Artificial intelligence (AI) is moving rapidly from the technology sector into healthcare. It is increasingly being explored for clinical decision support, health research, education, health-system management and other applications. The World Health Organization (WHO) emphasizes that AI has significant potential in health, but its adoption must be safe, ethical, equitable and appropriately governed. (World Health Organization)
For midwifery, this development raises an important question:
Could artificial intelligence change the way future midwives provide maternal and newborn care?
The answer is potentially yes—but not because technology can replace the midwife.
Instead, AI in midwifery may become a tool that supports skilled professionals in education, research, information analysis, monitoring and healthcare delivery while preserving human-centred care.
This article explores seven potential applications of artificial intelligence in midwifery, the opportunities and risks involved, and why future midwives need both clinical competence and digital literacy.
What Is AI in Healthcare?
Artificial intelligence refers broadly to computer systems capable of performing tasks that normally require aspects of human intelligence, such as recognizing patterns, processing information and generating outputs.
Several AI-related technologies are relevant to healthcare:
Artificial Intelligence
AI systems can analyze information and perform specific tasks based on algorithms and data.
Machine Learning
Machine learning allows systems to identify patterns in data and use those patterns to make predictions or classifications.
Generative AI
Generative AI can create new content, including text, images and other outputs. WHO's guidance notes that generative AI and large multimodal models are emerging technologies with potential applications in healthcare and research, while also presenting important risks that require governance. (World Health Organization)
Predictive Analytics
Predictive systems analyze data to estimate the likelihood of particular outcomes.
Clinical Decision Support
AI-enabled decision-support systems may help healthcare professionals interpret information or identify patterns. However, an AI output should not automatically be treated as a clinical decision.
For a midwifery student, the simplest way to think about AI is:
AI can process information and provide assistance, but the midwife remains responsible for professional clinical judgment within their scope of practice.
Why Does AI Matter in Midwifery?
Midwifery is fundamentally human-centred. WHO describes midwifery as skilled, knowledgeable and compassionate care across pregnancy, birth, postpartum and the early weeks of newborn life. WHO also emphasizes person-centred and respectful care. (World Health Organization)
At the same time, maternal and newborn healthcare involves large amounts of information, continuous monitoring, research, education and communication.
Digital technologies may therefore provide opportunities to support:
- Antenatal care
- Maternal-health education
- Risk assessment
- Clinical information management
- Midwifery education
- Research
- Remote healthcare services
- Health-system decision-making
However, technology should be introduced because it addresses a genuine problem—not simply because it is new.
7 Ways AI Could Transform Midwifery
1. AI for Antenatal Risk Assessment
One potential application of AI in maternal healthcare is supporting the analysis of antenatal information.
AI systems may be developed to identify patterns within large datasets and support risk stratification or early-warning processes.
Potential applications could include:
- Analysis of maternal health information
- Risk stratification
- Predictive modelling
- Early-warning systems
- Clinical decision support
For example, a validated system could potentially identify patterns associated with increased risk and bring relevant information to the attention of healthcare professionals.
However, this does not mean that an AI system should independently diagnose a pregnant woman.
AI-generated predictions require appropriate validation, clinical context and professional interpretation.
Key lesson: AI may assist with recognizing patterns, but qualified healthcare professionals must remain involved in clinical decision-making.
2. AI for Maternal and Fetal Monitoring
Maternal and fetal monitoring generates information that healthcare professionals must interpret carefully.
AI may potentially assist with analyzing patterns in monitoring data and identifying information that deserves professional attention.
Possible applications include:
- Maternal vital-sign monitoring
- Fetal monitoring
- Pattern recognition
- Early-warning systems
- Remote monitoring
The important distinction is between assistance and autonomy.
An AI system might identify a pattern, but the midwife or appropriate healthcare professional must consider the patient's complete clinical situation.
This is particularly important because pregnancy and childbirth are dynamic processes. Clinical decisions cannot safely depend on a single digital output.
3. AI for Newborn Care
The potential role of AI in newborn care is another emerging area.
