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The other large area of AI in healthcare has to do with the electronic medical records (EMRs) of a patient. Previously, a patient's charts were physical sheets of paper with history of the patient. Collaboration between HCPs meant literally sharing these papers, either physically or sending the file digitally. However, modern medicine has moved away from these paper systems and moved into EMRs. One benefit of applying AI and ML to these EMRs is that they are able to identify family members who are likely to suffer from hereditary disease [3]. In addition, EMR in combination with AI allows HCPs to be more efficient by allowing real‐time sharing of data for collaboration among colleagues. Since AI is used heavily to identify patterns, it could also be used to help predict patient's pharmaceutical needs and identify pharmaceutical abuse. If a patient is taking medication for a chronic ailment and on a regular basis, then the AI could identify when the patient is likely to be low and start a refill process with the pharmacy or automatically generate a request for additional refills to the HCP. This helps prevent the patient from having lapses in taking medication. In addition, if a patient were to be on a highly regulated form of medication, for instance, an opioid‐based product, AI would be able to monitor this across the board. So even if the patient is getting multiple scripts from multiple HCPs and filling them at a variety of pharmacies, if they are all connected to the patient's EMR, then the AI would be able to identify the abuse of pharmaceutical products.