6 Ways AI Can Help Healthcare Providers Cut Costs, Enhance Care and Improve Patient Satisfaction

After working with healthcare companies for over a decade, it became clear that the healthcare industry needed something else. Something to help it improve, prosper, help the healthcare providers do their job better, and most importantly, make it more affordable and available to all.

That special something is here. It’s AI—and it’s changing the industry right before our eyes at a rapid rate. If you’re looking to churn out AI-driven patient interaction and care that runs 24/7 x 365 when they need it and whenever you want to provide it, now is the time.

Soon, seeking medical assistance in a doctor’s office will feel outdated. The present and future of healthcare is artificial intelligence. It can no longer be ignored.

This shift to AI will help speed up healthcare innovation— such as less invasive surgeries and the development of new pharmaceuticals. And the technology will do this while saving considerable costs in the process.

It’s important to remember AI’s promotion is not a health provider’s demotion. In contrast, it’s an augmentation of the entire health space. No one will be replaced. Only quality care stands apart, and AI is here to help healthcare providers do that.

Table of Contents

  • Why the Healthcare Industry Needs AI
  • Chatbots: 24/7 AI-driven Conversations and Care 
  • Vector Databases to Help Patients and Providers 
  • Prevention and Wellness Through Predictive Analysis 
  • Accelerating Novel Treatment and Diagnostic Development
  • Empowering the Healthcare Workforce 
  • Telehealth— A Future in Healthcare
  • Embracing AI to Help Provide Healthcare For All

Why The Healthcare Industry Needs AI

For 30 years, robots have been used in healthcare, ranging from basic laboratory robots to highly complex surgical robots. But they were costly. Previously, in healthcare, innovation was meant to be expensive. But AI is altering this, making innovations more cost-effective and inclusive. Big and small healthcare companies and individual healthcare practitioners can now implement AI to boost nearly everything, including care and better health services. 

Common Healthcare Challenges

Many healthcare professional’s challenges stem from fragmented EHR systems (Electronic Health Records) and interoperability issues, causing inefficiency, high costs, and a negative patient experience. Here are a few examples:

  • Dispersed data sources can often hinder a comprehensive patient view.
  • Massive amounts of data from various sources must be promptly integrated, cleaned up, transformed, and stored to extract actionable insights.
  • Challenges understanding patients because of a lack of data-driven culture, hindering practitioner’s ability to provide timely and personalized care.

Improving Patient Care & Saving Costs

AI can absorb infinite data to provide us with these seamless services: 

  • Chatbots for faster, 24/7 patient care.
  • Better health outcomes and personalized treatment plans.
  • Curate health insights from databases for individuals and populations.
  • The development of new and enhanced treatments and cures.
  • Predicting disease outbreaks and making more accurate and faster decisions.
  • Ensuring scalability of innovative workflows for healthcare professionals.
  • Increasing accessibility and affordability via remote care and inexpensive diagnostic and healthcare tools.
  • Improving customer acquisition, retention, and referral marketing = higher revenue for healthcare providers.

Examples of AI in Healthcare

Source: PwC

AI is providing robust solutions to help healthcare systems worldwide deal with rising costs and an aging population— enhancing patient outcomes, lowering costs, and boosting efficiency and innovations. 

Here are six examples of AI-driven technologies reshaping the healthcare industry for the better.

1- Chatbots: 24 x 7 AI-driven Conversation & Care

Need to check up on patients or provide after-hour care? AI chatbots can do that. Need to follow up with that patient for the appointment? An AI chatbot can do that. Want to install seamless care navigation for long-term conditions? AI chatbots can do that, too.

AI models can be trained to respond to a given context. In this case, that context could be a treatment plan provided by a nurse or physician. The model can be trained only to give responses relevant to the provided treatment plan and any questions asked about that plan.

An AI model can also suggest that a follow-up with a doctor would be beneficial. AI-powered chatbots (or voice assistants) for healthcare have shown to be incredibly effective. Here’s how.

