U.S. AI In Nurse Scheduling Software Market Trends Analysis Report 2025-2033: Key Opportunities In Automating Scheduling, Optimizing Staff Allocation, And Enhancing Patient Care

(MENAFN- GlobeNewsWire - Nasdaq) The U.S. AI in nurse scheduling software market is poised for growth, driven by rising demand for operational efficiency and a nursing shortage.. AI advancements offer solutions to reduce costs and administrative burdens.

Dublin, Jan. 15, 2026 (GLOBE NEWSWIRE) -- The "U.S. AI in Nurse Scheduling Software Market Size, Share & Trends Analysis Report by Deployment Mode, Application, End-use with Growth Forecasts, 2025-2033" report has been added to ResearchAndMarkets's offering.
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.
Key Attributes:

Report Attribute	Details
No. of Pages	100
Forecast Period	2024 - 2033
Estimated Market Value (USD) in 2024	$55.58 Million
Forecasted Market Value (USD) by 2033	$516.41 Million
Compound Annual Growth Rate	28.4%
Regions Covered	United States

Key Topics Covered:
Chapter 1. Methodology and Scope
1.1. Market Segmentation & Scope
1.2. Market Definitions
1.3. Information analysis
1.4. Data validation & publishing
1.5. Information Procurement
1.6. Information or Data Analysis
1.7. Market Formulation & Validation
1.8. Market Model
1.9. Total Market: CAGR Calculation
1.10. Objectives
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
3.4.2. PESTEL Analysis
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
4.5. On-premises
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
5.5. Demand Forecasting & Staffing Prediction
5.6. Leave & Absence Management
5.7. Analytics & Reporting
5.8. Others
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
6.5. Ambulatory Surgical Centers (ASCs)
6.6. Long-Term Care Facilities
6.7. Home Healthcare Agencies
6.8. Clinics & Specialty Centers
6.9. Others
Chapter 7. Competitive Landscape
7.1. Company/Competition Categorization
7.2. Strategy Mapping
7.3. Company Market Position Analysis, 2024
7.4. Company Profiles
7.4.1. Company overview
7.4.2. Financial performance
7.4.3. Product benchmarking
7.4.4. Strategic initiatives

• QGenda, LLC
• In-House Health, Inc.
• symplr
• Connecteam
• Deputy
• MakeShift
• Medecipher Solutions
• ShiftMed

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