We are on the cusp of a revolution in how healthcare is delivered. And the principal agent behind this transformational change is artificial intelligence (AI).
Far from being an isolated innovation, AI is becoming an integral part of operational transformations that will drastically redesign the healthcare landscape. From patient management to x-ray analysis and diagnosis, there’s almost no area of healthcare that’s not being disrupted by AI. Its potential to deliver a faster, more targeted and exponentially more efficient level of care is truly groundbreaking, as thousands of AI-enabled healthcare platforms either in use or in advanced stages of development are poised to disrupt every corner of the sector.
AI is already reducing X-ray diagnosis delivery times by approximately 75%, and in ophthalmology, breakthroughs in retinal image scanning at scale could prevent 95% of blindness caused by diabetic retinopathy. One US healthcare company utilising AI for retinal scan analysis is providing clinicians with the opportunity to screen for over 140 systemic conditions, including cardiovascular and neurological issues.
It’s no exaggeration to say that AI is disrupting most of the traditional roles of physicians, with almost every technical function that relies on a combination of knowledge and process performed faster, more reliably and more accurately by AI.
Healthcare management
AI healthcare virtual assistants designed by organisations like Medcore Solutions are providing groundbreaking vital assistance for healthcare managers. AI-enabled virtual assistants are helping managers automate day-to-day planning and care coordination, staffing, appointment scheduling and patient correspondence with integrated data. They can also securely access patient information, and with the power to negotiate settlement – if empowered to do so by human managers – will pursue outstanding receivables.
Worldwide, the virtual-assistance market in healthcare alone is expected to top USD 2 billion within the next five or six years, with further growth likely to flourish exponentially.
Companies like Spectrum.life are also giving healthcare managers valuable assistance in patient engagement. Spectrum, for example, offers a digital portal to facilitate interactive and meaningful relationships with patients, and its AI health-navigation and clinician-matching tools are helping to deliver more efficient care for insurers as well as patients.
Image scanning
One of AI’s most immediate benefits in healthcare is its capability to identify and treat diseases early. And early diagnosis can be truly life-saving.
In ophthalmology, a specialisation projected to encounter over 70 million sight-threatening cases of diabetic retinopathy (DR) globally by 2045, the advances are staggering – a massive 95% of sight loss from DR can be eradicated with early AI-enabled diagnosis.
For specialisations like radiology, reporting times can be drastically reduced. While in some parts of the world releasing reports can take more than 10 days, and even in highly streamlined systems many hours, AI is allowing validated diagnosis to be available in minutes. What’s more, AI improves interpretation accuracy by around 40% compared with existing human error levels in radiology. That’s a human-error rate in scan processing of around 5%, down to under 3% with AI.
In the US, Northwell Health and Aegis Ventures has launched AI technology that can non-invasively examine features in the back of a patient’s eye – blood vessels, optical nerves and lesions, for example – and apply deep learning to scan for over 140 diseases elsewhere in the human anatomy.
Recruitment, credentialing and onboarding
Data-driven decision-making in the recruitment, onboarding and training of clinical staff is drastically improving the quality, speed and cost of the hiring process. Tern, an AI-powered digital end-to-end recruitment platform from the UK, is just one of many platforms now disrupting traditional recruitment methods in hiring and retaining top medical talent from around the world. And from a healthcare-management perspective, higher retention rates reduce the cost of short-term locums, with proven average savings for large hospitals of over USD 5 million.
Tern’s AI technology relies on predictive analytics to interrogate and scrutinise previous employment data, qualifications and performance metrics. And its contribution to more accurate assessments of the right fit for a role is huge and will only improve. Hiring accuracy is currently seeing a 30% increase, with data-driven hiring decisions driving down the costs associated with poor hires.
From a healthcare-facility point of view, digital AI recruitment platforms are giving medical facilities a competitive edge in finding and retaining qualified, permanent staff. But Tern’s AI technology not only finds staff – the platform’s autopilot also deals with everything from visas to housing, banking and pastoral support for staff relocating from elsewhere.
In short, a truly disruptive platform.
Healthcare customer service and call centres
Rapid and transformative advances in healthcare customer service are now using multilingual AI agents within interactive voice response (IVR) systems. These systems have evolved drastically to give patients a more efficient experience, with many reporting a 25%–30% increase in patient-satisfaction scores. Driven by natural language programming (NLP), machine learning and AI algorithms, AI-healthcare call centres can now offer dynamic, conversational experiences that are unrecognisable from the static menus characteristic of traditional call centres.
No matter how high the levels of human-staff training, these developments simply outstrip the capability of human agents; for example, Cosmos in Dubai offers multilingual customer service in over 80 languages and can interact empathetically with patients in granular detail on wide-ranging subjects such as treatment options and the state and progress of their medical conditions. With an innate ability to multi-task, AI customer-service centres can process and analyse a patient’s medical history, take notes, update records, schedule future appointments and recommend a physician based on its analysis of every single doctor’s background. With no drop-off in quality, these systems can handle 10,000 calls an hour, every hour, 365 days a year across multiple time zones without the need for lunch breaks, holidays or sick leave.
What’s in the pipeline? The breathtaking future of healthcare AI
Healthcare across the world is keen to avoid its own so-called Kodak moment. According to world-renowned AI-healthcare advocate, Professor Shafi Ahmed, the sector needs to ask itself how it can change to improve patient outcomes. In short, it needs to disrupt itself.
In Professor Shafi Ahmed’s view, AI is revolutionising healthcare as we know it. From AI interfaces as a first point of contact with a physician, to remote dermatology diagnosis using a smartphone and AI-enabled image scanning, the technology is dramatically reshaping how the sector delivers healthcare now and is making us reimagine how it might look in the future. In his own words, it’s the “alacrity of process” that delivers the exponential improvements in diagnosis, treatment and systems efficiencies.
Recent breakthroughs in AI from the Chinese firm Deepseek suggest that AI is beginning to disrupt itself, a trend that could have significant implications for healthcare. With big players like OpenAI, Google and Meta convinced of the strength and efficacy of their own AI moats, Deepseek has apparently managed to match the capabilities of its bigger rivals using one-tenth of the processing power and for 10% of the cost. That will allow healthcare players to do far more for far less. Cheaper development and infrastructure will enable pharmaceutical companies to design more in-house tailored models for healthcare delivery. And its affordability is likely to jumpstart projects in development that have been held back for reasons of disputed accuracy or safety.
Ali Parsa, founder of Babylon, has launched a personal AI clinical assistant designed to support clinicians and patients across the full spectrum of routine clinical and administrative tasks, including patient interactions, continuous monitoring, decision-making, and chronic and post-operative care. Over the course of the next decade, he believes that advances in healthcare AI are likely to match elastic demand with elastic supply. “AI should provide constant, near-free availability of healthcare services to everyone, everywhere”, he says.
It’s a truly compelling vision of the future.
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