Allowing various components of technology to come together seamlessly, Artificial Intelligence (AI) has been taking over the technology arena for some time. The pressing budget of UK’s National Health Services (NHS) has led to clinics being short-staffed and overworked. In the healthcare industry, AI uses algorithms to be tantamount to human cognition to analyze composite medical data. Institutions such as Massachusetts General Hospital, The Mayo Clinic, NHS have been applying AI programs to processes such as drug development, personalized medicine, treatment protocol development and patient monitoring. Use of AI may introduce certain type of risks such as algorithm bias, DNR implications and machine morality issues, though, research on the use of AI aims to validate its efficacy in improving patient results prior to its broader adoption. AI enables evaluation of current health of patients, access to more up-to-date research through NLP and identifies warning signs earlier in the care process thereby reducing risks of medical issues having long-term implications. Requiring a vast amount of data is indispensable for AI solutions to provide powerful insights. However, the obstacles faced in the use of AI must be overcome before a true change can take place.

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