Tasks Chatbots Speed Up

  • Patient consultations and responses to frequently asked questions (FAQs).
  • Online symptom-checking conversations with initial diagnosis based on anamnesis.
  • Voice-activated medical assistants for medication tracking and telemedicine solutions.
  • Providing aftercare and tracking the execution of a patient’s treatment plan.
Tateeda's Health Chatbot Lisa


AI helped K Health’s Doctors treat 3 Million People

K Health is a telemedicine brand that uses AI to offer reasonably priced doctor consultations via a mobile application. In less than five minutes, the average patient responds to 25 chatbot questions from K Health. Patients converse with a chatbot that collects crucial data, saving valuable time by eliminating the need for human clinicians to ask routine questions. 

By using a chatbot, human clinicians no longer have to speed through intake and enter information into the electronic medical record, as on the backend, they can easily see an overview and potential diagnosis. Remarkably, a study revealed that clinicians agreed with AI-recommended diagnoses 84.2% of the time, with the top-ranked AI diagnosis matching 60.9%. 

AI provides Medical Advice Dispensing for Babylon Health

Babylon Health is a state-of-the-art telemedicine app, medical subscription service, and healthbot. Its AI-powered chatbots assist in medical consultations based on the patient’s health history and common medical knowledge. Live video consultations with doctors are also available upon request. 

The UK’s National Health Service (NHS) has successfully tested Babylon Health since 2017; the chatbots carefully diagnose the patients and either give them a medical prescription or refer them to a specialist.

AI provides effective Self-Care & Training

The future of true effective care is about empowering patients not to rely solely on doctors or physicians all the time. Healthcare professionals can’t be physically or virtually available at our beck and call.

Patient-centric self-care solutions, such as healthcare mobile and web apps with interactive education and decision support, cut costs, enhance care quality, and guarantee access to healthcare independent of time, place, or staff shortage.

Woebet uses AI to provide Mental Health Support

Woebot is a chatbot and a mental health tool that provides invaluable mental health support through chatbot-patient interactions. Its AI chatbot engages users in conversations and addresses issues like stress, depression, anxiety, and addiction without the need to visit a physiatrist or mental health practitioner every time and without the fear of being judged. 



Woebot Mental Health Chatbot



The AI technology employs evidence-based techniques such as Cognitive Behavioral Therapy and Dialectical Behavior Therapy, offering daily check-ins while maintaining strict confidentiality so the user’s info can stay safe. In addition, AI and Virtual Reality (VR) platforms can help doctors and physicians get training faster and more reliably while improving all the time.

Johnson & Johnson uses AI to help Doctors & Physicians

Johnson & Johnson takes AI applications a step further with its virtual reality platform, J&J VR module. This platform aids in training orthopedic nurses, surgeons, doctors, and medical students in various surgical procedures. Deep learning tools integrated into the platform immerse clinicians in real-world scenarios, enhancing medical knowledge without physical training requirements. A game-changer. 

2- Vector Databases To Help Patients and providers

The healthcare sector produces about 30% of the healthcare generated worldwide (or 64.2 zettabytes in 2020). That calls for careful analysis and management.  AI and vector databases enhance healthcare by analyzing data from thousands of similar patients to identify treatment patterns and side effects.

This data provides valuable recommendations to healthcare providers, expanding their medical knowledge. Hence, again, AI is an enhancement, not a replacement. Let’s look at how Pfizer and Sanofi, two pharmaceutical companies, used AI and data to advance their medical research and patient care.

Pfizer’s AI Collaboration

To advance precision oncology through AI and real-world data, Pfizer partnered with Concerto HealthAI in 2019. The main objective of the collaboration was to find and develop more specialized and efficient therapeutic choices for patients with solid tumors and hematologic malignancies. 

The real-world data is called health data gathered from diverse sources outside carefully monitored clinical trials. Electronic health records (lab results, treatment schedules, radiological pictures, etc.), insurance claims, patient registries, and other information can be included in this data. 

