The long-term impact of AI integration on economic sustainability in healthcare: a cost-saving perspective
Farid, Huma (2025-11-18)
The long-term impact of AI integration on economic sustainability in healthcare: a cost-saving perspective
(18.11.2025)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
avoin
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe20251211117724
https://urn.fi/URN:NBN:fi-fe20251211117724
Tiivistelmä
A transformative force that is increasingly being recognised as a key driver in healthcare is artificial intelligence (AI). It has the potential to strengthen economic sustainability in healthcare by improving efficiency, supporting decision-making both in clinical and administrative settings. Due to the growing demand for access to quality care and escalating costs of medical facilities, healthcare systems are under enormous pressure, demanding more effective solutions. This study investigates how AI integration in healthcare can contribute to economic sustainability in healthcare by generating cost savings in the long term.
This study is guided by a theoretical framework drawn from literature on healthcare management and AI adoption. Within this framework, cost savings are positioned as the central outcome of AI integration emerging from different pathways, including administrative efficiency, early disease detection and prevention, reduced admissions and readmissions, resource optimisation, workforce planning, clinical efficiency, easy access to care, and data-driven savings. In addition to immediate efficiencies, the framework highlights second- and third-order benefits achieved through process adaptation, continuous monitoring, and scalable integration, framing economic sustainability as an ongoing process rather than a fixed goal.
This research makes both theoretical and practical contributions by using an exploratory qualitative approach. The findings show that AI has the potential to create measurable efficiencies, reduce costs, and support healthcare delivery. This study concludes that AI should not be considered merely a technological upgrade, but rather as a strategic initiative aimed at making healthcare facilities more economically sustainable. For this potential to be fully realised, managers, healthcare professionals, and researchers need to work towards aligning innovation with long-term value creation.
This study is guided by a theoretical framework drawn from literature on healthcare management and AI adoption. Within this framework, cost savings are positioned as the central outcome of AI integration emerging from different pathways, including administrative efficiency, early disease detection and prevention, reduced admissions and readmissions, resource optimisation, workforce planning, clinical efficiency, easy access to care, and data-driven savings. In addition to immediate efficiencies, the framework highlights second- and third-order benefits achieved through process adaptation, continuous monitoring, and scalable integration, framing economic sustainability as an ongoing process rather than a fixed goal.
This research makes both theoretical and practical contributions by using an exploratory qualitative approach. The findings show that AI has the potential to create measurable efficiencies, reduce costs, and support healthcare delivery. This study concludes that AI should not be considered merely a technological upgrade, but rather as a strategic initiative aimed at making healthcare facilities more economically sustainable. For this potential to be fully realised, managers, healthcare professionals, and researchers need to work towards aligning innovation with long-term value creation.