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Preparing for Agentic AI: KM Playbook

Mining Data and Knowledge for AI Success

The ever-accelerating pace of AI model developments is enough to make even the best and most tech-savvy KM practitioners dizzy. Just when we think we have a handle on how to incorporate AI technologies into our organizations and daily workflows, changes appear that challenge our high level strategic thinking and cause us to alter not only how we implement new technologies but also how we regard the possibilities of AI over and above those daily workflows…

Stability: An Overlooked, But Critical Element for AI Success

Scaling an AI project requires strong and stable data infrastructure to provide the foundation for your projects. Typically, this centers on three areas:

• User Focus—Aligning the AI products, data, and goals with the needs/goals of end users.

• Comprehensive Models—Creating the taxonomies, ontologies, schemas, etc. that describe your organization’s domain consistently across your systems, business units and interfaces.

• Organizational Alignment—Ensuring that strategy, data, technology, KPIs, and resourcing are all working together…