The healthcare industry faces persistent challenges, including staffing shortages, increased patient demand, and the ongoing impact of the recent global health crises. In response, there is growing enthusiasm for technologies, especially artificial intelligence (AI)—to help alleviate these burdens.
AI applications in healthcare are rapidly advancing, offering powerful solutions to streamline complex processes. For example:
- AI-powered scheduling systems reduce patient wait times by optimizing appointment bookings and resource allocation.
- Automated documentation tools use natural language processing to transcribe and summarize patient interactions, freeing clinicians to spend more time on direct patient care.
- Predictive analytics help providers anticipate patient needs, manage staffing, and identify at-risk populations for early intervention.
- AI-driven chatbots and virtual assistants enhance patient engagement by providing personalized information, answering questions, and supporting self-service options.
- Medical imaging analysis leverages AI to detect subtle patterns in scans, supporting earlier and more accurate diagnoses.
The value of AI in healthcare is already recognized: in 2022, the global market for AI-driven healthcare solutions was estimated at $800 million, with projections reaching $17.2 billion by 2032. As adoption accelerates, targeted applications—such as administrative automation, clinical decision support, and patient engagement—are attracting significant investment. These innovations are transforming how healthcare organizations deliver care, manage operations, and drive new levels of efficiency and innovation.
What makes AI ‘generative’?
Artificial intelligence (AI) has reached new heights of prominence in recent years, but the technology is older than its recent surge in popularity. “Traditional” AI and machine learning leverage algorithms to uncover patterns in data. GenAI builds on and extrapolates these technologies, creating additional content based on what it has “learned.” This content has many formats, including video, audio, and text.
GenAI chatbots can communicate in natural, conversational language. The technology that underlies popular GenAI chatbots is a Large Language Model (LLM), which trains bots on massive amounts of text to generate responses to user prompts.
Administrative applications of GenAI
In much the same way as it does in other industries, GenAI can help to untangle and simplify the processes by which patients, providers, and staff interact with healthcare systems. By reducing administrative burden, GenAI applications ease pressure on medical professionals, making room for more human-focused care and boosting patient engagement by enriching the patient experience.
Documentation assistance
Healthcare records represent a vital resource for both individual patient care and population-level insights—but only if the information in them is accurate and consistent. Detailed documentation requires time and attention, but administrative burdens cut into the time clinicians can spend with patients. GenAI’s natural language processing capabilities alleviate some of this burden by transcribing and summarising patient interactions, conducting patient questionnaires, and even suggesting potential diagnoses. The result is more consistent and faster documentation, allowing providers to focus on connecting with patients.
At the same time, GenAI offers similar benefits to the financial arm of the healthcare industry, automating documentation and communication, data entry, coding, and billing. Maintaining more accurate and reliable records leads to improved data privacy compliance, fewer insurance claim denials, and a significantly smoother Revenue Cycle Management (RCM) process overall.
Read more: Adopting Microsoft Copilot AI in finance transforms day-to-day operations
Patient engagement
Personalization is the watchword of modern customer interactions. As the consumer model of healthcare gains prominence, patients expect treatment and interactions tailored to their individual histories, preferences, and needs. GenAI is perfectly positioned to process patient information and deliver personalized content and communications.
Moreover, GenAI agents can grant patients greater agency and increase engagement through expanded, natural-language self-service options. These same agents can also serve as assistants to human service agents in healthcare industry contact centers, summarizing patient histories, surfacing the most relevant information, and suggesting personalized responses or courses of action in real time.
Read more: How AI is shaping the future of customer experience
Clinical applications of GenAI in healthcare
GenAI relies on high-quality training data, and in a healthcare setting, patient data privacy is a chief concern. However, while balancing this core consideration, GenAI can also extract valuable, even revolutionary, insights from large-scale analytics, identifying patterns that would otherwise go unnoticed.
Precisely tailored treatment
Leveraging a complete, 360-degree view of a patient’s history and current health, GenAI tools can craft targeted treatment plans for optimum effect—including drugs that interact with specific genes and biological mechanisms to maximize positive outcomes and minimize side effects.
Extrapolating from patient data, GenAI systems can also run predictive models to gauge individual responses to medication or generate synthetic patient data against which to evaluate treatment options for rare conditions with few real-world data sources.
Population health
Large-scale data analysis and prediction are crucial for developing informed community health initiatives. With GenAI, healthcare researchers and providers can identify health risks and model potential outcomes. In addition, GenAI supports research into social determinants of health, highlighting external factors and illuminating trends that can impact health outcomes for specific populations.
Based on these analyses, GenAI tools can guide the development of targeted communications and intervention methods, such as:
- Customized community messaging
- Disease forecasting
- Outbreak identification
- Real-time health monitoring
- Remote treatment options
- Risk assessment
Medical imaging
Comprehensive medical scans are key to accurate diagnosis and treatment. GenAI systems can integrate multiple views and scan types to develop a holistic view of a patient’s condition and support targeted treatment efforts.
Moreover, GenAI can enhance images and assist with their interpretation. GenAI tools can identify subtle trends and bring them to the attention of a trained provider, resulting in earlier and more accurate disease detection. These tools can also leverage this information to create realistic, synthetic images to educate and provide practice for medical students and other professionals.
Read more: Is AI a friend or foe? AI adoption in the age of technology anxiety
Explore new frontiers of healthcare with GenAI and CBTS.
The spread of GenAI has enormous potential for the healthcare industry, but adoption depends on more than the technology’s accuracy or efficiency. Trust is a critical component, particularly when dealing with information as personal and sensitive as health data. Both patients and healthcare professionals see opportunities, and both are willing to incorporate GenAI tools into the care experience—but that willingness depends on their confidence in the quality and security of the data on which they are built.
With decades of experience helping healthcare organizations modernize their IT environments to meet the ever-changing needs of their business, as well as a proven track record of success with building data strategies for AI, CBTS is the partner to help you make the leap to AI readiness.
Contact CBTS today to begin exploring the possibilities of GenAI for your healthcare enterprise.
