MARKET COMPETITIVENESS AND DEVELOPMENT OF DIGITAL INNOVATIONS IN HEALTHCARE INDUSTRY. - Abdivaliyeva Ezoza Gafur qizi,; Khusanov Salokhiddin, (TADQIQOTLAR, 2026)
The healthcare industry is undergoing a profound transformation driven by rapid digital innovation. While historical technological shifts have systematically improved people's  living  standards  and  health  indicators  around  the  world,  advanced  digital technologies  are  rethinking  clinical  possibilities,  from  supportive  imaging  to  the treatment of previously incurable diseases.This article provides an assessment of the development  and  impact  of  digital  innovations  in  healthcare,  focusing  on  two transformative  technologies:  augmented  reality  (AR)  and  neural  implants.  Using  a high-quality, evidence-based system, this study analyzes the clinical applications and market trajectories of AR and neural implants. The data was collected from industry research databases and clinical trial results documented by institutions such as Johns Hopkins University, Stanford Medical University, and Lawrence Livermore National Laboratory. Structured stakeholder analysis was applied to assess the multidimensional impact of these innovations on patients and healthcare professionals in four main areas: psychological, economic, cultural, and ethical. The results obtained indicate that both technologies  significantly  improve  clinical  accuracy  and  expand  therapeutic possibilities. AR reduces the surgical error rate by up to 21% and improves the training of medical personnel, supported by a projected cumulative annual growth rate (CAGR) of 25% by 2027. At the same time, neural implants, with a market value projected to reach $6.14 billion by 2032, effectively restore lost sensory, motor, and communication functions. For stakeholders, both technologies optimize clinical outcomes, reduce the cost  of  long-term  hospitalization,  and  foster  a  culture  of  continuous  innovation. However, they simultaneously pose serious challenges, including difficult conditions for training clinicians, high implementation costs that threaten equal access, a potential reduction in the quality of responsive patient care, and serious risks associated with the confidentiality of biometric and neural data.