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U.S. AI In Nurse Scheduling Software Market Size, Share & Trends Analysis Report By Deployment Mode (Cloud-based, On-premises), By Application (Shift Scheduling & Optimization, Demand Forecasting & Staffing Prediction), By End-use (Hospitals, Ambulatory S

Publisher Grand View Research
Published Nov 17, 2025
Length 100 Pages
SKU # GV20649612

Description

Market Size & Trends

The U.S. AI in nurse scheduling software market size was estimated at USD 55.58 million in 2024 and is projected to reach USD 516.41 million by 2033, growing at a CAGR of 28.40% from 2025 to 2033. The rising demand for operational efficiency and the growing shortage of nursing professionals are significant factors contributing to market growth. In addition, advancements in AI and machine learning are other factors fueling market growth.

Rising demand for operational efficiency drives the U.S. AI nurse scheduling software industry. Hospitals and clinics face complex staffing demands, driven by increasing patient influxes and fluctuating care needs. AI-powered scheduling solutions automate routine tasks, enhancing accuracy and enabling real-time adjustments. These systems optimize nurse allocation, reduce administrative burdens, and enhance shift coverage, leading to improved patient outcomes and reduced nurse fatigue.

AI-based nurse scheduling solutions automate manual scheduling, allowing managers to focus on patient care. Advanced algorithms adjust staffing in real-time based on census trends, patient acuity, and skill mix, thereby reducing overtime and agency costs. For instance, Epic Systems is developing AI-powered clinical documentation tools, expected to launch in early 2026, aimed at reducing the time nurses and clinicians spend on documentation and administrative tasks. The native AI charting tool will automatically draft parts of patient records using Microsoft’s Dragon Ambient AI integrated within Epic’s apps.

Moreover, the growing shortage of nursing professionals across the U.S. presents a significant challenge for healthcare systems, driving the adoption of AI-driven nurse scheduling software. Hospitals and long-term care facilities are increasingly struggling to maintain adequate staff-to-patient ratios while complying with labor regulations and ensuring high-quality care. For instance, according to the data published by the American Association of Colleges of Nursing (AACN), federal authorities project a shortage of 78,610 full-time registered nurses (RNs) in 2025 and 63,720 in 2030.

U.S. AI In Nurse Scheduling Software Market Report Segmentation

This report forecasts revenue growth at country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2021 to 2033. For this study, Grand View Research has segmented the U.S. AI in nurse scheduling software market report based on deployment mode, application, and end-use:
  • Deployment Mode Outlook (Revenue, USD Million, 2021 - 2033)
  • Cloud-Based
  • On-Premises
  • Application Outlook (Revenue, USD Million, 2021 - 2033)
  • Shift Scheduling & Optimization
  • Demand Forecasting & Staffing Prediction
  • Leave & Absence Management
  • Analytics & Reporting
  • Others
  • End-use Outlook (Revenue, USD Million, 2021 - 2033)
  • Hospitals
  • Ambulatory Surgical Centers (ASCs)
  • Long-Term Care Facilities
  • Home Healthcare Agencies
  • Clinics & Specialty Centers
  • Others (Rehabilitation & Mental Health Centers)
Please note The report will be delivered in 2-3 business days upon order notification.

