THE integration of artificial intelligence into healthcare is ushering in a new era of medical innovation and practice, promising to revolutionise how diseases are diagnosed, treated and managed. With its ability to analyse massive datasets, automate complex tasks and generate personalised insights, artificial intelligence has the potential to increase efficiency, improve accuracy and deliver better patient outcomes on a scale never seen before.
Computer systems equipped with artificial intelligence are already widely deployed in medical science. Their applications range from diagnosing patients, supporting drug discovery and development, improving communication between doctors and patients, and transcribing medical documents such as prescriptions, to treating patients remotely.
Artificial intelligence is increasingly being used to generate text from source documents and clinical trial databases for plain language summaries, clinical study reports, clinical protocols and publications. It also helps organise and structure information for faster, more reliable use in clinical settings. By reducing inefficiencies, improving patient flow and enhancing safety throughout the care pathway, artificial intelligence tools can significantly improve the overall patient experience.
For example, remote monitoring via intelligent telehealth, using wearable sensors, allows doctors to track patients continuously. AI systems can also generate new ideas, uncover hidden patterns and propose solutions that human clinicians may not have considered. In biomedical research and drug development, this means designing novel molecules, predicting how they interact with biological systems and matching treatments to individual patients with far greater precision than traditional approaches.
The benefits of artificial intelligence in healthcare are already evident. It is currently applied to the diagnosis of cancer, neurological conditions and cardiovascular disease, where early detection has proved vital for preventing complications and improving treatment outcomes. Human鈥揳rtificial intelligence collaboration ensures that data processing remains context-aware and that decisions are refined by human expertise.
This combination results in more nuanced problem-solving and decision-making. For instance, outside medicine, AI can already assess dissatisfaction in customer service calls by analysing tone of voice and keywords. Within healthcare, some artificial intelligence tools can even analyse genetic data to recommend personalised lifestyle changes, helping reduce the risk of developing conditions such as heart disease or certain cancers.
Beyond healthcare, research such as Co鈥檚 Impact of Technology on the Workplace report for 2025 shows artificial intelligence improving work-life balance for senior business leaders, with 61 per cent reporting that automating routine tasks has freed them to focus on complex, strategic responsibilities. A similar principle applies to medicine: if artificial intelligence reduces the burden of repetitive documentation, clinicians can dedicate more time to patients.
Yet, the rapid growth of artificial intelligence brings real dangers. Data bias 鈥� arising from incomplete datasets or deliberate manipulation 鈥� can cause serious harm, particularly to minority groups excluded from training information on ethnicity, gender or race. Whether artificial intelligence will ultimately strengthen or weaken the doctor鈥損atient relationship remains uncertain. Some experts believe it will eliminate tedious tasks and give doctors more face-to-face time with patients, while others fear over-reliance on machines could erode human connection and trust.
What is clear is that artificial intelligence in health care has moved beyond hype. By 2025 it has become embedded in clinical decision-making, from diagnostics and risk prediction to workflow optimisation and real-time patient insights. Looking ahead, artificial intelligence will drive further automation in personalised treatment planning, decision support, drug discovery, clinical trials and administrative processes. However, ethical considerations, robust data protection and strict regulatory oversight remain essential.
Artificial intelligence can accelerate literature reviews and drafting, but only experienced regulatory medical writers can ensure that outputs meet professional standards. A balanced approach 鈥� using artificial intelligence for routine tasks while reserving human skill for strategic analysis, fine-tuning and compliance 鈥� offers the best way forward. This collaborative model allows medical writing and healthcare delivery to harness the power of AI鈥檚 responsibly, improving efficiency, accuracy and, above all, patient outcomes.
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Jannath Newaz is an engineer and poet.
