AI Knowledge Analyst I

Role Summary

The AI Knowledge Analyst is a member of the Customer Care and Managed Services team, responsible for ensuring the knowledge ecosystems that power GHXs operations and AI platforms are accurate, well-governed, and continuously improving.  This role works closely with leadership, SMEs, data scientists, and operational teams to identify content gaps, manage knowledge lifecycles, and translate business needs into structured, AI-ready information assets. The AI Knowledge Analyst is equally comfortable working through a detailed content audit and presenting a structured recommendation to leadership.  Strong organizational skills, clear communication, and a bias for action are required. This is a role for someone who treats knowledge gaps as solvable problems and can move from gap identification to resolution with minimal direction.

Core Focus Areas

Knowledge Governance & Lifecycle Management

Maintain, organize, and govern the knowledge assets that support Customer Care and Managed Services teams. This includes managing intake, triage, and routing of knowledge requests; driving SME review cycles; and ensuring content is accurate, current, and ready for both human use and AI ingestion.

AI Knowledge Readiness

Identify, structure, and groom content that feeds GHXs AI platform. Partner with AI and data teams to ensure knowledge assets are formatted, accurate, and optimized for ingestion. Monitor AI solution performance and drive content improvements that translate into measurable efficiency gains.

Roles & Responsibilities

Knowledge Management & Content Quality

• Manage the intake, triage, and routing of knowledge-related requests from operational teams.
• Maintain content lifecycle through SME review checkpoints — flagging material for update, review, or archival on a consistent cadence.
• Identify obsolete, duplicate, or conflicting content and drive resolution through appropriate stakeholders.
• Conduct knowledge audits and implement improvement cycles based on performance data and stakeholder feedback.
• Translate operational knowledge into structured, AI-ingestible formats ensuring accuracy, consistency, and taxonomy compliance.

AI Knowledge Readiness & Technology

• Structure and groom knowledge content for ingestion into GHXs AI platforms; ensure format, tagging, and taxonomy standards are met.
• Monitor AI platform performance related to knowledge quality; recommend and track content-driven improvements.
• Partner with data scientists and AI developers to understand ingestion requirements and close content gaps.
• Stay current on trends in AI knowledge management, large language model content requirements, and KM tooling.

Process Improvement & Analysis

• Analyze and document knowledge workflows, identifying gaps or structural issues that reduce content usability or AI accuracy.
• Interpret usage data, feedback trends, and engagement metrics to recommend improvement opportunities.
• Support implementation of governance standards, taxonomy structures, and documentation templates.
• Learn and apply Lean/Six Sigma and knowledge-centered service (KCS) frameworks where applicable.

Cross-Functional Collaboration & Stakeholder Engagement

• Partner with SMEs, operational leaders, and AI teams to promote adoption of AI-enabled knowledge systems.
• Provide end-user training and support on knowledge tools, systems, and updated content resources.
• Collect stakeholder requirements and develop content solutions that meet operational team needs.
• Present knowledge health findings and recommendations to leadership with clear next steps.

Required Skills

• Strong written and verbal communication skills; ability to tailor message by audience.
• Familiarity with knowledge management systems (Confluence/Atlassian, Salesforce Knowledge, ServiceNow, or equivalent).
• Analytical mindset with ability to interpret usage data and translate findings into action.
• Detail-oriented with ability to manage multiple knowledge domains and adjust priorities as needed.
• Proficiency in Microsoft 365 (Word, Excel, SharePoint, Forms); CRM familiarity a plus (Salesforce preferred).
• Self-directed learner who identifies gaps and takes initiative to close them.
• Understanding of how content structure and taxonomy affect AI/ML model performance preferred.

Education & Experience

• 2+ years of related experience in knowledge management, operations enablement, content governance, or business analysis.
• Demonstrated experience developing and maintaining content for both human consumption (training, SOPs) and machine ingestion (AI platforms, knowledge bases).
• Bachelors degree in Business, Information Management, Organizational Development, or related field; or equivalent combination of education and experience.
• Change management or KM certification (Prosci, KCS, ACMP) a plus.