Table of Contents

100 Pages
Chapter 1. Methodology and Scope
1.1. Market Segmentation & Scope
1.2. Market Definitions
1.2.1. Deployment Mode Segment
1.2.2. Application Segment
1.2.3. End Use
1.3. Information analysis
1.3.1. Market formulation & data visualization
1.4. Data validation & publishing
1.5. Information Procurement
1.5.1. Primary Research
1.6. Information or Data Analysis
1.7. Market Formulation & Validation
1.8. Market Model
1.9. Total Market: CAGR Calculation
1.10. Objectives
1.10.1. Objective 1
1.10.2. Objective 2
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Snapshot
2.3. Competitive Insights Landscape
Chapter 3. U.S. AI in Nurse Scheduling Software Market Variables, Trends & Scope
3.1. Market Lineage Outlook
3.1.1. Parent market outlook
3.1.2. Related/ancillary market outlook.
3.2. Market Dynamics
3.2.1. Market driver analysis
3.2.2. Market restraint analysis
3.2.3. Market opportunity analysis
3.2.4. Market challenges analysis
3.3. Case Studies
3.4. U.S. AI in Nurse Scheduling Software Market Analysis Tools
3.4.1. Industry Analysis - Porter’s
3.4.1.1. Supplier power
3.4.1.2. Buyer power
3.4.1.3. Substitution threat
3.4.1.4. Threat of new entrant
3.4.1.5. Competitive rivalry
3.4.2. PESTEL Analysis
3.4.2.1. Political landscape
3.4.2.2. Technological landscape
3.4.2.3. Economic landscape
3.4.2.4. Environmental Landscape
3.4.2.5. Legal Landscape
3.4.2.6. Social Landscape
Chapter 4. U.S. AI in Nurse Scheduling Software Market: Deployment Mode Estimates & Trend Analysis
4.1. Segment Dashboard
4.2. U.S. AI in Nurse Scheduling Software Market Deployment Mode Movement Analysis
4.3. U.S. AI in Nurse Scheduling Software Market Size & Trend Analysis, by Deployment Mode, 2021 to 2033 (USD Million)
4.4. Cloud-based
4.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
4.5. On-premises
4.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
Chapter 5. U.S. AI in Nurse Scheduling Software Market: Application Estimates & Trend Analysis
5.1. Segment Dashboard
5.2. U.S. AI in Nurse Scheduling Software Market Application Movement Analysis
5.3. U.S. AI in Nurse Scheduling Software Market Size & Trend Analysis, by Application, 2021 to 2033 (USD Million)
5.4. Shift Scheduling & Optimization
5.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
5.5. Demand Forecasting & Staffing Prediction
5.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
5.6. Leave & Absence Management
5.6.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
5.7. Analytics & Reporting
5.7.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
5.8. Others
5.8.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
Chapter 6. U.S. AI in Nurse Scheduling Software Market: End Use Estimates & Trend Analysis
6.1. Segment Dashboard
6.2. U.S. AI in Nurse Scheduling Software Market End Use Movement Analysis
6.3. U.S. AI in Nurse Scheduling Software Market Size & Trend Analysis, by End Use, 2021 to 2033 (USD Million)
6.4. Hospitals
6.4.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
6.5. Ambulatory Surgical Centers (ASCs)
6.5.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
6.6. Long-Term Care Facilities
6.6.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
6.7. Home Healthcare Agencies
6.7.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
6.8. Clinics & Specialty Centers
6.8.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
6.9. Others
6.9.1. Market estimates and forecasts, 2021 to 2033 (USD Million)
Chapter 7. Competitive Landscape
7.1. Company/Competition Categorization
7.2. Strategy Mapping
7.3. Company Market Position Analysis, 2024
7.4. Company Profiles/Listing
7.4.1. QGenda, LLC
7.4.1.1. Company overview
7.4.1.2. Financial performance
7.4.1.3. Product benchmarking
7.4.1.4. Strategic initiatives
7.4.2. In-House Health, Inc.
7.4.2.1. Company overview
7.4.2.2. Financial performance
7.4.2.3. Product benchmarking
7.4.2.4. Strategic initiatives
7.4.3. symplr
7.4.3.1. Company overview
7.4.3.2. Financial performance
7.4.3.3. Product benchmarking
7.4.3.4. Strategic initiatives
7.4.4. Connecteam
7.4.4.1. Company overview
7.4.4.2. Financial performance
7.4.4.3. Product benchmarking
7.4.4.4. Strategic initiatives
7.4.5. Deputy
7.4.5.1. Company overview
7.4.5.2. Financial performance
7.4.5.3. Product benchmarking
7.4.5.4. Strategic initiatives
7.4.6. MakeShift
7.4.6.1. Company overview
7.4.6.2. Financial performance
7.4.6.3. Product benchmarking
7.4.6.4. Strategic initiatives
7.4.7. Medecipher Solutions
7.4.7.1. Company overview
7.4.7.2. Financial performance
7.4.7.3. Product benchmarking
7.4.7.4. Strategic initiatives
7.4.8. ShiftMed
7.4.8.1. Company overview
7.4.8.2. Financial performance
7.4.8.3. Product benchmarking
7.4.8.4. Strategic initiatives

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