Dr Hannah Allen is a GP and the Chief Medical Officer at Heidi.
- Chief Medical Officer | Heidi
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Dr Hannah Allen, practising GP and Chief Medical Officer at Heidi – a digital artificial intelligence (AI) care partner – provides key insights into what safety-first AI in healthcare looks like in practice.
Step into a GP surgery on a typical Monday morning and the strain is apparent. With appointments that run through lunch, reception staff squeezing in one more “urgent” patient, and a backlog of prescriptions and test results sits in the electronic inbox.
Behind the consultation room door, a clinician is trying to listen carefully, think clearly, and document accurately whilst navigating a clunky record system that was never built for the way general practice actually works.
Technology should reverse that reality, rather than intensifying it. Any digital tool must pass a simple test: does it give clinicians time and headspace for safe care, or does it add more friction to an already stretched system?
The most meaningful role for AI in healthcare is quiet: technology that handles the background work so clinicians can return to the core of medicine, connecting with patients, hearing their stories, and delivering high-quality care.
PAST DIGITAL TRANSFORMATION: UNFIT FOR GENERAL PRACTICE
Over the past decade, general practice has been pushed to breaking point. Demand and case complexity have risen; expectations have expanded; administrative work has skyrocketed.
The average health professional now spends well over a day each week on tasks that never appear on any rota: repeat prescriptions, document processing, coding, and chasing results.
Previous waves of digital transformation were supposed to help. Instead, many enterprise record systems were designed around managerial and financial requirements rather than the realities of a 10 or 15-minute consultation, leaving clinicians with slow, unintuitive workflows and drops in productivity despite the heavy investment.
As days run on without natural breaks, cognitive performance understandably falls and burnout increases. Against that backdrop, scepticism towards another round of technology is justified.
Dr Hannah Allen, GP and Chief Medical Officer, Heidi
The most powerful future for AI in healthcare is not a talking algorithm in the corner of the room. It is invisible technology that quietly manages information and administration so that clinicians can concentrate on patients without distraction.
Dr Hannah Allen, GP and Chief Medical Officer, Heidi
CHANGING THE DYNAMICS OF PATIENT CONSULTATION
Into this environment comes a new generation of ambient clinical AI: an AI care partner that supports the whole clinical day. Documentation has been the proven starting point, including ambient voice technology (AVT).
Instead of focusing on typing during or after the appointment, clinicians can focus on the patient whilst the technology listens in, assembles a structured draft note, and identifies tasks and follow‑up prompts based on the conversation.
Recent evaluations of AVT in UK primary and urgent care have reported documentation time per consultation cut by roughly half, with paperwork completed outside contracted hours reduced by more than 60 percent and many clinicians describing a noticeable drop in documentation‑related stress and better work‑life balance.
The impact goes beyond efficiency. Clinicians using these systems report greater psychological safety because they are no longer trying to memorise and later reconstruct every detail. The dynamic between clinician and patient shifts as it creates space for more direct eye contact, trust, and connection.
Importantly, AVT has clear limits around clinical judgement, particularly when we think about situations where context carries more weight than language alone. For example, a familiar patient mentioning chest pain in passing may not mean the same as a new, unexplained symptom in a stranger, even if the words are identical. Decisions about nuanced management of patients remain firmly with the clinician.
As these systems mature, the care partner role extends across the full clinical day: helping the clinician to prepare by synthesising fragmented patient history and highlighting priorities, bringing evidence and local guidelines into the conversation in real time at the point of care, and then coordinating what happens afterwards, from drafting referrals and tasks for the wider team to checking on treatment response and escalating when needed.
SAFETY, DATA PROTECTION, AND CLINICAL RESPONSIBILITY
Any AI system used in patient care must be built with safety and data protection embedded in it from the start. That means GDPR compliance and Data Protection Impact Assessments that set out what is collected, where it is hosted, and how it is processed.
Consultation data should not be reused to train models, and organisations need control over retention and deletion so local governance and national standards are met.
On safety, headline “hallucination rates” are not enough. Assurance requires precision monitoring, recall, and composite accuracy, backed by incident handling and independent audits so vendors are not marking their own homework.
Throughout, clinical responsibility does not shift. AI tools or care partners are not clinicians, and so notes, diagnoses, and treatments will always remain the clinician’s role. Regulators, defence organisations and professional bodies will continue to look to the human professional when care is scrutinised, so provider organisations and integrated care systems must choose tools that are demonstrably safe and effective.
THE FUNDING AND PROCUREMENT TEST
AI software is often squeezed into rigid budgets that tend to lack flexibility for system-wide benefits such as reduced burnout, better retention, or lower locum spend, even though workforce sustainability is one of the system’s most urgent challenges.
Integrated care systems are encouraged to act at scale, yet individual practices and departments still shoulder much of the contracting and compliance burden. Central frameworks, shared assurance routes, and “procure once for many” mechanisms can help safe technologies spread more quickly, aligning incentives with outcomes and staff well-being.
If those structural pieces do not move, the most promising AI will get stuck in the pilot stage rather than becoming a part of everyday care.
The most powerful future for AI in healthcare is not a talking algorithm in the corner of the room. It is invisible technology that quietly manages information and administration so that clinicians can concentrate on patients without distraction.
When AI becomes the quietest presence in the consulting room, the human relationship at the heart of medicine is finally able to speak louder.
This article was contributed by a guest author and published by the editorial team at EME Outlook, part of the Outlook Publishing global network of B2B industry magazines.
Outlook Publishing features leadership insights, industry perspectives, and company stories from organisations shaping sectors including manufacturing, mining, construction, healthcare, supply chains, food production, and sustainability.
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