Artificial intelligence is already in healthcare –

including audiology.

Some of it is genuinely very useful.

Some of it is also a bit overcooked. The important question is not whether AI is impressive, but whether it improves care in a way that is safe, transparent, and accountable. In audiology, AI can already help with practical tasks. Examples include: writing clinical notes, scheduling, organising patient information, taking phone calls, helping hearing aid wearers troubleshoot problems. Used well, that greatly reduces administrative workload. The practical upshot is more time spent solving hearing challenges.

What this looks like in practice: your audiologist now spends more time looking at you while you speak, compared to before – where you would watch and listen to hundreds of keystrokes while the audiologist tried to keep up. And it’s not their fault. The pressure is very real: auds see six to eight appointments per day, each of 30-60 minutes, and mostly back to back. Some do manage lunch breaks, which is always nice. But capturing history and appointment facts while mentally resolving problems and planning – this has to come first. And it’s not always easy. Which is why AI is so exciting right now.

But there are caveats that need to be acknowledged. First, AI can never replace a clinician: AI is is reasoning system, not a person. AI does not examine, interpret, reason, or understand in the way an audiologist does. Second, AI can sound knowledgeable and highly confident, and that is part of the risk. Modern AI systems are very good at producing fluent, plausible answers. They can also hallucinate, over-infer, happily find rakes to walk over, all the while misleading the user in the most overconfident yet subtle way possible. In healthcare, that means AI can and definitely should assist with thinking, but it should never be mistaken for judgement.

A third caveat – arguably the most important – is that patients need to know when AI is being used and what it is being used for. So, if a clinician says, “Do you mind if I use AI to help process this appointment?” then that is a reasonable moment to ask a few questions. Ask: “What information is being used and for what purpose?” “Where does that information go?” “Is it stored, and if so, for how long?” “Who can access it?” “What safeguards are in place to protect privacy?” None of these are minor technical details. They are part of informed consent and ethical care.

As such, patients should feel free to decline. If a clinician cannot clearly explain where the data goes, how long it is retained, who may access it, and what the tool is actually doing, then the explanation is not yet good enough. A responsible clinical tool should be understood by the people using it. Not treated as a mysterious invention that somehow sorts itself out.

A fourth related caveat is – right now (early 2026) many AI tools in healthcare are general-purpose; which is fine in principle. But if they are connected to email, cloud accounts, chat history, or broader productivity systems, then sensitive information may be handled in ways that are not obvious at the point of care. Privacy policies may describe this in broad terms, but patients are still entitled to ask questions about what happens to their information once it enters the system. Below is what good clinical use of AI should look like, in hear.’s opinion.