AI and Automation in Healthcare: Business Opportunities for 2025

AI and automation in healthcare involve utilizing tech solutions based on Artificial Intelligence (AI) to streamline time-consuming tasks, facilitate faster decision-making, and enhance patient outcomes. Think of it as providing healthcare teams with an extra set of hands and eyes that can analyze data, predict issues, and streamline operations more efficiently, eliminating the risk of manual errors. Basically, AI takes on the repetitive work so healthcare professionals can focus more on care.

Let’s see what the results of implementing AI automation algorithms based on stats are:

• Cera, a UK-based healthcare provider, uses AI to predict 80% of health deteriorations in advance, leading to a 70% reduction in hospitalizations. Their fall prevention system also cuts patient falls by 20% by predicting 83% of them in advance.
• A 2024 study by Cornell University on age-related macular degeneration (AMD) showed that using AI assistance improved diagnostic accuracy significantly. The F1-score increased by over 50% in some cases, and clinicians completed their diagnoses up to 40% faster with AI support.
• According to the Financial Times, the smart hospital market, driven by AI and robotics, is expected to hit $148 billion by 2029, as more healthcare facilities adopt tech to improve patient care.
• Another study by Financial Times states that in 2024, $800 million was invested in AI-powered tools that summarize doctor-patient conversations and cut down clinician admin work. Companies like Microsoft, Amazon, and startups like Nabla are leading this charge.

All these stats prove that AI automation for healthcare is indeed worth noticing, and you may definitely need to try implementing this approach too.

To help you better navigate the subtleties of AI automation for healthcare, we’ve selected vibrant use cases, along with examples of enterprises that successfully implemented AI automation.

Following the implementation experience of world-leading healthcare providers and medical businesses, we’ll discuss 3 key aspects AI in healthcare may help you optimize, including:

• Patient experience
• Medical staff productivity
• Patient care process optimization

Let’s break this all out in a comprehensive way to refine your healthcare business operations.

Healthcare is a deeply human interaction, where one person turns to another for help, often in vulnerable moments, expecting empathy and care. Let’s see how AI automation in healthcare can help you better bond with patients and enhance their experience.

AI-powered health assistants

Healthily (formerly Your.MD), a UK-based health tech company, built an AI-powered chatbot that acts like a digital health assistant. It helps users understand their symptoms, ask health-related questions, and get reliable, personalized insights without needing to visit a doctor right away. It’s especially helpful for people in areas where access to healthcare is limited.

Personalized treatment

K Health, working with data from Maccabi Healthcare Services and the Mayo Clinic, created an AI system that tailors health advice to the individual. By analyzing millions of real patient records, the platform gives users information about what others with similar symptoms have been diagnosed with, helping patients and doctors make better decisions, faster.

Another thing is to make your medical professional feel appreciated, reinforce them to deliver superior results, and facillitate a comfortable working environment. Healthcare AI automation can help you do this in several ways, as described below.

Medical imaging interpretation

South Australia Medical Imaging (SAMI) started using an AI tool by Annalise.ai to help radiologists read chest X-rays. Think of it like a second pair of eyes that highlights anything unusual, making the process quicker and reducing the chance of missing something important.

Real-time consulting scribe

Mass General Brigham saw a 40% drop in clinician burnout after adopting AI-powered medical scribes. These smart tools take care of the note-taking during patient visits, so doctors can spend more time talking with patients and less time typing.

Automated medical coding

Yale New Haven Health found that doctors accepted around 80% of notes generated by their AI documentation tool. That means less manual charting, fewer coding errors, and more time spent actually caring for patients instead of filling out forms.

Poorly classified workflows and administrative overhead commonly may lead to compromised treatments, diagnostic delays, and general patient dissatisfaction. See how successful medical care providers solved this issue using healthcare AI automation:

Real-time symptom analysis

Mount Sinai Health System rolled out an AI-based remote monitoring system during COVID-19 that tracks patients’ vital signs through wearables. It flags any worrying changes in real time, helping medical teams step in before things get serious. IT already helped cut hospital readmissions by 20%.

Automated care plan adjustments

UK-based Cera Care uses AI to monitor older adults and adjust care plans on the fly. If the system detects changes in a person’s condition, it can prompt caregivers to take action early. This approach has significantly reduced hospital visits and helped the NHS save both time and money.

Predictive patient risk scoring

Health Navigator partnered with a UK health group to identify people who were likely to end up in the ER. With the help of AI, they offered those patients extra coaching and support, which led to fewer emergency visits and better health outcomes overall.

Let’s proceed, as now it’s time for you to disclose key advantages of AI medical automation.

