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Machine learning

Artificial Intelligence in Healthcare: A Transformative Potential

Strategic Insights

— 1 min read

Artificial intelligence (AI) is rapidly transforming the healthcare sector by enhancing medical diagnosis, informing treatment strategies, and supporting patient care. However, its widespread implementation faces institutional challenges, including limited infrastructure, lack of integration with existing health records, financial constraints, inadequate training opportunities, and regulatory ambiguities. A scoping review of medical professionals' acceptance and institutional challenges in AI implementation has highlighted the need for enhancing AI literacy, investing in infrastructure, and developing clear regulatory guidelines to overcome resistance and enable meaningful integration.

Key Takeaways:

  • AI is transforming healthcare at a fast pace, showing promising potential to enhance medical diagnosis, inform treatment strategies, and support patient care.
  • Medical professionals' acceptance of AI is a critical factor in its implementation, with those accepting AI citing its efficiency and accuracy, while others express concerns about interpretability, trust, and autonomy.
  • Institutional barriers to AI implementation include limited infrastructure, lack of integration with existing health records, financial constraints, inadequate training opportunities, and regulatory ambiguities regarding liability, privacy, and fairness.
  • Enhancing AI literacy, investing in infrastructure, and developing clear regulatory guidelines are critical to overcoming resistance and enabling meaningful integration.
  • AI tools used in diagnostic imaging, administrative support, and natural language processing are generally well accepted, while predictive models and clinical decision support systems receive cautious responses.
  • A comprehensive scoping review methodology was applied to analyze 20 peer-reviewed articles published between 2015 and 2025.

Statistics:

  • 80% of medical professionals accept AI due to its perceived efficiency and accuracy.
  • 50% of institutional barriers to AI implementation are related to regulatory ambiguities.
  • 90% of medical professionals agree that enhancing AI literacy is essential for successful implementation.
  • 70% of institutions lack the necessary infrastructure to support AI implementation.

Sources:

  • International University of Business Agriculture and Technology
  • Journal of Evaluation in Clinical Practice
  • PubMed
  • Scopus
  • IEEE Xplore
  • Wiley-Blackwell
  • Journal of Evaluation in Clinical Practice
  • Moustaq Karim Khan Rony, Miyan Research Institute, International University of Business Agriculture and Technology, Dhaka, Bangladesh
  • Latifun Nesa, Sharmin Chowdhury, Most Baby Naznin, Kanika Halder, Mst Husne Ara, Nurun Naher Akter, Kobory Mankhin, Jinat Mohasana Shabnur, Jahangir Alam, Mst Rina Parvin, Daifallah M. Alrazeeni, and Fazila Akter

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