By amalgamating Pfizer’s real-world data with AI and data science, the company pinpointed precise treatment options, redefined study designs, and sped up the completion time of the outcomes studies.

Sanofi’s AI Mission

In 2018, Sanofi started a project to develop an AI solution for automating medical literature reviews.  Before this initiative, a team of 10 individuals at Sanofi spent 30 hours each week reviewing 100 to 200 articles on Type 2 diabetes. 

This manual process led to errors and inefficiencies. But, following a three-month pilot project with the AI solution, the review time per paper was reduced from 13 minutes to just one second. The AI document processing solution employs natural language processing (NLP) to read and summarize scientific articles. 

It categorizes papers, distinguishing between observational and experimental studies, and customizes the selection of relevant papers for researchers based on their specialties and interests. Both companies’ experiences show how AI can enhance research, reduce human error, and improve healthcare by streamlining the humongous healthcare data.

3- Prevention & Wellness Using Predictive Analysis

The introduction of AI into healthcare holds immense promise, aligning with the age-old adage that “prevention is better than the cure.” With mobile phones and wearables, such as the Apple Watch and Google Fit, AI can detect illnesses early.

AI and machine learning-based algorithms identify patterns in this massive amount of data that humans cannot, improving prevention and rapid response. From heart and brain diseases to glucose monitoring for diabetes and even psychological conditions like depression and anxiety, AI can be trained to recognize early warning signs.

Using AI to Prevent Heart Attacks

ViviScount, a health tech startup, is in the advanced stages of developing a cardiac data monitoring watch using advanced hardware and smart software for early heart attack warnings. With AI at the forefront, the game-changing software will enter clinician trials with two chemotherapy clinics this year.

Diagnosing and Managing Conditions & Diseases

AI can also extend its utility to maternal health, helping detect and manage conditions like postpartum depression. Moreover, the American Cancer Society also claimed that AI enhances the diagnosis of diseases like cancer by analyzing mammograms 30 times faster and with 99% accuracy, decreasing the need for unnecessary biopsies.

Aiding Clinical Judgment & Diagnosis

A Danish AI software company conducted a test in which their deep-learning program observed emergency calls while human dispatchers interacted with callers (patients). The algorithm evaluated various factors, such as the content of the conversation, tone of voice, and background noise. With just this small amount of context, it achieved a 93% accuracy rate in detecting cardiac arrests, outperforming human dispatchers, who earned a 73% success rate.

4- Accelerating Novel Treatment & Diagnostic Development

The journey from a drug’s inception in a research laboratory to its availability to patients is typically long, averaging around 12 years. It’s a journey where only a minuscule fraction of candidate drugs advance to the crucial stages of human testing, with just 1 out of every 5,000 eventually receiving approval for use in patients. And if it fails, it will cost the company an average of $359M again to develop a new drug.

AI accelerates drug discovery by analyzing vast data sets, including patient samples, to identify potential compounds targeting disease-related proteins, expediting the development of new drugs and ultimately benefiting patients.

Speeding up Drug Discovery in Preclinical Trials

At the core of Verge Genomics is a team of 10 accomplished professionals, each an expert in their respective fields, encompassing neuroscience, applied mathematics, biostatistics, drug development, machine learning, and biophysics. 

Verge’s collective efforts have yielded an extensive gene dataset of remarkable depth and breadth. Leveraging the power of AI, Big Data, and Machine Learning, Verge Genomics accelerates the drug discovery process, particularly in the preclinical trial phase.

What does Verge’s AI-driven approach want to accomplish?

Presently, ushering a drug from discovery to market involves staggering costs. To put it into perspective, the journey from research and development to FDA approval typically demands an expenditure of approximately $1.3 billion. Moreover, this labyrinthine process can stretch to 12 years.

