AI solutions are only as good as the content that powers them. When content lacks the necessary quality, structure, and enhancement, AI tools will fail to appropriately understand it, leading to a high risk of “hallucinations,” as well as distrust and frustration from your end users. EK is expert not just in content operations, governance, and design, but also in advanced semantics and AI at every stage from strategy through implementation. We’ll combine these unique areas of expertise to assess your content and support you to ensure your content model will provide enough context to reduce hallucinations and improve AI initiative outcomes.
What Makes Content AI-Ready?
Content that is ready for AI is:
- High quality: The tried and true “garbage in/garbage out” applies to AI-ready content. Reduce the volume of content by cleaning out content that is not current or is duplicate.
- Relevant and accurate: Ensure all content has a purpose. Is the content aligned to business strategy or task completion? Is the information presented correct and reliable?
- Contextualized: Modeling your knowledge domain establishes a foundational relationship between your content strategy and business strategy, providing context to enrich the meaning AI derives from content.
- Semantically rich: Metadata and contextual tags provide essential context like purpose, audience, and relationships to other content guiding LLMs to interpret content accurately, ensuring AI-driven interactions are meaningful and relevant.
- Structured and standardized: Structured content is explicit, relevant, and clear in its relationships, providing additional context to LLMs.
- Governed: Content governance includes standardization, quality control, and proper metadata tagging, ensuring that once content is AI-ready it stays that way over time.
What is the AI-Ready Content Accelerator?
Working with EK’s content strategy, artificial intelligence, and semantic solutions experts will help your team:
- Analyze the current state of your content and metadata for factors affecting AI readiness.
- Develop and prioritize use cases to validate the content model’s impact on AI outcomes.
- Model the structure and relationships of prioritized content to increase context and compatibility with GenAI solutions.
- Transform and enrich prioritized content.
- Test the improved content model for impact on prioritized AI use cases.
- Develop a strategy and roadmap to move your content model and content operations toward an AI-ready target state.
Key Deliverables
- AI-Ready Content Primer: Technically rigorous guidance about what makes content AI-ready as well as best practices for improving content along all of the factors which improve AI readiness.
- AI-Ready Content Analysis Report: Technically rigorous report of the current state of your prioritized content and its current AI-Readiness with tactical data points to enable content cleanup.
- Knowledge Model: A conceptual map of key business concepts which informs the design of your MVP content model.
- MVP Content Model: Content structure and relationships at the right level of technical rigor for your prioritized use cases.
- Content Operations Expansion Plan: As a companion to the content model, the expansion plan provides key insights into how to scale the MVP content model and supporting content processes.
Key Outcomes
- Reliable, high quality content that is validated for relevancy, currency, deduplication, accuracy, and semantic richness.
- Data to demonstrate the impact of high quality content on prioritized AI use cases.
How it Works
