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Google has officially embedded AI into Gmail, and this is not just another productivity update. Email is one of the most cognitively demanding systems people use daily, and now AI is sitting directly inside it. With Gemini, users can summarise long email threads instantly, ask their inbox questions in plain English, write or polish emails for free, receive reply suggestions that actually sound like them, and check tone, grammar, and clarity. Soon, Gmail will also auto-filter clutter, flag VIP messages, and surface high-stakes emails. The rollout starts in U.S. English, with more languages coming, and some advanced features requiring Pro or Ultra plans. From a therapy perspective, this shift matters more than it appears. Email is not just communication. It is executive functioning in action. It requires planning, prioritisation, working memory, emotional regulation, and pragmatic language skills. For many clients, and many clinicians, email is a daily source of cognitive overload. What Gemini is doing is externalising parts of that cognitive load. Summarising threads reduces working memory demands. Asking the inbox questions bypasses inefficient search strategies. Tone and clarity checks support pragmatic language. Drafting assistance lowers initiation barriers. These functions closely mirror the supports we already use in therapy, making Gemini function like a cognitive scaffold rather than a replacement for thinking. So how might therapists actually benefit from this? For speech and language therapists, Gemini can support professional written communication without compromising clinical intent. Writing parent emails, school correspondence, or multidisciplinary updates often requires precise tone, clarity, and pragmatics. AI-assisted drafting and tone refinement can reduce linguistic load while allowing the therapist to retain full control over content and boundaries. Clinically, these same features can be used to model appropriate email responses with older clients or adolescents working on functional communication and pragmatic skills. For psychologists and mental health professionals, the benefit lies in cognitive and emotional regulation. Difficult emails often trigger avoidance, anxiety, or overthinking. AI-supported drafting can help clients initiate responses, reduce rumination, and focus on the message rather than the stress of wording. In therapy, this opens space to discuss decision-making, boundaries, and reflective use rather than avoidance. For neurodivergent clients, particularly those with ADHD or ASD, Gemini may reduce barriers related to initiation, organisation, and interpretation of long email threads. Used intentionally, it can support access without masking needs. Used uncritically, it risks bypassing skill development. This distinction is where clinical guidance matters. There are also ethical considerations we cannot ignore. Gmail is not a clinical platform. Identifiable client information should never be entered into AI systems without safeguards. AI assistance does not remove professional responsibility for confidentiality, judgment, or relational nuance. The larger shift is this. AI is no longer a separate tool we choose to open. It is becoming part of the cognitive environment our clients live in. That means therapy cannot ignore it. Our role is not to resist these tools or to hand thinking over to them. Our role is to help clients and clinicians use AI reflectively, as support rather than authority. Three billion inboxes are about to change. Human judgment, clinical reasoning, and ethical care still need to lead.

The way people seek and process health information is evolving. Increasingly, individuals turn to digital tools to understand symptoms, test results, and medical terminology before or after interacting with healthcare professionals. The introduction of ChatGPT Health reflects this shift and represents a more structured approach to how health related conversations are supported by AI. Health questions are rarely neutral. They are often driven by uncertainty, anxiety, or difficulty interpreting complex information. ChatGPT Health has been designed as a dedicated environment for these conversations, acknowledging that health information requires clearer boundaries, higher safety standards, and careful framing to avoid misunderstanding or harm. One of the most clinically relevant features is the option for users to connect their own health data. This may include laboratory results, sleep patterns, activity levels, or nutrition tracking. When information is grounded in personal context, explanations become more meaningful and cognitively accessible. From a therapeutic standpoint, this can reduce information overload and support clearer self reporting, particularly for individuals who struggle with medical language or fragmented recall. Privacy and user control are central to this design. Health related conversations are kept separate from other interactions, and users can manage or delete connected data at any time. Information shared within this space is protected and not used beyond the individual’s experience. This emphasis on consent and transparency is essential for maintaining trust in any clinical or health adjacent tool. ChatGPT Health is not positioned as a diagnostic or treatment system. However, its value for therapists lies in how it can support diagnostic thinking without replacing professional judgement. In clinical practice, many clients present with disorganised histories, vague symptom descriptions, or difficulty identifying patterns over time. AI supported tools can help clients structure information prior to sessions, such as symptom onset, frequency, triggers, functional impact, and response to interventions. This structured preparation can significantly improve the quality of clinical interviews and reduce time spent clarifying basic details. For therapists, this organised information can support hypothesis generation and differential thinking. Patterns emerging from sleep disruption, fatigue, emotional regulation difficulties, cognitive complaints, or medication adherence may prompt more targeted questioning or indicate the need for formal screening or referral. In this way, AI functions as a pattern recognition support tool rather than a diagnostic authority. This is particularly relevant in neurodevelopmental and mental health contexts. Recurrent themes related to executive functioning, sensory processing, emotional regulation, or communication breakdowns can help clinicians refine assessment planning and select appropriate tools. The AI does not label conditions or confirm diagnoses, but it may help surface clinically meaningful clusters that warrant professional evaluation. In speech and language therapy and related fields, this can enhance functional profiling. Clients may use the tool to articulate difficulties with comprehension, expression, voice