US Artificial Intelligence (AI) in Remote Postnatal Care Market - Forecasts From 2025 To 2030

Description

US AI in Remote Postnatal Care Market Size:

US Artificial Intelligence (AI) in Remote Postnatal Care Market is anticipated to expand at a high CAGR over the forecast period.

To learn more about this report, request a free sample copy

The United States grapples with a maternal health crisis where postpartum complications form one of the major factors leading to pregnancy-related deaths. Remote AI applications emerge as a targeted response, leveraging algorithms to analyze vital signs and behavioral data from wearables and apps. These tools facilitate continuous monitoring without requiring physical presence, directly countering barriers like geographic isolation and provider shortages that affect rural areas mainly.

________________________________________________________________

US AI in Remote Postnatal Care Market Analysis:

Growth Drivers

Workforce shortages in maternal care, coupled with the lack of basic infrastructure required to meet the parental emergency, are propelling the demand for AI-driven remote postnatal solutions, as rural and underserved areas lose obstetric providers at rates exceeding annual. According to the "2024 Nowhere to Go: Maternity Care Deserts Across US" report, nearly 35% of the US counties lack basic obstetric services, care, and birth centers. AI-based tools process wearable data to detect anomalies like blood pressure spikes, enabling proactive triage that reduces emergency visits by alerting providers remotely. This shift creates direct uptake, with AI filling the void left by the decline in ob-gyns.

Technological maturation in predictive analytics underpins sustained growth. Studies reveal that machine learning models, trained on de-identified electronic health records, forecast complications with accuracy for postpartum hemorrhage. This precision draws end-users like maternity centers, where integration with existing EHR systems streamlines workflows and cuts manual screening time. Pandemic-era telehealth normalization, followed by the establishment of a national strategic police to bolster the implementation and adoption of AI, is further impacting the market expansion.

Challenges and Opportunities

Data biases embedded in AI algorithms constrain demand by eroding trust among diverse user groups, particularly Black and Indigenous women who bear higher postpartum mortality risks. Providers hesitate to scale deployment, fearing liability and inequitable outcomes, which dampens adoption in safety-net clinics serving the majority of low-income mothers. This headwind limits market penetration, as unaddressed disparities prompt regulatory scrutiny and slow payer approvals.

Ethical dilemmas around privacy further impede uptake, and in postnatal contexts, where emotional vulnerability peaks, these issues deter engagement, reducing the effective addressable market by sidelining tech-averse segments. Resource-limited end-users, including small maternity centers, face integration hurdles with legacy systems, exacerbating a digital divide that confines advanced features to urban hospitals.

Conversely, equity-focused AI advancements unlock substantial opportunities. Federated learning techniques, which train models across decentralized datasets without centralizing sensitive information, mitigate bias by incorporating diverse inputs from tribal health programs. Hence, this approach expands access for remote users, potentially capturing a large number of underserved women, thereby elevating platform utilization.

Supply Chain Analysis

The supply chain for U.S. remote postnatal AI centers on digital infrastructure, with cloud computing as the backbone for data processing and model deployment. These facilities handle the ingestion of vital signs and behavioral data from user apps, ensuring low-latency analytics essential for real-time alerts. Likewise, Dependencies on semiconductor components for edge devices, such as wearables interfacing with AI platforms, introduce vulnerabilities.

And the ongoing tariff war has further impacted semiconductor supply from major economies, namely Taiwan and China will further ripple the hardware dependencies. Furthermore, the logistical complexities arise from data sovereignty requirements under HIPAA, mandating U.S.-based storage to prevent cross-border flows. This confines operations to domestic providers, inflating costs compared to global alternatives.

Government Regulations

________________________________________________________________

US AI in Remote Postnatal Care Market Segment Analysis:

By Technology: Machine Learning

Machine learning dominates the technology segment by powering predictive models that directly amplify demand in remote postnatal care. The growing emphasis on improving the precision of forecasting the overall risk associated has overburdened providers, who integrate machine learning into apps for automated scoring of vital trends from home devices, reducing manual reviews and enabling coverage for millions of annual high-risk cases. Likewise, demand escalates amid workforce constraints, especially in rural settings. Hence, end-users favor ML for its adaptability, retraining on local datasets to personalize alerts, which further sustains high engagement rates in postpartum cohorts.

