A STUDY ON THE ADOPTION, UTILIZATION, AND FUTURE PERCEPTION OF AI-DRIVEN HEALTHCARE TOOLS

Abstract

Artificial intelligence has been growing ever since its conception. It has revolutionized many significant fields, from finance to healthcare, from human resources to building software. It is bound to grow in the future with new advancements coming in every now and then. But when it comes to sensitive fields like health care and medicine, its adoption and utilization are not as easy to understand as it is in other fields like finance. The majority of the time, when artificial intelligence is correlated with the healthcare field, medical professionals are kept Add the core of the study, and rarely is the user's perspective understood. This project will keep keeping general public in focus of the study and understand their utilization, trust, and adoption of artificial intelligence tools, in addition to how they perceive the future of these tools. There are multiple drivers and multiple barriers the widespread adoption of these tools in current times as well as in future as well. This study focused on what factors are more significant to the general user and what matters to them the most. In addition to this the most commonly used tools Were identified using the responses obtained from the general public. Using multiple tools like SPSS, Excel, etc., significant quantitative analysis was done in addition to the qualitative analysis of the respondents in order to analyze and observe the attributes. The respondents were provided with multiple closed and open-ended questions to gain opinions. Both quantitative and qualitative analyses were conducted to solidify the results, and conclusions were made strictly on the basis of the results of different analyses. The primary objective of the research was to understand different characteristics of the general public. As secondary objectives of the research, results were expected to show what the most widely used tools, the most influential driver, and the most influential barrier. These insights are crucial to understanding what users want and what matters most to them. This helps in building strategies according to what is needed and not what might be needed. 4 The study concludes that the successful integration of AI in personal healthcare will need tools with user-centered design, better trust mechanisms, and policies that balance innovation with ethical responsibility. These insights offer practical implications for developers, healthcare managers, and policymakers working towards AI for improved healthcare delivery.