Audiologists

Audiologists already use some AI tools in their work. For example, hearing tests can be partly automated: smartphone and computer apps now let people self-administer hearing exams using smart algorithms, and studies find these automated tests are nearly as accurate and much faster than manual ones ^{[1] [2]}. Hearing devices themselves have built-in AI: many modern hearing aids use machine learning to adjust sound to each person’s preferences (much like how online stores recommend products) ^{[2] [2]}.

In fact, research shows AI-assisted cochlear implant “mapping” can match or even beat manual tuning by experts, improving patients’ hearing outcomes ^[3]. Even safety tasks like workplace noise monitoring are being aided by AI: one study developed smart sensors and ML models that classify loud noise levels and alert workers (detecting hazards with about 91% accuracy) ^{[1] [1]}. Clinics also use software to automate routine business tasks: for example, data-driven marketing tools can automatically send personalized follow-up messages when patients buy devices ^[4].

AI tools for audiology exist today, but how fast they’re adopted depends on costs and attitudes. On the plus side, technology is available: free or cheap apps can screen hearing on phones ^[1], and advanced “AI” hearing aids are already sold in the market ^[2]. Using these tools can be cost-effective.

For example, a smartphone test costs basically nothing compared to an audiologist’s time. Audiologists are also in demand (about 15,800 jobs now, with 7% growth forecast) ^[5], so adding technology can help serve more patients. Moreover, there is a global shortage of hearing specialists and rising hearing-loss needs ^[1], which encourages clinics to try AI to reach underserved areas.