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Northfield Today
By the People, for the People
Healthcare Needs AI Platforms, Not Just Task Automation
Experts say healthcare organizations must shift from isolated AI tools to operational AI platforms that orchestrate end-to-end processes.
Published on Feb. 21, 2026
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Healthcare organizations are rapidly investing in artificial intelligence, but a critical gap remains: most are still automating tasks, not transforming workflows. This disconnect is hindering the potential for AI to deliver the promised scale and impact. The focus is shifting from isolated AI tools to operational AI platforms that orchestrate end-to-end processes, moving beyond just speeding up individual tasks.
Why it matters
Simply speeding up individual tasks within the existing reactive healthcare model doesn't address the underlying inefficiencies. The true potential of AI lies in system-level execution - the ability to run workflows from start to finish, even when faced with unexpected hurdles or incomplete data. This requires AI to be embedded into the core infrastructure of a health system, not bolted on as an add-on.
The details
Platforms like Luma's Operational AI are demonstrating this shift, running workflows end-to-end across areas like access, engagement, intake, and payment capture. This coordinated approach saves staff hours and integrates directly with existing Electronic Health Records (EHR) and other systems. Healthcare's digital evolution has progressed from improving access points to layering automation onto existing manual processes, and the emerging phase is a fundamental architectural redesign of how work flows across the entire healthcare journey.
- Healthcare organizations have been rapidly investing in AI over the past several years.
The players
Luma
A provider of operational AI platforms that orchestrate end-to-end healthcare workflows.
Northfield Hospital + Clinics
A healthcare system that has exemplified the architectural approach to AI integration, building a digital front door and applying AI to high-friction workflows.
What’s next
Healthcare organizations will need to carefully plan and execute on the architectural integration of AI into their core infrastructure in the coming years to unlock the full potential of the technology.
The takeaway
The future of AI in healthcare lies in operational platforms that can orchestrate end-to-end workflows, not just automate individual tasks. This shift requires treating AI as infrastructure, not just a feature, and fundamentally redesigning how work flows across the entire healthcare journey.