fatigue, swallowing concerns, or cognitive load in daily communication. This can enrich case history data and support more focused assessment and goal setting. It is essential to clearly distinguish diagnostic support from diagnostic authority. ChatGPT Health should never be used to assign diagnoses, rule out medical conditions, or provide clinical conclusions. Instead, it can support therapists by helping clients organise experiences, improving symptom description, highlighting patterns for exploration, and increasing preparedness for assessment. Therapists remain responsible for interpretation, clinical reasoning, and decision making. Part of ethical practice will involve explicitly discussing these boundaries with clients and reinforcing that AI generated insights are informational, not diagnostic. For patients, this tool may increase health literacy, confidence, and engagement. Being better prepared for appointments and therapy sessions can reduce anxiety and support more collaborative care. However, patients also require guidance to avoid overinterpretation or false reassurance. Therapists play a key role in helping clients contextualise information, process emotional reactions to health data, and identify when professional medical input is necessary. The development of ChatGPT Health involved extensive collaboration with physicians across multiple specialties, shaping how uncertainty is communicated and when escalation to professional care is encouraged. This strengthens its role as a preparatory and reflective resource rather than a directive one. As AI continues to enter health and therapy spaces, its clinical value will depend on how clearly roles and boundaries are defined. When used as a tool for organisation, reflection, and hypothesis support, rather than diagnosis or treatment, systems like ChatGPT Health can enhance clinical efficiency, improve communication, and support more informed participation in care while keeping professional judgement firmly at the centre. The future of AI in healthcare is not about replacing diagnosis. It is about supporting better histories, clearer questions, and more thoughtful clinical reasoning.

As therapists working daily in teletherapy, we have all felt the shift. AI is no longer something happening “out there” in tech headlines it is quietly entering our platforms, our workflows, and our clinical decision-making spaces. The question for us has never been whether AI will be used in therapy, but how it can be used without compromising ethics, clinical judgment, or the therapeutic relationship. Over the past year, we have actively explored, tested, and critically evaluated several AI-driven tools in teletherapy contexts. What stands out most is this: the most useful AI tools are not the loudest ones. They are the ones that reduce friction, cognitive load, and therapist burnout while preserving our role as the clinical authority. Expanding Access Without Diluting Care One of the most meaningful developments we’ve seen recently is how AI is being used to expand access to therapy rather than replace it. Platforms such as Constant Therapy have expanded their AI-driven speech and cognitive therapy programs into additional languages, including Spanish and Indian English. This matters clinically. It allows us to assign culturally and linguistically relevant home practice that aligns with what we are targeting in sessions, instead of relying on generic or mismatched materials. From our experience, this kind of AI-supported practice increases carryover without increasing preparation time something teletherapy clinicians deeply need. Conversational AI That Supports Continuity, Not Dependency Mental health platforms like Wysa, particularly with the introduction of Wysa Copilot, reflect a growing shift toward hybrid models where AI supports therapists rather than attempts to replace them. These systems help structure between-session support, guide reflective exercises, and support homework completion, all while keeping the clinician in the loop. When we tested similar conversational AI tools, what we valued most was not the chatbot itself, but the continuity. Clients arrived to sessions more regulated, more reflective, and more ready to engage because the therapeutic thread had not been completely paused between sessions. Speech and Language AI: Practice, Not Diagnosis Advances in automatic speech recognition have significantly improved the quality of AI-assisted speech practice tools. In articulation and fluency work, we’ve used AI-supported practice platforms to increase repetition, consistency, and feedback during teletherapy homework. Clinically, we see these tools as structured practice partners not assessors and certainly not diagnosticians. They help us gather cleaner data and observe patterns, but interpretation remains firmly in our hands. When used this way, AI becomes an efficiency tool rather than a clinical shortcut. Voice Biomarkers as Clinical Signals, Not Labels Another emerging area is the use of voice biomarkers tools that analyze vocal features to flag possible emotional or mental health risk markers. Tools like Kintsugi and Ellipsis Health are increasingly discussed in clinical AI spaces. When we explored these tools, we found them useful as conversation starters, not conclusions. In teletherapy, where subtle nonverbal cues can be harder to read, having an additional signal can help us ask better questions earlier in the session. We are very clear, however: these tools support clinical curiosity; they do not replace clinical judgment. Ethics, Regulation, and Our Responsibility Not all AI adoption has been smooth and rightly so. In 2025, several regions introduced restrictions on AI use in psychotherapeutic decision-making. From our perspective, this is not a step backward. It reflects a necessary pause to protect clients, clarify consent, and reinforce professional boundaries. As therapists, we carry responsibility not just for outcomes, but for process. Any AI tool we use must be transparent, ethically integrated, and clearly secondary to human clinical reasoning. What We’re Taking Forward Into Our Telepractice Based on what we’ve tested and observed, these are the principles guiding our use of AI in teletherapy: We use AI to reduce administrative and cognitive load, not to replace thinking.We choose tools grounded in clinical logic, not generic productivity hype.We prioritize transparency with families and clients about how technology is used.We treat AI outputs as data points, never as decisions. What feels different about teletherapy in 2026 is not the presence of AI it’s the maturity of how we engage with it. When AI is positioned as a background support rather than a clinical authority, it allows us to show up more present, more regulated, and more attuned to our clients. Teletherapy does not need less humanity. It needs protection of it. Used responsibly, AI helps us do exactly that.

