Blog Post

Artificial intelligence (AI) is reshaping healthcare around the globe—and when firms like KPMG publish data-based reports, we all stand up and take notice. Their latest Intelligent Healthcare study reveals that 85% of healthcare organizations are developing AI solutions in-house, with generative AI (GenAI) being the most widely adopted technology. In the Global South, especially Sub‑Saharan Africa, these findings signal more than progress—they point to transformative opportunities.

Dominant Trends in Healthcare AI Adoption

The KPMG report highlights a green wave of internal innovation: 85% of healthcare providers across the US, UK, Japan, Germany, and more are launching GenAI pilots and scaling AI across clinical workflows [medicaldevice-network.com]. This growth is echoed by GlobalData’s projection that the healthcare AI market will expand to ~$19 billion by 2027.

👉 Why it matters: Developing solutions internally allows institutions to align AI with local health challenges, data governance, and cultural contexts. In regions like Sub‑Saharan Africa, this means deploying AI tailored to endemic diseases, clinic workflows, and infrastructure constraints—far beyond generic off-the-shelf platforms.

Evolutionary vs. Revolutionary Impact

KPMG terms AI’s role in healthcare evolutionary, not revolutionary, suggesting steady, sustainable transformation rather than flashy disruption. This reframing sets realistic expectations:

• Administrative automation: AI tools are reducing clerical workload, freeing caregivers to focus on patient care.
  
  
• Diagnostics and treatment optimization: AI algorithms quickly analyze X‑rays, lab results, and patient histories to support clinical decisions.
  
  

Local context matters. A tool built in South Africa to aid rural clinics, for instance, might focus on antenatal care data gaps—different from solutions built for wealthy urban hospitals in other continents.

The Business & ROI Case

In their 2025 GenAI Value Report, KPMG reports that 65% of U.S. healthcare companies believe AI is already transforming operations. Furthermore, 92% of executives expect major competitive gains, and 68% forecast moderate to high returns from AI investments.

For healthcare providers in the Global South, limited budgets and tight margins make these ROI figures compelling. AI can streamline logistics (e.g., medicine distribution), optimize staff allocations, and predict disease outbreaks—often at lower cost than human-driven systems.

The Challenge of “Trusted AI”

KPMG emphasizes the need for trustworthy, ethics-first AI. Their report outlines frameworks and governance models that healthcare leaders should implement to mitigate bias, privacy breaches, and unintended risks .

In regions with diverse populations and limited regulatory infrastructure, these principles are essential. Protocols like explainability, equity, and privacy-first AI must be ingrained—from model training to real-world deployment.

Impact on Accessibility & Care for Vulnerable Populations

According to the AI in Healthcare Wikipedia overview, AI is helping to expand care to developing nations by enabling remote diagnosis, telemedicine, and mobile health—filling critical provider gaps.

Studies on AI-enabled remote patient monitoring show how generative AI and sensors can detect early deterioration and manage chronic conditions effectively. This is a game-changer for rural clinics without 24/7 doctors.

A Roadmap for the Global South

To leverage these trends, healthcare leaders in Sub‑Saharan Africa and similar regions can:

1. Understand internal capabilities: Begin AI projects within existing infrastructure—EHR integration, local language support, etc.
   
   
2. Adopt phased value models: Use KPMG’s “Enable–Embed–Evolve” maturity framework to roll out AI, ensuring scalability without overwhelming resources.
   
   
3. Embed trust and ethics: Governance frameworks should accompany AI from design to usage, especially in multi-ethnic societies.
   
   
4. Prioritize tele- and remote-care: AI solutions should tackle use cases like remote diagnostics, supply-chain optimization, and population health analytics—high-impact and cost-effective.
   
   

Conclusion

The KPMG report reinforces a powerful reality: artificial intelligence is no longer a distant promise—it is an active, strategic force in shaping global healthcare. With 85% of healthcare organizations already developing AI in-house, the momentum is undeniable.

For stakeholders across the Global South—governments, healthcare providers, NGOs, and innovators—this presents a pivotal opportunity. By investing in trusted, scalable, and contextually relevant AI solutions, these regions can not only bridge longstanding gaps in care delivery but also lead in shaping a more equitable digital health future.