Artificial intelligence and dichotomy on benefits and challenges: what do healthcare providers say?

Bharat Singh, Surekha Kashyap, Ankita Grover


Background: In a developing country like India, with a vibrant information technology (IT) sector, employing Artificial Intelligence (AI) should be carefully weighed before its introduction in healthcare with relation to perception of healthcare providers (HCP's/Doctors).  

Methods: This qualitative study was conducted in medical college and affiliated hospital in India. Initially a pilot study was conducted for reliability and internal consistency of questionnaire. Thereafter, pre-tested questionnaire was distributed to 153 healthcare providers and their responses were analyzed on SPSS version 20.0 (IBM) to identify the demographic and job-related differences in their perception regarding the benefits and challenges of using AI in healthcare.

Results: Most of respondent were agreed upon the benefits of using AI in healthcare and most cited benefits were speedy decision making, better resource utilization and improvement in staff satisfaction. Similarly most cited challenges were lack of training on AI enabled machines, lack of skilled technical support, high cost of AI and data privacy issue. Further, Age and Job experience were significantly associated with benefits like timely and speedy decision making, improvement in the patient and staff satisfaction respectively. Furthermore, Age, Department, Job experience, Job profile were significantly associated with challenges like high cost of AI, lack of skilled technical support, lack of training in AI enabled machines and lack of trust in AI among patients.

Conclusions: Significant challenges of using AI in healthcare with demographic and job related variable based on the results of this research paper need to be resolved first in order to overcome the initial resistance in employing AI in healthcare.



Artificial Intelligence, Decision making, Healthcare providers (Doctors), Integrated Decision Support System, Perceived AI Benefits, Perceived AI challenges

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Kobayashi Y, Ishibashi M, Kobayashi H. How will "democratization of artificial intelligence" change the future of radiologists? Jpn J Radiol. 2019;37(1):9-14.

Aminololama-Shakeri S, Lopez J E. The Doctor-Patient Relationship with Artificial Intelligence. Am J Roentgenol. 2019;212:308-10.

Sen D, Chakrabarti R, Chatterjee S, Grewal D S, Manrai K. Artificial intelligence and the radiologist: the future in the Armed Forces Medical Services. J R Army Med Corps. 2019;1-3.

Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, Wang Y, Dong Q, Shen H, Wang Y. Artificial intelligence in healthcare: past, present and future. Stroke Vascular Neurol. 2017 Dec 1;2(4):230-43.

Moghadami H, Kharrat M. An Internet of Human (IoH) Framework for Improving Healthcare Business Models. Iranian J Med Informat. 2018 Dec 16;8(1):3.

Paul Y, Hickok E, Sinha A, Tiwari U. Artificial Intelligence in the Healthcare Industry in India, 2018. Available at: Accessed 19 January 2018.

Hussain W, Ishak W H, Siraj F Artificial intelligence in medical application: An Exploration. Health Inform Eur J. 2002;16:1-9.

Nealon J, Moreno A. Agent-Based Applications in Health Care. In: Moreno A, Nealon JL, eds. Applications of Software Agent Technology in the Health Care Domain. Whitestein Series in Software Agent Technologies and Autonomic Computing, Birkhäuser, Basel; 2003: 3-18.

Schulz J P, Nakamoto K. Patient behavior and the benefits of artificial intelligence: The perils of ‘‘dangerous’’ literacy and illusory patient empowerment. Patient Educ Couns. 2013;92(2):223-8.

Sun T Q, Medaglia R. Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. J Gov Inf. 2019;36(2):368-83.

Ursachi G, Horodnic IA, Zait A. How reliable are measurement scales? External factors with indirect influence on reliability estimators. Procedia Econom Finance. 2015 Jan 1;20:679-86.

Maskara R, Bhootra V, Thakkar D, Nishkalank N. A Study on the perception of medical professionals towards artificial intelligence. Int J Multidiscip Res Dev. 2017;4(4):34-9.

Miotto R, Wang F, Wang S, Jiang X, Dudley J T. Deep learning for healthcare: review, opportunities and challenges. Brief Bioinform. 2018;19(6):1236-46.

AI use in European healthcare@ HIMSS Analytics/ e-health trendbarometer, 2018. Available at: Accessed 9 May 2018.

Walsh P. Automating Healthcare Can Improve the Patient Experience, 2018. Available at: Accessed 6 July 2018.

Kanyadi P. Using the Power of AI to Improve Staff Retention, Job Satisfaction, 2018. Available at: Accessed 10 October 2018.

Seeley R. IT Department can benefit from AI, but at high cost, 2018. Available at: Accessed 6 August 2018.

Mcquater K. Generational gap in perceptions of AI, 2017. Available at: Accessed 6 December 2018.

Survey: Automated Patient Experiences Will Transform the Delivery of Care, 2018. Available at: Accessed 3 September 2018.

Taylor B. Building trust in healthcare, AI and automated decision-making, 2018. Available at: Accessed 29 June 2018.

Groover M C. Automation, 2019. Available at: Accessed 6 January 2019.

Pomering B. Health Perspectives: Are people ready to embrace artificial intelligence and robotics in healthcare? Available at: Accessed 11 June 2018.