As we reach the end of the year, many of us are reflecting not just on our caseloads or outcomes, but on how much our daily practice has shifted. 2025 was not the year AI took over therapy. Instead, it was the year AI quietly settled into our workflows and pushed us as clinicians to become more intentional about protecting clinical judgment while embracing useful innovation. From speech therapy and mental health to teletherapy platforms, AI moved from experimental to practical. What matters now is how we, as therapists, choose to use it. AI This Year From Hype to Real Clinical Use One of the most noticeable changes in 2025 is how AI tools are being designed around clinicians rather than instead of them. Platforms such as Wysa, particularly through clinician supported tools like Wysa Copilot, reflect this shift. These systems are no longer simple chatbots. They now function as structured supports that help maintain therapeutic continuity between sessions while keeping clinicians in control. From our own testing and use, the value has not been in AI talking to clients, but in how it supports reflection, homework follow through, and emotional regulation between sessions. Clients arrive more prepared, and sessions feel less like a restart and more like a continuation. Speech and Language Practice Where AI Truly Helps In speech and language therapy, AI had its strongest impact this year in practice intensity and consistency. AI assisted articulation and voice practice tools now offer more accurate feedback and structured repetition that is difficult to achieve consistently between teletherapy sessions. We have used these tools as practice partners rather than assessors. They help us collect clearer data and observe patterns over time, while interpretation remains human. Their strength lies in freeing our cognitive space so we can focus on planning, adapting, and responding within sessions. Accessibility and Reach A Quiet Win Another important development this year has been the expansion of AI driven therapy platforms into additional languages and regions. Tools like Constant Therapy expanding into multiple languages signal something important. AI can reduce access barriers without lowering clinical standards. For teletherapy, this has translated into better carryover, more culturally relevant practice materials, and stronger engagement outside live sessions. Voice Based AI and Emotional Signals Used With Caution 2025 also brought increased attention to voice based AI tools that analyze speech patterns for emotional or mental health signals. Tools such as Kintsugi and Ellipsis Health are often mentioned in this context. From our experience, these tools work best as signals rather than answers. In teletherapy, where subtle cues can be harder to detect, they can guide deeper clinical questioning. They do not diagnose, and they should never replace observation, clinical interviews, or professional judgment. Ethics and Regulation Took Center Stage This year also reminded us that innovation without boundaries is risky. Increased regulation around AI use in therapy particularly related to crisis detection, consent, and transparency has been a necessary step. As clinicians, this aligns with what we already practice. Therapeutic work requires accountability, clarity, and human responsibility. AI must remain secondary to the therapeutic relationship. How We Are Using AI Going Forward As we close the year, these principles guide our clinical use of AI. We use AI to reduce administrative and cognitive load rather than replace thinking.We choose tools grounded in clinical logic and therapeutic models.We remain transparent with clients and families about AI use.We treat AI outputs as supportive data rather than clinical decisions. When used this way, AI becomes an ally rather than a distraction. Looking Ahead If 2025 was the year of testing and learning, the year ahead will likely focus on refinement. We expect clearer standards, better clinician informed design, and deeper conversations around ethics, inclusion, and sustainability. Most importantly, we expect the focus to return again and again to what matters most. Human connection, clinical reasoning, and ethical care. AI will continue to evolve. Our role as therapists remains unchanged. We interpret. We adapt. We connect.