Healthcare AI Trends Set to Transform the Industry in 2024

As artificial intelligence prepares to take center stage in the coming years, organizations must gear up for a technically advanced 2024. In addition to the changes we have observed in the previous years, healthcare AI will continue to dominate and bring significant differences in health services.

However, given the uncertainty associated with AI technology, organizations may need to step back and develop AI strategies that aren’t dependent on a single platform.

With its benefits centered around better patient care, precision diagnostics, drug discovery, and virtualization of healthcare services, here are the key healthcare AI trends for 2024.

Healthcare AI Trends That Will Dominate 2024

1. Personalized and Precision Medication

As AI can now analyze a patient’s DNA for diagnosis, this information will be used to deliver personalized treatment. For a group of people with similar issues, scientists can create medicines targeted to treat issues down to the molecular level.

Hence, precision medicine, an offshoot of personalized medication, will lead to better patient outcomes. It will also ensure the optimized use of medical resources. As a result, AI will play an important role in addressing the upcoming healthcare challenges.

2. AI Copilots to Workforce Shortages

Healthcare workforce shortages is not an ideal situation to be in for any organization. As healthcare AI comes to the rescue, it will equip healthcare workers with the data and intelligence they need to deliver better care.

From assisting with in-hospital care to working as at-home caregivers, AI assistance can guide workers to improve healthcare service delivery.

In hospitals, we have technologies like DeepMind to help doctors with medical image analysis and detecting abnormalities. These AI technologies leverage healthcare datasets to find anomalies in medical images.

Similarly, for better at-home care, Babylon Health and related solutions work as AI-powered chatbots. They leverage healthcare NLP technology to work as virtual assistants and share information as and when required.

3. Electronic Health Records with AI

AI is transforming healthcare data management, upgrading their role from a static data repository to an intelligent tool. AI-based EHR operations improve access and analysis to unlock hidden insights and automate tasks.

With in-built data de-identification features, AI models can extract data from unstructured notes, reports, and images. In addition to organizing data, it helps with better clinical decision-making.

Advancements in EHR means real-time access to patient information. As AI can also detect patterns, forecasting the needs can help with proactive resource allocation and preventive care interventions.

I2b2 is developing an AI platform that can extract clinical narratives from EHR data to automatically generate reports. This is going to improve a clinician’s understanding of the patient through clear and concise summaries.

4. Adoption of Digital Twin in Hospitals

The digital twin technology will see a high-scale adoption in the coming years. It creates a virtual model of real-world systems, objects, processes, tools, etc. In healthcare settings, the digital twin technology can help identify the effectiveness of a process in different conditions.

As it simulates the implementation, we can also change the settings in the virtual world and execute the system with favorable results in the real world.

Apart from mirroring hospital systems, this technology can also create virtual human body models. This will be helpful in assessing the impact of a treatment or medication and lifestyle choices. Using the information from the virtual body, clinicians can recommend medicines and treatments in the real world and obtain accurate results.

The brain is the most complicated part of the human body to emulate with the digital twin technology. But in 2024, we may model mirroring the brain’s functions in a full-fledged digital twin model. Denmark-based Silico Medicine is in the early stages of building such a model.

5. Focus on Mental Health Support

Several technologies are focusing on the physical body, but 2024 will introduce developments in the mental health domain. Healthcare AI-driven mental health support applications will see higher adoption in 2024.

On-demand AI-powered accessible therapy solutions transform AI chatbots into empathetic virtual therapy. The conversational AI-based chatbots can provide support and guidance through cognitive behavioral therapy. Talkspace is a mobile application offering similar features as it utilizes text-based therapy sessions to provide emotional support.

There will be smart solutions to read facial expressions and voice patterns to detect potential mental health concerns. Spring Health is already working in this direction to monitor user interactions and flag signs of depression or anxiety.

In addition, some other healthcare services expected to improve are surgery with robotics, a focus on ethical AI, and new legislation aimed at the responsible use of AI technology. For healthcare organizations to successfully gauge the new developments in healthcare AI, let Shaip help you implement the solutions you need to progress.


Healthcare AI continues to develop and become better as new technologies and techniques emerge. With the potential to completely transform all types of healthcare services, meticulous implementation of AI technology is essential.

The focus on AI in healthcare will be to improve physical and mental healthcare. At Shaip, we stay on top of all the developments to help you implement the best healthcare AI has to offer. Contact us today to learn more about our capabilities and how we can help your organization become a leading example of leveraging AI to deliver advanced healthcare services.

Author Bio

health service

Vatsal Ghiya is a serial entrepreneur with more than 20 years of experience in healthcare AI software and services. He is the CEO and co-founder of Shaip, which enables the on-demand scaling of our platform, processes, and people for companies with the most demanding machine learning and artificial intelligence initiatives.


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