AI-enabled systems could potentially support:
- Newborn monitoring
- Risk identification
- Health education
- Documentation
- Follow-up support
- Research
For example, AI could potentially help organize large amounts of newborn-health information or assist researchers in identifying patterns in datasets.
But emerging technology should not automatically be presented as established clinical practice.
Before an AI tool is used in real-world newborn care, questions about accuracy, safety, validation, privacy, equity and professional accountability must be addressed.
4. AI for Midwifery Education
This may be one of the most immediately useful areas for AI for midwifery students.
Students can potentially use responsible AI tools as supplementary learning resources for:
- Revision
- Case-based learning
- Clinical scenarios
- Question generation
- Research planning
- Concept explanations
- Literature exploration
- Study organization
For example, a student could ask an AI system to explain a difficult concept in simpler language and then verify the explanation using textbooks, clinical guidelines and peer-reviewed research.
However, students should not allow AI to replace actual learning.
A strong future midwife should understand the science behind a clinical decision—not simply know how to ask an AI system for an answer.
A simple rule for students:
Use AI to accelerate learning, not to avoid learning.
AI-generated information can also be incorrect, incomplete or misleading. Therefore, important academic and clinical information should be verified against reliable sources.
5. AI for Clinical Documentation and Workflow
Healthcare professionals spend significant time managing information and documentation.
AI may potentially support some administrative and information-management tasks, including:
- Summarizing information
- Organizing data
- Documentation assistance
- Administrative workflows
- Information retrieval
If such systems are used in healthcare, privacy and confidentiality become critical.
Maternal and newborn health information is sensitive. Healthcare organizations therefore need appropriate policies, security measures, professional oversight and data-governance processes.
AI should never become an excuse for careless handling of patient information.
6. AI for Maternal Health Research
The future of AI in midwifery research could also be significant.
Researchers may use AI-assisted tools to help with:
- Literature discovery
- Information organization
- Data organization
- Pattern identification
- Research-question development
- Evidence synthesis
- Data-analysis support
For healthcare students, this could make research skills increasingly important.
However, AI assistance is not the same as scientific judgment.
A researcher must still evaluate:
- Study quality
- Bias
- Methodology
- Statistical validity
- Relevance
- Limitations
- Ethical considerations
AI can help a researcher work with information, but it should not be treated as an unquestionable scientific authority.
7. AI and Maternal Healthcare in Africa
The African context deserves particular attention.
Digital health and AI could potentially support maternal healthcare through:
- Telehealth
- Health education
- Rural healthcare support
- Referral systems
- Digital health records
- Language-accessible information
- Workforce support
- Maternal-health research
WHO recognizes that AI has potential to address challenges such as workforce gaps and resource limitations, while also emphasizing the need for equitable and sustainable implementation. (World Health Organization)
However, Africa also faces challenges that cannot be ignored.
These include:
- Internet connectivity
- Digital literacy
- Infrastructure
- Cost
- Data quality
- Privacy
- Algorithmic bias
- Language diversity
- Local validation
- Health-system readiness
An AI system developed in one country should not automatically be assumed to work equally well in another.
The future of AI in African maternal healthcare must be locally relevant, evidence-based, equitable and appropriately validated.
Can AI Replace Midwives?
No—AI Should Support Midwives, Not Replace Them
This is perhaps the most important message of this article.
Midwifery is much more than processing information.
Midwives provide:
- Communication
- Compassion
- Emotional support
- Physical assessment
- Clinical judgment
- Advocacy
- Health education
- Respectful maternity care
- Shared decision-making
- Professional accountability
WHO emphasizes that quality maternal and newborn care should protect dignity, privacy and confidentiality, respect rights, support informed choice and provide continuous support. (World Health Organization)
These human dimensions cannot simply be reduced to an algorithm.
Therefore:
The future should not be AI versus the midwife. It should be the midwife empowered by responsible technology.
AI Ethics in Midwifery
Technology can create opportunities, but it also creates responsibilities.
Privacy and Confidentiality
Patient information must be protected. Healthcare professionals and students should never enter confidential patient information into inappropriate AI systems.
