How an Integrated Health System Built an AI Workforce Case the CHRO Could Take to the Board

A Connecticut-based integrated health system scored automation and augmentation feasibility across 47 shared services roles. Etter modeled the financial impact against its own headcount data and put a function-level AI workforce case in front of senior leadership in eight weeks.

~48,000

Employees

$7B+

Revenue

Integrated Healthcare

Industry

Connecticut, USA

Headquarters

About the organization

The ccustomer is one of the largest and most comprehensive integrated health systems in the United States, running a fully connected network of hospitals, specialty practices, and shared services functions. Its 48,000+ employees span clinical and administrative workacross Revenue Cycle, Finance, Supply Chain, and HR. As AI adoption accelerated across healthcare, leadership needed a rigorous, data‑backed view of howautomation and augmentation would reshape shared services, and what that meant for talent strategy, role design, and long‑term capability architecture.

The Core Challenges

No Structured View of Where AI Actually  Lands
Leadership needed to know which shared services roles and  tasks were most exposed to AI‑driven change, at a level of detail that would  let them prioritize transformation spend.
Job Architecture Scattered Across Systems
Headcount and job architecture data lived across multiple  teams and systems. Enterprise workforce planning needed one unified taxonomy  to anchor decisions to.
Insights That Land With HR and the  Business
Senior HR and business leaders wanted intuitive, simulation‑driven outputs that worked across very different levels of  technical fluency, not analysis pitched at specialists.
Difficulty Isolating Net-New AI Opportunity
UiPath and Power BI were already delivering incremental  gains. The investment case depended on isolating genuinely net‑new AI  opportunity from what was already within reach.

47

Roles Assessed

4

Functions Covered

8

Weeks to 1st Stakeholder Meeting

90%+

Automation Feasibility (Top Roles)

3x

Productivity Uplift (Financial Analyst)

The Solution

The organization partnered with Draup to deploy its Etter workforce intelligence platform across 47 shared services roles, delivering structured AI impact assessments and executive-ready simulation outputs in 8 weeks.

01
AI Impact Assessment
Each of the 47 roles was scored on automation and augmentation potential across all task workloads, providing a structured, comparable view of AI exposure across Revenue Cycle, Finance, Supply Chain, and HR.
02
Financial Simulator
Draup modeled the capacity-freed and financial impact of AI adoption at the function level, using the organization's actual headcount data to translate transformation potential into concrete business terms.
03
Tech Stack Prioritization
Role-specific technology recommendations were curated with estimated hours saved, distinguishing existing tool capabilities from net-new AI additions  addressing a core requirement from HR leadership.
04
Workforce Twin & Role Adjacency
A workforce twin mirrored the org's taxonomy to simulate real-time transformation scenarios. Role adjacency mapping outlined no-layoff redeployment pathways as automation freed capacity
6,100+​
Locations
4M+​
Career Paths​
1.7M+​
Peer Group Companies​
28K+
Skills
3,500+​
Roles
1B+​
Professionals​
55K+​
Universities​
1B+​
Job Descriptions​
200K+​
Courses​
180K+​
Technology Solutions​
1.6M+​
Account Priorities​
Labor Market Data Contextualized with Business Intelligence for Every Decision

Analyzing 1B+ data points
daily from 100K+ sources

6,100+​
Locations
4M+​
Career Paths​
1.7M+​
Peer Group Companies​
28K+
Skills
3,500+​
Roles
1B+​
Professionals​
55K+​
Universities​
1B+​
Job Descriptions​
200K+​
Courses​
180K+​
Technology Solutions​
1.6M+​
Account Priorities​