How AI Agents Are Rewiring Corporate DNA in Healthcare
Key Takeaways:
- Agentic AI is enabling new levels of efficiency and insight in healthcare
- Patients can benefit from better outcomes, and more personalized, continuous treatment
- Embedding AI processes often requires cultural change within healthcare organizations
- Third-party expertise is key to a successful agentic AI implementation
Healthcare AI is booming all over the world. The American market for healthcare AI alone is expected to grow from less than $12 million in 2023 to over $100 million by 2030.
Much of this growth will be driven by agentic AI implementation, which will take AI use beyond simple task automation towards more autonomous processes that don’t need human intervention. This will create major changes in the organization and culture of healthcare bodies, and this blog explores what that means in practice.
The Ripple Effect: How AI Transformation Starts Small But Spreads Organization-Wide
The impact of general AI on healthcare operations has already been substantial. In the United Kingdom, pilots of AI-driven scheduling systems by the National Health Service have reduced missed appointment rates by as much as 30%. Not only has this allowed thousands more patients to receive consultations, but it has also generated annual savings of up to £27.5 million per trust (NHS bodies overseeing care in a local area).
As AI functions have become more embedded in regular operations, there have been a number of knock-on effects in other areas, as more departments come to realise what AI can do for them:
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Physicians can use AI to take care of clinical documentation to save time |
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IT can expand automation across departments with standardized communication and consistent note formats |
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Administrators can expand appointment scheduling capabilities across billing and pharmacy functions, increasing their productivity and improving patient relations |
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Pharmacies and nursing can use shared data insights and medication dosing algorithms to upskill staff, improve patient safety and enhance collaboration |
In time, AI-driven insights in one area will increasingly influence decision-making processes in others. For example, diagnostic discoveries can automatically generate changes to scheduling, resource planning and care pathways, so that patient care is retuned to changing medical needs. Eventually, these AI-generated workflows will become the norm in healthcare, and will be treated as the benchmark.
How AI is Redefining Roles and Relationships in Healthcare
The next step of this integration process will be agentic AI implementation. So far, only 35% of companies across all sectors have implemented AI agents, and only 17% have done so across most of their workflows. The ability to use AI in ways that require little or no human oversight will naturally create more value and productivity in healthcare, and so will be a major growth area in the months and years ahead.
AI agents will redefine some healthcare job roles, and also create new ones entirely. Nurses will become AI data interpreters and doctors will become AI-empowered diagnosticians. But just as importantly, there will also be an AI-driven cultural change in the doctor-patient relationship, as care can move beyond the traditional appointment-based model to a more continuous, personalized set-up.
It won’t be long until doctor-patient relationships all over the world are based around:
Beyond Technical Implementation: AI-Driven Cultural Change in Healthcare
As agentic AI starts to be considered more of a trusted decision-making partner, both clinicians and patients will feel more comfortable with the technology. Over time, more and more people will become accustomed to shared decision-making, where AI is the ever-present consultant that can inform treatment, but doesn’t replace the human empathy which is essential in any healthcare setting.
As an example of how embedded AI can be in healthcare culture, the Cleveland Clinic in the US state of Ohio has deployed a Virtual Command Center, in which AI is fully integrated across several functions. All relevant stakeholders can view current status and future forecasts across waiting times, bed availability, patient admissions and staffing levels. This allows all staff within the facility to make better decisions around their day-to-day operations, and ensure more patients are able to be treated.
In Summary: The Methodology Behind AI Agents in Healthcare
It’s clear that there is huge, transformative potential around agentic AI implementation in healthcare. But those organizations that have already made progress with agentic AI didn’t do so overnight: it requires careful planning and expert guidance across technological deployment and AI-driven cultural change.
This level of expertise often requires third-party support, and it’s where we at Ciklum, with our proven track record with AI in healthcare, are ideally placed to help. Our end-to-end implementation strategy, from initial concept through scaling to center-of-excellence capability, means we can help you strike the right balance between AI-driven efficiency and empathetic, human-centered care.
To find out more, read our eBook on deploying agentic AI at scale, or get in touch with the Ciklum team.