By End-User: Hospitals

Hospitals anchor end-user demand for remote postnatal AI, driven by mandates to curb high readmission costs. Furthermore, the ongoing technological investments in enhancing healthcare infrastructure have accelerated the adoption of modern innovations in various healthcare practices. And this integration with next-generation concepts aligns with value-based care models, where hospitals deploy AI to monitor a large number of patients remotely. Additionally, the regulatory pressures followed by staff gapping further stimulate the AI-adoption.

________________________________________________________________

US AI in Remote Postnatal Care Market Competitive Environment and Analysis:

The competitive landscape features a mix of specialized digital health firms and diversified players, with ten key entities vying for share through app-based platforms and predictive tools.

Maven Clinic Co.

Maven Clinic Co. positions itself as a full-spectrum provider, integrating AI for personalized postpartum pathways across major US counties via employer partnerships. Its platform uses machine learning (ML) to triage mental health risks, serving millions of users and achieving a high retention rate through virtual coaching.

Ovia Health

Ovia Health differentiates via evidence-based behavioral frameworks, supporting maternal journeys with AI-driven postpartum experiences. The constant updation in its digital solutions that meet the requirements of women during their pregnancy stage has established Ovia amongst the reliable market players.

Recent Market Developments

• September 2024: Ovia Health launched its Comprehensive 12-Month Postpartum Experience within the Ovia app, integrating AI for personalized recovery tracking and behavioral nudges to address care gaps in extended Medicaid coverage periods.
• April 2024: Maven Clinic expanded its Fertility & Family Building solution with AI-enhanced natural conception modules, incorporating predictive analytics for ovulation and risk assessment to support preconception-to-postpartum continuity.

________________________________________________________________

US AI in Remote Postnatal Care Market Scope:

US Artificial Intelligence (AI) in Remote Postnatal Care Market Segmentation:

• By Technology
  • Machine Learning (ML)
  • Natural Language Processing (NLP)
  • Computer Vision
  • Others
• By Application
  • Maternal Health Monitoring
  • New-Born Health Monitoring
  • Postpartum Care
  • Others
• By End-User
  • Hospitals
  • Maternity Clinics & Centers
  • Others

Table Of Contents

1. EXECUTIVE SUMMARY

2. MARKET SNAPSHOT

2.1. Market Overview

2.2. Market Definition

2.3. Scope of the Study

2.4. Market Segmentation

3. BUSINESS LANDSCAPE

3.1. Market Drivers

3.2. Market Restraints

3.3. Market Opportunities

3.4. Porter's Five Forces Analysis

3.5. Industry Value Chain Analysis

3.6. Policies and Regulations

3.7. Strategic Recommendations

4. TECHNOLOGICAL OUTLOOK

5. US ARTIFICIAL INTELLIGENCE (AI) IN REMOTE POSTNATAL CARE MARKET BY TECHNOLOGY

5.1. Introduction

5.2. Machine Learning (ML)

5.3. Natural Language Processing (NLP)

5.4. Computer Vision

5.5. Others

6. US ARTIFICIAL INTELLIGENCE (AI) IN REMOTE POSTNATAL CARE MARKET BY APPLICATION

6.1. Introduction

6.2. Maternal Health Monitoring

6.3. New-Born Health Monitoring

6.4. Postpartum Care

6.5. Others

7. US ARTIFICIAL INTELLIGENCE (AI) IN REMOTE POSTNATAL CARE MARKET BY END-USER

7.1. Introduction

7.2. Hospitals

7.3. Maternity Clinics & Centers

7.4. Others

8. COMPETITIVE ENVIRONMENT AND ANALYSIS

8.1. Major Players and Strategy Analysis

8.2. Market Share Analysis

8.3. Mergers, Acquisitions, Agreements, and Collaborations

8.4. Competitive Dashboard

9. COMPANY PROFILES

9.1. Babyscripts, Inc.

9.2. Bloomlife, Inc

9.3. Wildflower Health

9.4. Ovia Health

9.5. Maven Clinic Co.

9.6. Nurture

9.7. Delfina

9.8. Marani Health, Inc.

9.9. NUVO, Inc.

9.10. HARMAN International (Samsung Electronics)

10. APPENDIX

10.1. Currency

10.2. Assumptions

10.3. Base and Forecast Years Timeline

10.4. Key benefits for the stakeholders

10.5. Research Methodology

10.6. Abbreviations

LIST OF FIGURES

LIST OF TABLES

Companies Profiled

Babyscripts, Inc.

Bloomlife, Inc

Wildflower Health

Ovia Health

Maven Clinic Co.

Nurture

Delfina

Marani Health, Inc.

NUVO, Inc.

HARMAN International (Samsung Electronics)

Related Reports