Healthcare AdministratorsvsMedical Coders and Health Records Specialists

until most of the change has landed

High adoption

until most of the change has landed

Very High adoption

AI is automating scheduling, revenue cycle and reporting in health systems, moving administrators towards AI governance and change leadership.

Autonomous coding now assigns codes from clinical notes for a growing share of encounters, leaving specialists to audit, resolve exceptions and manage records.

1. Operational AI for capacity and staffing
2. Revenue cycle automation
3. Office copilots for reporting and communication
4. Procurement of clinical AI
5. High sector adoption
6. Low observed usage by managers themselves

1. Autonomous coding engines
2. Computer-assisted coding and encoder platforms
3. EHR-embedded AI
4. Ambient clinical documentation
5. Revenue-cycle cost pressure
6. Payer automation and audit

1. AI governance and risk management
2. Change leadership
3. Data and operational analytics
4. Procurement and vendor management
5. Regulatory and compliance knowledge
6. Financial stewardship

1. Coding audit and compliance
2. Complex inpatient and specialty coding
3. Clinical documentation integrity
4. Health information governance
5. Payer rules and denial management
6. Data literacy and reporting

1. Epic
2. Qventus
3. Waystar
4. Workday
5. Microsoft 365 Copilot

1. Solventum 360 Encompass (formerly 3M)
2. Nym
3. Fathom
4. CodaMetrix