Knowledge Assessment for Generative AI Projects
Organizations are seeking innovative ways to harness the potential of ChatGPT, LLMs, Generative AI, and other cutting-edge AI technologies to revolutionize knowledge management and elevate the experiences of both employees and customers. Among these advancements, Retrieval-augmented generation (“RAG”) emerges as a powerful differentiator that places internal knowledge at the forefront.
With RAG solutions, organizations unlock a multitude of benefits and mitigate risks:
- Protects valuable intellectual property, safeguards proprietary knowledge, and differentiates you from competitors. Eliminates potential hallucinations, guaranteeing the delivery of accurate and reliable information to users.
- Complies with brand guidelines, ensuring that all generated content adheres to the established brand identity and voice. This consistency strengthens the organization's reputation and builds trust with employees and customers.
- Provides comprehensive audit trails for answers, empowering organizations to track and analyze the knowledge management process. This level of transparency enhances accountability and enables continuous improvement and refinement of knowledge resources.
What Is the KM for AI Readiness Assessment?
Embark on a two-week investigation into your organization's alignment, knowledge management, and technical capabilities. Uncover the essential factors that can impede your ability to integrate state-of-the-art generative AI solutions into your Knowledge Management culture, program, and systems.
This assessment comes in four parts:
1. Educate executives and stakeholders about the key benefits and limitations of ChatGPT types of applications.
2. Outline critical success factors for achieving business value from LLM-based technologies through information architecture.
3. Examine four critical areas of KM for AI readiness:
- Evaluation of knowledge quality, including structure, fitness to purpose, and metadata enrichment
- Establishment of baseline metrics to demonstrate measurable success
- Ongoing governance and decision-making
4. Summarize the current state in an executive working session designed to identify gasps, set realistic goals, and prioritize actions.
Why Is This Assessment Important?
- Organizations compete on their knowledge
- Generative AI performs most effectively on componentized knowledge
- A knowledge architecture powers semantic search
A RAG-based system leads to:
- Reduced customer support costs
- Improved knowledge access
- Increased operational efficiencies
What Do I Get?
- Business value statement
- Prioritized use cases
- Vision development working sessions
- Organizational, Data/Content, and Technical Readiness scorecards
- AI Proof-of-Value (PoV) plan