AI systems can monitor behavioral patterns and workload trends among healthcare staff to detect early signs of burnout. These tools analyze variables like time spent per task, irregular working hours, and decreased response efficiency. By flagging such indicators, you can intervene before fatigue impacts care quality. This approach strengthens staff well-being and ensures consistent performance across shifts, which is one of the unobvious yet powerful uses of AI and automation in healthcare.

AI-powered systems streamline the clinical trial enrollment process by scanning electronic health records, lab results, and genetic data to match patients with trials they qualify for. This eliminates the need for thorough manual screening and increases patient access to potentially life-changing treatments. It’s a game-changer for research teams, helping them speed up recruitment and improve trial accuracy, which is a core strength of healthcare AI automation when applied to precision medicine and research operations.

Managing inventory in hospitals is complex. Oversupply may lead to wasted resources, while shortages may cause compromised care. AI automation enables real-time monitoring of usage patterns and predicts future supply needs based on seasonal trends, appointment volumes, or local disease outbreaks. This helps avoid waste, reduce costs, and keep medical supplies on hand when demand surges. For operations teams, it’s a clear win, transforming supply chains from reactive to predictive.

In clinics where radiologists or high-end equipment are scarce, AI-powered imaging tools can support diagnostics by enhancing image quality, spotting abnormalities, and prioritizing urgent cases. These solutions work with basic imaging equipment and minimal bandwidth, enabling frontline workers to deliver accurate care where it’s needed most. This makes AI automation healthcare a critical asset in expanding access to medical diagnostics across rural or underserved communities.

Now we’ll guide you through the process of implementing healthcare AI automation, specifically in the way we do this in Cleveroad:

The first step in adopting healthcare AI automation is not jumping straight into the tech part. First, you’ll need to select a reliable and trustworthy IT partner. You need a team that truly understands clinical workflows, patient data, and healthcare regulations like HIPAA and GDPR. Make sure to thoroughly review case studies, read client feedback on platforms like Clutch or Goodfirms, and make sure they’ve delivered real results in similar environments.

At Cleveroad, we have over 13 years of experience in software delivery for the healthcare domain. Besides, we offer collaboration models that suit your needs, whether you require extra support, a dedicated team, or end-to-end delivery. With a transparent Agile process and proven track record in eHealth, we can help you reduce costs and improve efficiency, while focusing on delivering real value from your AI investment.

• Check out our recent cases for eHealth in our portfolio.

At this point, we would like to introduce an extensive video feedback from one of our clients, Breanne Butler, Project Manager at Prime Path Medtech, a medical device manufacturing company. The project we’ve collaborated on is QSuite - an efficient FDA and ISO compliant QMS that improved clients’ services for tracking certification flow and saved up to 20% in gross customers' expenditures.

We run a focused AI design sprint where our experts collaborate with your team to identify the highest-value areas for AI-driven automation, whether that’s automating appointment scheduling, optimizing care pathways, or assisting physicians through AI-based diagnostics. We assess the quality and availability of your data, determine tech feasibility, and shape a clear roadmap for how generative AI will enhance patient outcomes, reduce admin overload, and support your business objectives.

Next, we build a working prototype to validate your AI automation concept in real healthcare settings. This PoC is created within weeks and deployed on your infrastructure, whether it's cloud, on-premises, or hybrid. We apply automation tools to a limited use case, such as claims processing, and gather data on how exactly the implementation of AI will impact your business processes. This ensures your investment is grounded in tested results, not assumptions of unnecessary fancy functionality.

Once the PoC delivers positive outcomes, we expand it into a complete healthcare AI automation solution. Our engineers optimize performance, strengthen security, and ensure seamless integration with your existing systems like EHRs, CRMs, or billing platforms. We follow a structured software development life cycle that emphasizes usability, compliance, and scalability. The AI system is then launched in your production environment to support daily operations.

Implementing AI automation in healthcare can come with its own set of challenges. Below, we’ve outlined the most critical pitfalls you might face and how Cleveroad’s experts can help you navigate them effectively and reduce the risk of failure.

Medical AI automation processes massive amounts of sensitive patient data. Without strict protocols, this data can be exposed to breaches or misuse, putting organizations at legal and ethical risk. With the risk of frequent cyberattacks in healthcare, providers must comply with HIPAA, GDPR, and other regulatory standards to safeguard PHI (Protected Health Information) and facilitate top-tier healthcare data security. Encryption, secure APIs, and role-based access are all must-haves, but implementing them right requires deep technical know-how.

Cleveroad’s solution: Cleveroad ensures airtight security by building solutions in compliance with HIPAA, GDPR, FHIR, HL7, HITECH, PIPEDA, CDA, etc. Our engineers use end-to-end encryption, OAuth 2.0, PHI, data residency and retention, and secure cloud environments like AWS and Azure to protect data both in transit and at rest. Cleveroad’s DevSecOps practices embed security at every stage of development, ensuring you can safely scale your AI systems without risking patient data.

