AI Knowledge Analyst
Posted 24 Sep 2026
Advertised as “AI Knowledge Analyst I ”
BranchFactor Summary
The original posting with the fluff stripped out
- Level
- I
- Expected experience
- 2+ yrs
- Management level
- Individual contributor
No salary listed for this role.
Field of studyBusiness, Information Management, Organizational Development (or related)
Study levelBachelor's
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 GHX's 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 GHX's 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 GHX's AI platforms; ensure format, tagging, and taxonomy standards are met.
- Monitor AI platform performance related to knowledge quality; recommend and track content-driven improvements.