https://aident.co.uk/UK practice principals, associate dentists and practice managers — clinically trained but not technical — who are evaluating, buying and running AI tools for radiograph reading, patient triage and front-desk admin inside an NHS or mixed practice.https://aident.co.uk/blog/001-what-ai-actually-does-inside-a-uk-dental-practice-today/https://aident.co.uk/blog/001-what-ai-actually-does-inside-a-uk-dental-practice-today/Separates the four genuinely deployed categories — radiograph analysis, triage, notes, front desk — from marketing fiction, and gives principals a map of which ones are worth attention first.https://aident.co.uk/blog/002-how-ai-reads-a-dental-radiograph-explained-without-the-maths/https://aident.co.uk/blog/002-how-ai-reads-a-dental-radiograph-explained-without-the-maths/Argues that clinicians need a working mental model of pixel-level pattern detection — not deep learning theory — to judge when an AI output deserves trust.https://aident.co.uk/blog/003-the-six-front-desk-jobs-ai-can-realistically-take-over/https://aident.co.uk/blog/003-the-six-front-desk-jobs-ai-can-realistically-take-over/Breaks reception work into discrete tasks and shows that automation succeeds on bounded, repetitive jobs and fails on anything requiring judgement about a distressed patient.https://aident.co.uk/blog/004-is-your-dental-ai-a-medical-device-a-principal-s-guide-to-uk/https://aident.co.uk/blog/004-is-your-dental-ai-a-medical-device-a-principal-s-guide-to-uk/Makes the case that diagnostic claims are the dividing line: if a tool tells you a lesion is present, it is regulated, and buying an unregistered one puts the clinician on the hook.https://aident.co.uk/blog/005-what-an-ai-dental-scribe-actually-captures-during-an-exam/https://aident.co.uk/blog/005-what-an-ai-dental-scribe-actually-captures-during-an-exam/Walks through a real check-up transcript to show what ambient capture gets right, what it invents, and why the dentist still writes the diagnosis line.https://aident.co.uk/blog/006-teledentistry-in-nhs-practice-what-you-are-allowed-to-do/https://aident.co.uk/blog/006-teledentistry-in-nhs-practice-what-you-are-allowed-to-do/Clarifies that remote assessment is permitted and claimable in narrower circumstances than vendors imply, and maps the boundary before a practice builds a workflow on it.https://aident.co.uk/blog/007-sensitivity-specificity-and-why-your-ai-flags-caries-that-is/https://aident.co.uk/blog/007-sensitivity-specificity-and-why-your-ai-flags-caries-that-is/Argues that a high-sensitivity detector tuned for research benchmarks will over-call in a low-prevalence NHS recall population, and shows how to read the threshold setting.https://aident.co.uk/blog/008-what-dental-ai-software-really-costs-per-surgery-per-year/https://aident.co.uk/blog/008-what-dental-ai-software-really-costs-per-surgery-per-year/Builds a full cost model including per-image fees, training time and integration work, and shows why headline per-month pricing understates the first-year figure by a wide margin.https://aident.co.uk/blog/009-gdc-standards-and-ai-assisted-diagnosis-where-responsibility/https://aident.co.uk/blog/009-gdc-standards-and-ai-assisted-diagnosis-where-responsibility/Establishes that the registrant carries the clinical decision regardless of what the software said, and what that means for how you document disagreement with a tool.https://aident.co.uk/blog/010-cutting-failed-appointments-with-automated-reminders/https://aident.co.uk/blog/010-cutting-failed-appointments-with-automated-reminders/Uses reminder timing and channel data to argue that message cadence, not message wording, drives most of the FTA reduction practices report.https://aident.co.uk/blog/011-designing-a-triage-form-that-sorts-real-dental-emergencies/https://aident.co.uk/blog/011-designing-a-triage-form-that-sorts-real-dental-emergencies/Shows that the value of digital triage comes from a small number of red-flag questions, and that longer forms reduce completion without improving sorting.https://aident.co.uk/blog/012-who-signs-an-ai-generated-clinical-note/https://aident.co.uk/blog/012-who-signs-an-ai-generated-clinical-note/Argues that the sign-off step must be an active clinical read, not a click, and proposes a practical check that takes under a minute per patient.https://aident.co.uk/blog/013-bitewings-periapicals-and-panoramics-where-ai-adds-most/https://aident.co.uk/blog/013-bitewings-periapicals-and-panoramics-where-ai-adds-most/Contends that detection performance varies sharply by view type and that practices should switch AI on for bitewings first rather than across the whole radiograph