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Artificial intelligence is revolutionizing healthcare by replacing tedious and time-consuming processes with unparalleled efficiency. For example, AI can now automate the analysis of total kidney volume, which used to take 45 minutes per patient, and get results in a matter of seconds. In a similar vein, AI-powered scribes can cut down on manual documentation time by up to 90% and speed up recording by 170%. AI is being quickly incorporated into fields including disease diagnosis, health monitoring, and virtual consultations in addition to administrative duties. Its speed and accuracy in handling large volumes of labor are changing the way healthcare providers handle time-consuming but necessary tasks, allowing them to concentrate on patient care. I sincerely hope that with this new technology, visits to the hospital will no longer be an entire day affair as I have experienced, especially when you are waiting for hours in an emergency room to get an x-ray and then have to wait even longer for that X-ray to be examined. Instead, the AI would use pattern recognition to scan the X-ray, determine how severe of a fracture it is plus the best method of repair, and the patient would have an answer in a few minutes instead of hours.

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Artificial intelligence (AI) is evolving medical imaging by using the massive computing abilities of machine learning to mine body scans

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AI is transforming personalized care by enabling highly customized treatment techniques. It can detect early indicators of patient deterioration using remote monitoring systems such as wearables and sensors (I imagine this is a more advanced version of the technology in Fit-Bits that indicate an increase in heart rate), resulting in timely interventions. By evaluating large datasets created by pharmacogenomics, AI assists healthcare providers in predicting drug responses and designing treatment strategies according to an individual's genetic profile. This precision transforms patient treatment, boosting outcomes while reducing unpleasant responses. AI, whether through intelligent telemedicine or advanced data analysis, bridges the gap between general medical practices and personalized therapy, allowing us to enter a new era of highly customized healthcare solutions. I find the prospect of individualized prognoses to be science fiction turned reality, as we have already made strides with personalized genetic testing with companies such as 23andMe, and now we can consider using AI with said information for easier comprehension and, if necessary, a unique treatment plan instead of the “one size fits all” methods we are used to.

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How will AI transform precision medicine? – Ava Amini

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AI has revolutionized drug/medicine development, bringing amazing advancements to the field. Tools like AlphaFold can make precise protein structure predictions, improving drug design and reducing costs with incredible accuracy at a rate that humans could never compete with. AI also excels at identifying key disease targets through network analysis and employs models like GANs (Generative Adversarial Networks) to design molecules optimized for specific purposes. Additionally, AI supports clinical trials by easing patient recruitment and fine-tuning trial protocols, making the process more efficient. These applications highlight how AI has significantly accelerated drug discovery while maintaining a focus on cost reduction and innovation. I personally find this incredibly fascinating in that we are at a point where we can simulate drugs and medicines that do not even exist yet to see how the body would react to them based on the information we currently have.

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How AI is accelerating drug discovery - Nature's Building Blocks | BBC StoryWorks

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Mayo Clinic Press Editors. (2024, March 27). AI in healthcare: The future of patient care and health management. Mayo Clinic Press. https://mcpress.mayoclinic.org/healthy-aging/ai-in-healthcare-the-future-of-patient-care-and-health-management/ (This article helped me get information on how much faster AI processing is compared to humans when it comes medical imaging analysis)

Bajwa, J., Munir, U., Nori, A., & Williams, B. (2021). Artificial intelligence in healthcare: Transforming the practice of medicine. Future Healthcare Journal, 8(2), 188–194. NCBI. https://doi.org/10.7861/fhj.2021-0095 (This article provided information on the speed at which AI can operate on specific medical jobs)

Hamed Taherdoost, & Alireza Ghofrani. (2024). AI’s role in revolutionizing personalized medicine by reshaping pharmacogenomics and drug therapy. Intelligent Pharmacy, 2(5). https://doi.org/10.1016/j.ipha.2024.08.005 (This article was key for information regarding personalized medicine)

Podgornyy, A. (2025, February 28). Five AI Innovations That Will Redefine Healthcare In 2025. Forbes. https://www.forbes.com/councils/forbestechcouncil/2025/02/28/five-ai-innovations-that-will-redefine-healthcare-in-2025/ (This article gave me the statistics of AI versus human scribing in medical professions)

Ocana, A., Pandiella, A., Privat, C., Bravo, I., Luengo-Oroz, M., Amir, E., & Gyorffy, B. (2025). Integrating artificial intelligence in drug discovery and early drug development: a transformative approach. Biomarker Research, 13(1). https://doi.org/10.1186/s40364-025-00758-2 (The article was my main source of information regarding how AI aids in drug development)