Algorithmic Bias
AI systems learn from data. If training data are incomplete or biased, an AI system may produce biased results.
This is particularly important when considering diverse populations and healthcare settings.
Accuracy
AI can generate incorrect information.
A confident-looking answer is not automatically a correct answer.
Accountability
Healthcare professionals cannot simply blame an AI system when something goes wrong.
Appropriate responsibility and professional oversight must remain central.
Informed Choice
Where AI is incorporated into healthcare processes, appropriate communication and consent arrangements should be considered.
Equity
AI should not create a situation where technologically advanced populations receive better care while underserved communities are left behind.
WHO emphasizes that ethics, human rights, accountability and equitable access should be central to AI in health. (World Health Organization)
The JOSIAS Framework for Responsible AI in Midwifery
To help students and healthcare professionals think critically about AI, I propose the JOSIAS Framework.
J — Justify the Problem
Before using AI, identify the actual healthcare, educational, research or maternal-health problem.
Do not start with the technology. Start with the problem.
O — Observe the Evidence
Look for credible scientific evidence before trusting or implementing an AI solution.
S — Study the Science
Understand how the technology works and, equally importantly, understand its limitations.
I — Innovate Solutions
Develop responsible, practical and context-appropriate solutions.
A — Apply in Practice
Use validated technologies appropriately in education, research and healthcare.
S — Support with Evidence
Continuously verify AI-generated information using credible scientific and clinical evidence.
JOSIAS in one sentence:
Justify → Observe → Study → Innovate → Apply → Support with Evidence.
This approach encourages future healthcare professionals to become critical users of AI rather than passive consumers of AI-generated information.
Potential Benefits vs Risks of AI in Midwifery
|
Potential Benefits |
Potential Risks |
|
Faster information analysis |
Incorrect outputs |
|
Personalized education |
Over-reliance |
|
Decision support |
Algorithmic bias |
|
Workflow support |
Privacy concerns |
|
Research assistance |
Academic misconduct |
|
Remote support |
Digital inequality |
|
Health education |
Misinformation |
The key point is balance.
AI's
potential benefits do not eliminate the need for human oversight.
How Midwifery Students Can Prepare for the AI Era
Future midwives should consider developing both clinical and digital competencies.
1. Develop basic AI literacy
Understand what AI can and cannot do.
2. Strengthen clinical knowledge
Technology cannot compensate for weak foundational knowledge.
3. Learn evidence-based practice
Know how to identify reliable healthcare evidence.
4. Develop research skills
Learn how to search, evaluate and interpret scientific literature.
5. Verify AI-generated information
Never automatically accept an AI answer as fact.
6. Protect patient confidentiality
Treat patient information with the same seriousness whether technology is involved or not.
7. Learn AI ethics
Understand privacy, bias, accountability and equity.
8. Maintain clinical reasoning
Develop your own ability to assess information and make appropriate professional judgments.
9. Develop digital-health skills
Learn how digital tools are changing healthcare delivery.
10. Use AI as a learning assistant
AI should complement your education—not replace textbooks, lecturers, clinical experience or critical thinking.
What Will the Future Midwife Look Like?
The future midwife may need more than traditional clinical competence.
A future-ready professional may need:
Clinical competence + Digital literacy + Research skills + Communication + Ethical reasoning + Human-centred care
This does not mean every midwife must become a computer scientist.
It means healthcare professionals should understand enough about digital technologies to use them safely, critically and responsibly.
The AI-ready midwife is therefore not someone who blindly trusts technology.
It is someone who knows:
- When technology can help
- When technology cannot help
- When evidence is insufficient
- When human judgment is essential
- How to protect patient information
- How to question AI-generated outputs
Conclusion: AI Should Strengthen Midwifery—Not Replace the Midwife
Artificial intelligence has the potential to influence maternal healthcare, newborn care, midwifery education, research and healthcare workflows.
But potential is not the same as proof.
The responsible future of AI in midwifery requires evidence, validation, ethics, privacy, equity and human oversight.