Additionally, Cleveroad is an IT vendor certified with ISO/IEC 27001:2013, meaning that we provide medical software services in alignment with leading world security practices.

AI systems can unintentionally reflect biases found in the training data, leading to unequal treatment recommendations based on race, gender, or geography. These biases impact diagnostic accuracy, treatment prioritization, and clinical decision-making, leading to disparities in care and outcomes.

Cleveroad’s solution: We use diverse and representative datasets when designing AI models to reduce the risk of bias. Our data science team applies fairness-aware machine learning methods and model auditing tools to ensure ethical outcomes. Real-time analytics dashboards and explainable AI models enable medical staff to interpret decisions and intervene when needed, combining algorithmic insights with human clinical judgment.

Solutions engaging AI automation for healthcare often require a high upfront investment in infrastructure, software, medical staff training, and integration with existing systems. Smaller clinics and hospitals may struggle with cost of AI in healthcare, especially when ongoing maintenance, model retraining, and updates are factored in.

Cleveroad’s solution: Cleveroad optimizes cost-efficiency by offering Proof-of-Concept (PoC) development using modular system architectures. A PoC enables the deployment of a small-scale solution to test the real-world performance of the software, before committing to full-scale implementation. This approach allows for data-driven validation and risk reduction prior to broader rollout. We also use cloud-based infrastructures (e.g., AWS, GCP) and open-source ML frameworks (like TensorFlow and PyTorch) to reduce licensing and server costs.

Even though AI tools improve speed and consistency, overreliance can lead clinicians to blindly trust machine-generated outputs. This undermines critical thinking and may compromise patient safety if the system fails or produces inaccurate results. A healthy balance between automation and human oversight is vital.

Cleveroad’s solution: We mostly focus on building AI-powered systems with human-in-the-loop design, ensuring your medical experts remain central to the decision-making process. At Cleveroad, we implement explainable AI features, intuitive UX design, and customizable rule engines that allow medics to review, override, or adjust recommendations.

Cleveroad is a healthcare software development company with 13+ years of experience in assisting medical businesses refine their care with robust software solutions. We specialize in providing various MedTech services, including custom healthcare software development, legacy systems modernization, AI/ML in healthcare, and more.

Apart from these we implement a wide range of third-party integrations for healthcare solutions, including Kareo, MemoraHealth, Truepill, DailyMed, Twilio, DrChrono, Stripe, Eligible, etc.

We deliver various types of medical software from scratch, including EHR/EMR, Telemedicine platforms, e-prescription solutions, medical billing software, Remote Patient Monitoring(RPM), medical imaging and visualization software, etc.

Here’s what benefits you’ll obtain by collaborating with us:

• Certified partner. Cleveroad holds ISO/IEC 27001:2013 for information security and ISO 9001:2015 for quality management, key certifications for secure and compliant healthcare solutions.
• End-to-end development. Cleveroad delivers end-to-end AI automation in healthcare, streamlining the entire process, from planning and evaluating tasks to creating, training, and integrating AI models into medical software.
• Expert healthcare-focused development team. You’ll access 250+ skilled in-house professionals, 75% of whom are seniors and middle-level specialists. Our cross-functional team knows how to handle the complexity of healthcare apps, from medical APIs to EHR integrations.
• Flexible collaboration. You can choose the most suitable model for your healthcare organization: IT staff augmentation boosts your team with niche AI expertise, dedicated teams handle full-cycle development with domain focus, and project-based cooperation ensures end-to-end delivery under fixed scope.

To prove our experience in Healthcare software development, we’d like to represent our recent case - IoT-based system for monitoring EKG and blood oxygen level.

A US-based medical device manufacturer turned to Cleveroad to bring its IoT-powered ECG monitors and pulse oximeters into the digital space. The company aimed to build a mobile app that would let users track heart and oxygen levels in real-time and needed a robust e-commerce platform to sell devices directly to customers. Alongside this, they envisioned creating a professional community space for doctors and patients to connect.

Our team tackled the project by delivering mobile apps for iOS and Android, equipped to sync seamlessly with the company’s devices via Bluetooth. To meet strict US healthcare regulations, we embedded AES-256 encryption and HIPAA-compliant data storage protocols. Beyond the app, we developed an e-commerce module and launched a WordPress-based medical forum integrated with the mobile platforms, turning the solution into a full-service digital ecosystem.

As a result, the client received a compliant, scalable mobile solution that reliably connects to their ECG and pulse oximeter devices. Doctors and patients now benefit from user-friendly, at-home health tracking, while the new e-commerce functionality and medical forum strengthened the brand’s digital presence, opened new revenue channels, and built trust within the professional community.