Md. Faiyazuddin, Syed, Anand, G., Siddiqui, R. K., Mehta, R., Khatib, M. N., Shilpa Gaidhane, Quazi Syed Zahiruddin, Hussain, A., & Sah, R. (2025). The Impact of Artificial Intelligence on Healthcare: A Comprehensive Review of Advancements in Diagnostics, Treatment, and Operational Efficiency. Health Science Reports, 8(1). https://doi.org/10.1002/hsr2.70312 (This article was my source of information for ethical and societal concerns of AI in healthcare)

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As with anything related to artificial intelligence, the future of AI in healthcare is both exciting and complex, as it brings incredible advancements alongside significant ethical challenges. AI's reliance on vast amounts of data raises concerns about privacy and security, as seen in the 2023 data breach at 23andMe. This breach exposed sensitive information from nearly 7 million users, including ancestry data and personal details, highlighting the risks of data misuse and inadequate safeguards. That gives artificial intelligence quite a bad rep, especially when you consider how many data breaches there have been in other industries that we discussed in previous assignments such as the T-Mobile breaches. As AI continues to revolutionize healthcare—enhancing diagnostics, personalizing treatments, and streamlining administrative tasks—making sure the data stays protected is key. Addressing these vulnerabilities, alongside preventing biases in AI systems, will be critical to maintaining trust and equity in healthcare. Balancing innovation with ethical responsibility will define the role of AI in shaping the future of medicine.

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The societal impact of AI in healthcare is immense, bringing many benefits while still posing significant challenges. AI enhances health outcomes by streamlining diagnostics, optimizing treatments, and improving efficiency in care delivery. Its ability to automate administrative tasks and accelerate processes reduces costs, making quality healthcare more accessible. However, these advancements also raise concerns. The reliance on AI systems necessitates robust data privacy safeguards to protect sensitive patient information, a critical issue in today’s data-driven world. Additionally, while AI reduces workloads, it has the potential to displace certain roles in healthcare, leading to economic and social adjustments. Not only that, but with the rise in AI in educational fields, any people that enter the workforce may be too reliant on AI and may not reach the level of specialization in medical fields as in the past. I’ve seen this firsthand where some peers need to google every single thing, no longer thinking for themselves. Equity is another crucial factor—ensuring that AI-driven advancements benefit diverse populations rather than enhancing existing inequality. As AI continues to shape healthcare, its societal impact will require careful management to balance innovation with fairness and inclusivity. This balance will determine how effectively AI transforms healthcare while maintaining trust and accessibility for all.

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I found this project very insightful considering this is an industry, as I mentioned previously,  I am aspiring to work in. The research itself was not too difficult but it did take me a while to narrow down which applications I wanted to focus on so they did not overlap too much and I didn’t constantly repeat the same benefits or concerns when it comes to AI in the healthcare workplace. I ended up deciding on concise information assessment, personalized care, and faster drug development as those were the most interesting topics that I came across and in some cases a personal connection of how this technology could have helped me when I needed it during my visits to the hospital. The ethical and societal portions were similar to what I discussed in previous assignments especially when it comes to the big concern of AI: data privacy and breaches. Overall, this was a very interesting dive into what could be my future.

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As an aspiring healthcare worker, it seemed fitting that I choose this industry to discuss. Although I do not know exactly what career I want in the industry, no matter what I choose, AI will have a purpose there from radiology to sonography and to scribing, which are some examples that I will discuss later. AI is, in general, known for making things easier for us and that remains true with its ability to use pattern recognition and fast processing speeds to get patient results faster, personalizing the experience depending on the patient needs and genetic history, and even developing new drugs that don’t take 10-15 years to create and test. On the societal aspect, AI can help make care more accessible to those who need it and cannot see a doctor. However, as is the case whenever AI comes up, we also need to discuss the limitations and cons. The most important ones that are a cause for concern are the data privacy and potential breaches of sensitive information, made even more sensitive when it’s a patient's medical history. There is also the concern of employment cuts if AI is simply more efficient at doing the job than people are as well as concerns over the quality of the incoming workforce if it is too reliant on AI and the internet. All of that aside, I strongly believe that using AI in this industry will make doctors more efficient and spend more time with patients instead of wasting precious time on writing reports or analyzing image scans for hours.