Midwives should not be replaced by technology. Instead, appropriately designed technology should help skilled healthcare professionals access information, learn, research, monitor patients and improve healthcare processes.
WHO's recent work on midwifery models of care continues to emphasize person-centred, evidence-based care and the important role of midwives in maternal and newborn health. (World Health Organization)
The central message is simple:
AI should strengthen midwifery—not replace the midwife.
And this leaves us with an important question:
If technology is becoming part of healthcare, are we preparing today's midwifery students to use it responsibly?
Frequently Asked Questions
What is AI in midwifery?
AI in midwifery refers to the use of artificial-intelligence technologies to potentially support areas such as education, research, information analysis, monitoring and healthcare workflows. It should complement professional midwifery judgment rather than replace it.
How can AI help midwives?
AI may assist with information analysis, education, research, documentation, monitoring and decision-support processes. Its usefulness depends on evidence, validation, appropriate implementation and professional oversight.
Can AI replace midwives?
No. Midwifery involves clinical assessment, communication, compassion, advocacy, ethical responsibility and human-centred care. AI can support these professionals but cannot substitute for the complete role of a qualified midwife.
How can AI support antenatal care?
Validated AI systems may potentially assist with risk assessment, data analysis, prediction and decision-support processes. Any clinical output must be interpreted within the patient's overall clinical context by appropriately qualified professionals.
What are the risks of AI in midwifery?
Important risks include inaccurate outputs, algorithmic bias, privacy breaches, over-reliance, inadequate validation, misinformation and unequal access.
How can midwifery students use AI responsibly?
Students can use AI as a supplementary learning tool while verifying important information against textbooks, clinical guidelines and credible scientific literature. They should also protect confidential patient information and maintain academic integrity.
What is the future of AI in midwifery?
AI may become increasingly integrated into healthcare education, research, monitoring and digital-health systems. The future will likely require midwives who combine clinical competence with digital literacy and ethical reasoning.
How can AI support maternal healthcare in Africa?
Potential applications include health education, telehealth, research, information management and support for underserved populations. Successful implementation requires attention to infrastructure, affordability, digital literacy, data quality, privacy, equity and local validation.
About the Author
N.
Josias
Undergraduate Student Midwife | Catholic University of Rwanda (CUR)
Healthcare Researcher | Digital Health & AI Learner
JO Research Writing Initiative
Evidence-Based
Writing • Meaningful Research • Real Impact
THE FUTURE MIDWIFE SERIES
This article is Part 1 of the Future Midwife Series.
Part 2 — Digital Health Skills Every Student Midwife Needs
Part 3 — Can AI Replace Midwives?
Part 4 — AI Ethics in Maternal Healthcare
Part 5 — Telemedicine and Maternal Health
Part 6 — The Future of Midwifery in Africa
Part 7 — How Student Midwives Can Use AI for Research
Part 8 — Building an AI-Ready Midwifery Workforce
Follow the JO Research Writing Initiative for evidence-based healthcare education, research, innovation, digital health and midwifery content.
This article is for educational purposes and does not replace professional clinical guidance or institutional protocols.
SEO Information
Primary keyword: AI in midwifery
Secondary keywords: artificial intelligence in midwifery; AI in maternal healthcare; AI in newborn care; AI for midwives
Suggested
URL slug:
ai-in-midwifery-maternal-newborn-care
Meta
description:
Discover how AI in midwifery could support maternal and newborn care,
education, research and digital health while keeping human-centred care at the
center.
Suggested
tags:
AI in Midwifery, Artificial Intelligence, Maternal Health, Newborn Care,
Digital Health, Midwifery Education, Midwifery Students, Healthcare AI, AI
Ethics, Maternal Healthcare, Healthcare Research, African Healthcare
Recommended authoritative sources
WHO — Artificial Intelligence for Health
WHO — Ethics and Governance of AI for Health
WHO — Maternal Health and Midwifery
WHO — Compendium on Respectful Maternal and Newborn Care
By
N. Josias | Undergraduate Student Midwife | Healthcare Researcher & Digital
Health Learner