I recently returned from the Behavioral Health Tech (BHT) conference in Nashville, where clinicians, health systems, payers, technology companies, and behavioral health leaders gathered to discuss the field's future. Over more than three decades in psychiatric practice, I’ve seen a lot of innovations in behavioral health technology. A few have fundamentally changed how I practice, but many have simply generated excitement without affecting patient care.

This year, the tone was different. People still wanted to talk about what’s new, but the conversation had shifted more to how we use new technology in ways that actually improve behavioral health care.

Whether AI, remote monitoring, or biomarkers, it’s clear the future of behavioral health technology is in the data. We have access to more data than ever before. We can measure symptoms over time, collect information from wearables and other biomarkers, monitor what happens between appointments, and use AI to identify patterns across increasingly large datasets.

But more information does not automatically translate into better care. We need to decipher what information is useful and worth gathering. Below are four key points I took away.

1. AI and the Guardrails It Still Needs

AI has very quickly become part of nearly every aspect of healthcare, and behavioral health is no exception. Though I expected its application to be a hot topic, I was pleasantly surprised to find just as many centered on where its use makes the most sense and what safeguards should be in place.

That caution makes sense in our fields. Psychiatric diagnosis is highly nuanced. There’s considerable overlap in symptom profiles across conditions, and presentation can be affected by factors like trauma, comorbidities, medication use, substance abuse, and more.

AI is an........

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