AI is already part of our everyday lives, changing how we perform simple tasks and go about our work. But when it comes to healthcare and medicine, it’s a different ball game. The healthcare industry is complex, costly, and full of moving parts. For a long time, we didn’t have technology powerful enough to ease that burden. Until now.
With the emergence of agentic AI in healthcare, there’s real potential for how care is delivered. Unlike traditional artificial intelligence, this new wave of autonomous AI is about more than just responding to prompts. Using sophisticated reasoning and planning, it can act independently and learn from experience. That means it can support real-time decisions, carry out tasks on its own, and improve outcomes for healthcare professionals. While adoption is still in its early stages, with just 1% of enterprise applications using agentic AI in 2024, Gartner predicts that number will surge to 33% by 2028.
As digital maturity grows and the technology becomes more widespread, we’ll see Agentic AI make a meaningful impact across the industry.
While generative AI focuses on creating, agentic AI is built to understand and act. It operates through multiple AI agents that leverage large language models (LLMs) and advanced reasoning. What sets it apart is its ability to make decisions, set goals, and take steps to achieve them.
Take a healthcare example. If tasked with triaging a patient’s clinical question, agentic AI doesn’t just stop at analyzing the data. It might use generative AI to summarize the patient’s medical history, but then it applies agentic capabilities to decide who in the care team handles the case and routes it their way.
Agentic AI takes what generative AI produces and turns it into action, just like a human would. Only faster, more reliably, and at scale. For a deeper look at where healthcare AI is headed next, check out AI Predictions 2025: Big Tech Investments Accelerating Innovation.
Agentic AI personalizes treatment by continuously analyzing patient-specific data. By analyzing genetic profiles, medical records, and even live health data, agentic AI enables doctors to recommend targeted therapies, like chemotherapy, radiation, or surgery, based on what will work best for that individual. One recent study found that AI-personalized treatments improved cancer patient survival rates by 20% compared to standard care, and extended progression-free periods by 15%.
Agentic AI detects early signs of emerging health threats by analyzing public health, social, and clinical data in real time, such as sudden spikes in symptom-related search terms or visits to the ER. Pandemics can’t be curbed by quick fixes alone. They require early warnings and real-time action. By continuously monitoring live health signals and identifying unusual patterns, agentic AI enables earlier outbreak detection and response. When paired with predictive analytics in medicine, it can pinpoint hotspots and accelerate vaccine development by narrowing down the most promising candidates.
Bringing a new drug to market can take years. The process is expensive and involves immense research. Agentic AI helps speed up the process by running advanced simulations that show how different compounds behave in virtual patient models, including how they might affect the body or trigger side effects. This early insight helps researchers prepare for clinical trials sooner and shortens the time it takes to deliver treatments to patients.
Admin work is the glue that holds healthcare operations together, but it often pulls clinicians away from actual patient care. Agentic AI reduces this administrative burden by acting as a digital assistant to healthcare providers. Without any human input, it can transcribe doctor-patient conversations into clinical notes, schedule follow-ups, and retrieve relevant patient information during consultations.
According to Gartner’s “Top Strategic Technology Trends for 2025,” agentic AI is one of the most transformative forces shaping enterprise technology. In healthcare, a well-planned strategy is necessary for agentic AI’s effective implementation.
Start by identifying tasks that are resource-heavy yet offer limited value. Tasks like appointment scheduling, prescription renewals, and patient intake often hinder productivity and can be performed through automation. Pinpointing these bottlenecks early enables you to focus AI where it can have the greatest impact.
Be specific about what you aim to achieve. Whether it's reducing wait times or improving patient satisfaction, define concrete goals and timelines. A clear roadmap will help you track progress and know when you've reached success.
If patient records are spread across multiple platforms or departments, it becomes difficult for AI to operate effectively. Consolidating data into centralized information can help AI generate accurate insights and make better clinical decisions.
Partnering with an experienced AI solution provider enables stronger alignment between your AI initiatives and healthcare objectives.
Regularly assess your AI strategy, refining it based on actual outcomes, emerging technologies, and evolving healthcare needs.
What’s Next for Agentic AI in Healthcare
Going forward, agentic AI will become more adaptive, contextual, and responsive. Future systems will interpret nuance, grasp the medical situation, and respond intelligently and sensitively, much like a skilled healthcare professional would.
Agentic AI can form a “power duo” with doctors and specialists, working alongside them to support clinical decisions in complex cases. While agentic AI can analyze large volumes of patient data, surface relevant insights, and recommend evidence-based treatment plans, clinicians bring the human expertise and ethical oversight that AI can’t replicate. With the global healthcare AI market projected to reach $187 billion by 2030, expect a sharp rise in patient-focused AI applications across the industry.
The integration of agentic AI with IoT devices and wearables will become helpful in providing continuous, proactive care. Smart devices will collect real-time biometric data such as heart and respiratory rate. Agentic AI will then process this data on the fly to detect early warning signs and trigger timely interventions, before symptoms even appear.
Although still emerging, agentic AI can take robotic-assisted surgery to an advanced level. By combining real-time data processing with highly calibrated control, surgeons can perform procedures with minimal invasiveness and greater accuracy, especially in complicated, high-stakes situations.
Healthcare providers are already leveraging AI to automate routine tasks like scheduling and documentation. But the real opportunity lies in delivering care that’s timely, personalized, and feels human. And that’s where agentic AI makes a difference.
As Fei-Fei Li, Professor of Computer Science at Stanford, puts it: “AI agents will transform the way we interact with technology, making it more natural and intuitive. They will enable us to have more meaningful and productive interactions with computers.”
At Ciklum, we apply Experience Engineering to every solution we build. That means combining our deep understanding of user experience, product design, and AI systems to architect, implement, and scale agentic AI solutions that genuinely help both patients and professionals.
Want to see what that looks like in practice? Get in touch with our experts for a consultation.