and automatically apply relevant metadata and keywords.
It can also improve personalization and targeting. Having structured content creates a clear, standardized format for AI to easily understand and work with, which can then create customized marketing at a scale that was previously unheard of. It can also help deliver more personalized services and innovative solutions to your customers or clients.
Another benefit of optimizing your content structure for AI is that it can streamline editorial workflows. It allows for automating content assembly, which ensures compliance and enables real-time collaboration across all of your teams. Using AI can make sure that all content fits within organizational style guides, as well as performing real-time editing and readability checks. This reduces errors, makes your content quality more consistent, while also freeing up your team to focus more on higher-level creative tasks.
Steps to Build an AI-Ready Content Structure
As with many projects, to build an AI-ready content structure for your brand site, you need to start with an audit. Look at your existing content and architecture so you can identify what areas you need to focus on. This is looking for any gaps, redundancies, or places where you can semantically enhance existing content. You should also set clear goals for the AI system to make sure that your content structure lines up with what you want the AI to achieve.
Next, you should develop thematic content clusters and break content into modular, answer-focused sections. Keep them concise so that AI can easily pull data. Reinforce expertise by creating pillar pages for core topics and linking any related subtopics.
While doing that, you also need to set and implement schema and metadata standards. Use structured data to help AI systems recognize the content type and understand the context. Your content should also be natural and written in a clear, simple style. When it comes to metadata standards, there is no one, single standard that everyone uses, but there are several, such as:
- Schema.org – collaborative vocabulary developed by search engines that uses structured data like JSON-LD to annotate web content with context and meaning.
- Dublin Core Metadata Initiative (DCMI) – widely used simple standard of 15 core elements for describing digital resources.
- Croissant – created for machine learning projects and combines typical metadata with details about data structure and ML-specific information.
Lastly, you should ensure cross-team alignment among developers, content creators, and SEO. This will help to prevent poor data quality, biased AI models, and failed initiatives, while ensuring consistency, relevance, and accuracy.
Ndevr’s 3E Approach for AI-Ready Content
Why should you consider Ndever to help you develop AI-ready content for your website? Our 3E approach guides us as we work with you. We focus on the Audience Experience by using this content structure to enhance discovery and personalized content delivery. We provide you with tools and workflows that make structured content easy to produce, which focuses on the Creator Experience. And lastly, to help with the Developer Experience, we build scalable, flexible frameworks for future AI integrations.
Tech Firm Uses AI-Ready Content to Improve Searchability and SEO
To understand just how much introducing an AI-ready content structure can help, let’s take a look at how a company made it work. A large-scale tech company that helps protect networks, computers, applications, and more, decided to implement structured content and AI-driven workflows. The company incorporated metadata, which enabled AI to efficiently organize content. This made it easier for users to find relevant information. It also boosted SEO, which drove more web traffic and associated content adoption, allowing for faster updates. As a result, the company saw a significant reduction in manual effort, since AI facilitated content reuse and streamlined its documentation workflow.
Schedule Your AI-Readiness Consultation
Whether you’re ready to jump in or have a few more questions, reach out to Ndevr to schedule a free consultation.
