Checklist Report - Utilizing Agentic AI to Increase Productivity

Superior AI Relies on AI-Ready Knowledge and Data

AI is entering our lives at astonishing speed. For KM professionals, it has many ramifications, not least of which is its ability to spread knowledge widely throughout an organization and beyond. The use cases are varied, with possibilities for better internal productivity and more effective external communication. Customer service agents can be spared dealing with mundane requests, letting AI handle them. Administrative details, such as scheduling, calendaring, and routine email responses, can be delegated to AI. This frees the human employees for more complex tasks. Externally, customers can easily find what they are looking for on company websites because AI has created appropriate metadata and chatbots interpret the intent of an inquiry. Sounds like a win-win for increasing access to knowledge, streamlining information relevancy, and empowering knowledge workers...

Knowledge and Data First: Building Superior AI

AI initiatives succeed or fail on the knowledge beneath them. To make copilots, agents, search, automation, and decision support accurate and trustworthy, organizations must prepare knowledge around three foundations: quality, structure, and context.

The conversation about enterprise AI often begins with models, platforms, and use cases. Yet every capability depends on a less visible asset: the knowledge the system must use. Policies, procedures, product information, technical documentation, contracts, compliance requirements, process maps, and business rules describe how the organization works. If that knowledge is unreliable or difficult to interpret, even an advanced model will produce inconsistent results.