Use case type

Healthcare workflow automation

This category uses AI to streamline administrative and coordination tasks in healthcare settings, such as scheduling, documentation, and task routing. It helps reduce manual effort and improve staff efficiency.

Use cases

38

Examples

38

Industries

4

Timeline

22 mo

Data updated 1 day ago

Adoption over time

Documented cases per month

By case publish month · completed months only

27 cases documented across 37 months (Jul 23 – Jul 26), peaking at 5 in May 2026.

4 earlier cases before Jul 23 not shown

Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.

Company examples

Use cases of this type

10 shown from 38 use cases

Valant Medical Solutions, Inc. provides electronic health record software to behavioral health providers and practices.To add enhanced telehealth capabilities and improve patient communication, the company built a new telehealth solution for more than 2,500 behavioral health practices using AWS Communication Developer Services, Amazon Chime SDK, Amazon Pinpoint, and Amazon Simple Email Service (SES).The solution added voice, video, messaging, email, SMS, automated reminders, and customized robocall workflows, and integrated with Valant's EHR and practice management software.

Valant Medical Solutions, Inc.Healthcare

ViClinic, a healthcare technology company, set out to streamline end-to-end care workflows across intake, documentation, authorization, care coordination, pre-authorization, coding, billing, and follow-up.The company wanted to reduce administrative burden and avoid delayed or denied claims without compromising clinical decision-making or compliance.IBM watsonx Orchestrate was used to embed governed agentic AI into healthcare workflows with human oversight and auditability.

ViClinicHealthcare

Vital, a US healthcare company, uses Amazon Bedrock and Amazon Nova to run generative AI workflows that improve patient communication and help surface high-risk findings across clinical records.The company migrated from a more complex multi-cloud setup to AWS to reduce cost, improve scalability, and support HIPAA-aligned healthcare workloads.

The Keck School of Medicine of USC, part of the University of Southern California, faced slow, manual, and error-prone Medicare Coverage Analysis (MCA) processes causing delays in clinical trial activation and completion.The school collaborated with Google Cloud and partner Pluto7 to implement machine learning models that automated complex decision-making workflows in clinical trial budgeting and billing.The ML system reads standard care guidelines and predicts billing designations with 70-90% accuracy, accelerating the MCA budgeting process from days to milliseconds.This automation shortened clinical trial activation times by 50% and improved efficiency in managing approximately 200 annual clinical trials, freeing up staff and budget.The use of Google Cloud serverless infrastructure and BigQuery enables scalable analytics and ongoing enhancements with ML.

Keck School of Medicine of USCHealthcare

MultiScale Health Networks uses Google Cloud to power MultiScale Hive, a real-time health system for healthcare providers.The platform helps clinicians communicate more securely, collaborate on EHR and health operations data, and act on patient issues in real time.

MultiScale Health NetworksHealthcare

Availity, a U.S.-based healthcare technology company, used Amazon Q Developer, Amazon Q Business, and Amazon Bedrock to streamline software development workflows and reduce routine engineering overhead.The company built specialized generative AI bots integrated into development tools and chat systems to automate documentation, security assessment, release readiness, and risk analysis.

AvailityHealthcare

Compunnel Digital, a healthcare technology solutions provider, has implemented intelligent automation solutions using Microsoft technologies to enhance healthcare administrative efficiency and patient outcomes.They deploy AI and automation solutions, including automated appointment scheduling, claims processing, electronic health record management, predictive analytics, virtual health assistants, drug inventory management, staff scheduling, fraud detection, and remote patient monitoring.The solutions integrate Microsoft Power Automate, Azure AI Health Bot, and AI-driven analytics to automate healthcare workflows effectively.

CompunnelHealthcare

SERGAS, implemented by NTT DATA, uses Innovatrial built on Research and Engineering Studio (RES) on AWS to centralize structured and unstructured clinical and biomedical data for clinical trial operations.The platform uses Amazon S3, Amazon EC2, Amazon Managed Blockchain, AWS IAM, and Amazon QuickSight, plus customer machine learning models for NLP-driven cohort identification and workflow automation.Researchers can translate natural-language inclusion/exclusion criteria into searchable queries to identify candidate cohorts in minutes instead of weeks, while dashboards and alerts improve visibility and regulatory tracking.

Servizo Galego de Saúde (SERGAS)Healthcare

Omada Health launched an AI-powered nutrition experience on AWS to provide real-time, evidence-based guidance and motivational interviewing to members.The solution used a fine-tuned Llama 3.1 8B model on Amazon SageMaker AI, with Amazon S3 for training data and artifacts and clinician review for safety and quality.

Omada HealthHealthcare

Microsoft and UiPath collaborated to automate healthcare workflows using Azure AI Foundry agents integrated with the UiPath Maestro platform.The solution automates the detection of incidental findings in radiology reports, aggregates patient history, and generates actionable reports quickly for clinicians.This integration reduces administrative burdens on clinicians and operational risks, improving the speed and quality of patient care.

Common questions

Healthcare workflow automation at a glance

How many healthcare workflow automation use cases are documented?
The AI Use Case Hub documents 38 real healthcare workflow automation deployments across 4 industries, with 38 detailed company examples you can browse.
Which industries adopt healthcare workflow automation the most?
Healthcare workflow automation is most common in Healthcare (89%), Pharma (5%) and Professional Services (3%).
Which countries lead in healthcare workflow automation?
United States leads documented healthcare workflow automation deployments, followed by Switzerland and United Kingdom.
What technologies are used for healthcare workflow automation?
Teams most often build healthcare workflow automation with Azure, Microsoft Teams and Azure OpenAI.
What AI capabilities power healthcare workflow automation?
Across the documented deployments, the most common capability patterns are Agent (18%), Copilot (8%) and Multi-agent (5%).
What results do companies report from healthcare workflow automation?
Across the 38 deployments reporting outcomes, companies most often cite speed & agility (63%), customer experience & trust (63%) and new product / capability (53%). Where impact is quantified, the strongest evidence is in time & speed: a median +23.8% across 2 reported metrics.