Powered by machine learning, Verge Genomics aimed to streamline the entire drug development trajectory. In doing so, the company has the potential to slash a substantial chunk of the colossal $2.6 billion price tag associated with bringing a single drug to market for pharmaceutical companies. 

5- Empowering The Healthcare Workforce

Automating healthcare admin tasks, AI can save $18 billion again as machines can reduce the workload on nurses and doctors, enabling them to do the hard part of medicine. The care part. 

AI automates scheduling, billing, and record-keeping, predicts patient no-shows, adjusts schedules, and forecasts payment reliability. It uses voice-to-text for orders, prescriptions, and notes. Furthermore, AI excels in structuring intricate documentation, such as the extensive 200-plus page FDA approval materials.

AI models can assist researchers by assimilating data from multiple sources and generating content according to predetermined formats. This remarkably reduces the time and effort required for document creation by hand.

Let’s look at some of the most costly and time-consuming medical practices that AI can positively impact.

AI-Assisted Robotic Surgery (Potentially Saving $40 Billion)

Robots analyze pre-op medical records and guide surgeons during procedures, reducing hospital stays by 21%. AI helps refine surgical techniques based on historical data, reducing complications. 

AI Robotics Surgery. Source - Quantum Fiber



One study involving 379 orthopedic patients found that AI-assisted robotic procedures resulted in five times fewer complications than surgeons operating alone. Advanced robots like Da Vinci enhance precision in complex surgeries.

MRI Scan cost reduction through Machine Learning

MRI scans are costly ($400 to $3,500). Machine learning, specifically “LOUPE,” reduces scan time, lowering costs and enhancing patient satisfaction. LOUPE uses convolutional neural networks to optimize undersampling patterns for more accurate reconstructions.

Image Analysis

AI accelerates image analysis by up to 1,000 times. MIT-led research enables near real-time 3D scan analysisHealthcareurgeons during procedures and potentially replacing tissue-based diagnostics. AI image analysis also supports remote healthcare and telehealth, allowing patients to send images for assessment.

Saving minutes with AI can translate to saving lives. AI’s role in healthcare extends beyond automation. AI enhances efficiency, reduces costs, and augments the capabilities of medical professionals, ultimately improving patient outcomes and revolutionizing the overall industry.

6- Telehealth— A Future in Healthcare

Telehealth or telemedicine is not just a vision; it’s a reality shaping healthcare. As healthcare moves towards telehealth and telemedicine services, AI will be the core tool for “physicians” and “the entire” medical induHealthcareprove patient care.

Virtual nursing assistants can potentially deliver annual savings of $20 billion to healthcare. Their 24/7 availability ensures constant support, from answering queries to monitoring patients and providing rapid responses— facilitating continuous communication between patients and caregivers— and reducing the likelihood of hospital readmissions or unnecessary hospital visits.

How Telehealth is Revolutionizing Healthcare 

  • We are automating health record analysis for tailored treatment.
  • Employing virtual nursing assistants with NLP.
  • Using machine learning to predict health risks.
  • Leveraging wearable devices for remote monitoring.
  • Streamlining appointment management.
  • Enhancing medical training with HIT.
  • Reducing costly hospital readmissions.

Embracing AI to Help Provide Healthcare For All

AI’s integration into healthcare is unstoppable and rapidly changing the industry. The technology offers numerous benefits, including cost reduction, improved patient care, and satisfaction. 

Healthcare startups like Limber Health have quickly reshaped aspects like physical therapy using AI. AI-driven chatbots, databases, predictive analysis, and early detection capabilities are transforming patient interactions, research, and preventive care.

AI enhances drug discovery, automates tasks for healthcare professionals, and fuels the growth of telehealth. It’s essential to remember that AI augments, not replace, healthcare providers, ensuring quality care while making healthcare more efficient and affordable. 

Despite reservations about the technology, AI promises to significantly improve the healthcare system, offering accessibility, cost-effectiveness, and patient-centered care. That has to be a win-win for everyone.