library.https://aident.co.uk/blog/014-an-eight-week-pilot-protocol-for-any-dental-ai-tool/https://aident.co.uk/blog/014-an-eight-week-pilot-protocol-for-any-dental-ai-tool/Provides a structured pilot with baseline metrics and a pre-agreed kill criterion, arguing that pilots without a defined failure condition always convert to purchases.https://aident.co.uk/blog/015-uk-gdpr-and-patient-photographs-sent-to-an-ai-service/https://aident.co.uk/blog/015-uk-gdpr-and-patient-photographs-sent-to-an-ai-service/Works through lawful basis and special category conditions to show that consent is usually the wrong basis for clinical images, and what to rely on instead.https://aident.co.uk/blog/016-consent-and-channel-choice-for-sms-email-and-whatsapp-recall/https://aident.co.uk/blog/016-consent-and-channel-choice-for-sms-email-and-whatsapp-recall/Shows that messaging preference records, not marketing consent, govern recall contact, and that most practices hold the wrong permissions on file.https://aident.co.uk/blog/017-ai-phone-answering-versus-a-human-answering-service/https://aident.co.uk/blog/017-ai-phone-answering-versus-a-human-answering-service/Compares cost, call containment and escalation quality, and argues that AI wins on volume overflow while outsourced humans still win on complaints and pain calls.https://aident.co.uk/blog/018-how-to-read-a-dental-ai-vendor-s-clinical-evidence-pack/https://aident.co.uk/blog/018-how-to-read-a-dental-ai-vendor-s-clinical-evidence-pack/Teaches buyers to check dataset origin, reader study design and whether the comparison group resembles a UK general practice — the three places evidence packs are weakest.https://aident.co.uk/blog/019-when-the-ai-and-the-dentist-disagree-building-a-house-rule/https://aident.co.uk/blog/019-when-the-ai-and-the-dentist-disagree-building-a-house-rule/Proposes a written practice policy for resolving disagreement, arguing that ad hoc resolution produces inconsistent charting across associates in the same practice.https://aident.co.uk/blog/020-out-of-hours-and-nhs-111-referrals-where-remote-triage-fits/https://aident.co.uk/blog/020-out-of-hours-and-nhs-111-referrals-where-remote-triage-fits/Argues that remote triage earns its keep by filtering the Monday morning backlog rather than by replacing the urgent care rota.https://aident.co.uk/blog/021-ai-notes-and-fp17-accuracy-avoiding-a-claims-problem/https://aident.co.uk/blog/021-ai-notes-and-fp17-accuracy-avoiding-a-claims-problem/Makes the case that generated notes must be checked against the banded claim, because narrative richness can contradict the treatment actually claimed.https://aident.co.uk/blog/022-ai-measurement-of-periodontal-bone-loss-useful-or-noise/https://aident.co.uk/blog/022-ai-measurement-of-periodontal-bone-loss-useful-or-noise/Argues that automated bone level measurement is most valuable for longitudinal comparison and staging consistency, not for single-visit diagnosis.https://aident.co.uk/blog/023-the-data-processing-agreement-clauses-that-matter-in-dental-/https://aident.co.uk/blog/023-the-data-processing-agreement-clauses-that-matter-in-dental-/Identifies the handful of clauses — sub-processors, model training rights, data location, deletion on exit — that determine whether a DPA actually protects patients.https://aident.co.uk/blog/024-structured-templates-or-ambient-notes-match-the-tool-to-the-/https://aident.co.uk/blog/024-structured-templates-or-ambient-notes-match-the-tool-to-the-/Argues that exams and consultations suit ambient capture while restorative and surgical visits are better served by structured templates, and that mixing them badly is why adoption stalls.https://aident.co.uk/blog/025-showing-ai-radiograph-overlays-to-patients-without-overselli/https://aident.co.uk/blog/025-showing-ai-radiograph-overlays-to-patients-without-overselli/Contends that overlays raise case acceptance but create a consent risk if presented as certainty, and offers language that keeps the clinician's judgement visible.https://aident.co.uk/blog/026-open-apis-in-uk-dental-software-who-actually-lets-you-connec/https://aident.co.uk/blog/026-open-apis-in-uk-dental-software-who-actually-lets-you-connec/Argues that integration depth, not feature lists, decides whether an AI tool gets used daily, and audits what the main UK systems currently expose.https://aident.co.uk/blog/027-getting-usable-patient-photos-for-remote-assessment/https://aident.co.uk/blog/027-getting-usable-patient-photos-for-remote-assessment/Shows that most remote assessments fail on image quality rather than clinical difficulty, and that simple capture guidance fixes the majority of retakes.