Background:

Artificial Intelligence (AI) has quickly evolved from a theoretical concept to a practical tool in healthcare, including audiology, influencing everything from diagnostics to rehabilitation. While this transformation has generated excitement, it has also raised concerns within the field

With the advent of “smart” hearing aids in the early 2000s, some hearing aid companies began promoting their products as AI-powered, although many of these technologies were more accurately described as rule-based or adaptive machine learning systems(ML). At the time, the boundaries between AI and ML were blurry, and anything that showed responsiveness to environmental input was labeled “intelligent”

Aim of the work:  This review critically examines the evolution of AI in audiology, tracing its development from early claims in selected hearing technologies to current applications and potential future advancements. Inspired by the philosophy of judo, we propose that audiologists embrace AI’s transformative potential, strategically redirecting its progress to enhance clinical practice, education, and patient outcomes rather than resisting its integration.

Describtion: Through a chronological analysis of past technologies, validated modern tools, and emerging advancements, this review examines how audiologists can evolve their skillsets, enhance traditional assessment methods, and effectively manage patient expectations shaped by AI-driven algorithms.