{"id":33469,"date":"2025-06-28T06:32:05","date_gmt":"2025-06-28T06:32:05","guid":{"rendered":""},"modified":"-0001-11-30T00:00:00","modified_gmt":"-0001-11-30T00:00:00","slug":"the-role-of-cross-functional-teams-in-successfully-deploying-ai-technologies-in-health-services-1596916","status":"publish","type":"post","link":"https:\/\/www.simbo.ai\/blog\/the-role-of-cross-functional-teams-in-successfully-deploying-ai-technologies-in-health-services-1596916\/","title":{"rendered":"The Role of Cross-Functional Teams in Successfully Deploying AI Technologies in Health Services"},"content":{"rendered":"

AI projects in healthcare need attention on different parts of an organization\u2014people, processes, technology, and data. A recent study by Victoria Uren and John S. Edwards added Data as a fourth key part to the usual People, Processes, and Technology framework. This approach helps healthcare groups get ready for AI by focusing not just on new technology but also on the people and how work is done.<\/p>\n

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When AI is used in areas like customer care, phone services, or claims processing, different teams in a healthcare provider must work together. For example, IT teams know the technology well, but they rely on administrative staff who interact with patients daily and on operations leaders who understand how work is divided and scheduled.<\/p>\n

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If these groups don\u2019t work together, AI projects can fail because they don\u2019t fit with existing work, lack good data, or don\u2019t give users enough training and help. Cross-functional teams improve communication, choose the most useful AI projects, and keep AI plans flexible so changes can be made when needed.<\/p>\n

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The Current State of AI Adoption in U.S. Healthcare Customer Service<\/h2>\n

A 2023 McKinsey survey showed that 45% of healthcare operations leaders see using AI as a top goal, up 17 points from 2021. Many healthcare groups want AI to reduce work like answering phone calls and handling claims.<\/p>\n

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However, only about 10% of calls handled by AI systems get fully resolved without needing a live agent afterward. This shows AI needs to work better with human help, which cross-functional teams support. These teams improve AI by testing, changing conversations based on results, and adding feedback from people.<\/p>\n

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Healthcare workers often spend 20 to 30% of their time on tasks like looking for information or doing repetitive jobs. AI can help save this time by automating simple tasks. But this only works if administrators and office managers who know daily routines are part of the process.<\/p>\n

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Cross-Functional Collaboration: Bridging Technical and Business Divides<\/h2>\n

Bringing AI into healthcare is not just about technology. It also involves behavior and how the organization works. A Deloitte report said that culture is one of the biggest barriers to AI success. Many healthcare groups still use old ways that resist change, and AI projects often lack strong support from leaders or follow-up after launch.<\/p>\n

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Cross-functional teams connect IT departments, which build AI tools, with clinical and administrative teams, who use them with patients. This makes sure AI tools work well in real life and don\u2019t interrupt patient care.<\/p>\n

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For example, feedback from front-desk workers helps improve AI phone systems to recognize common patient questions and route calls correctly. Also, billing and claims experts help guide AI that supports claims, making these processes up to 30% more efficient in some tests.<\/p>\n

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Cross-functional teams also help set rules to manage risks with AI. They monitor AI, check that it is used fairly, and make sure it follows health laws like HIPAA.<\/p>\n

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HIPAA-Compliant Voice AI Agents<\/h4>\n

SimboConnect AI Phone Agent encrypts every call end-to-end – zero compliance worries.<\/p>\n

Secure Your Meeting <\/a>\n <\/div>\n<\/div>\n

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Data Readiness and Its Role in AI Success<\/h2>\n

Data readiness is a big challenge for AI in healthcare. AI models need access to good, relevant, and protected data to work well. This includes patient charts, call records, claims data, and scheduling details. All these must be managed carefully to keep privacy and accuracy.<\/p>\n

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Uren and Edwards said that strong data management is needed along with new technology. Many health providers still use old IT systems, which makes data sharing and flow harder for AI tools.<\/p>\n

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Cross-functional teams bring together those who provide data, data analysts, and IT staff to clean, organize, and manage data sets. Without this teamwork, AI may perform poorly or cause mistakes that affect patient experience.<\/p>\n

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AI Call Assistant Manages On-Call Schedules<\/h4>\n

SimboConnect replaces spreadsheets with drag-and-drop calendars and AI alerts.<\/p>\n

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AI and Workflow Automations in Healthcare<\/h2>\n

AI helps a lot when it automates daily office work. It can take over tasks like scheduling appointments, patient registration, phone answering, and claims processing. This cuts down the workload for staff, so they can focus more on patient care.<\/p>\n

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Simbo AI is a company that uses AI to automate phone services in healthcare. Their AI systems answer patient questions fast. This lets human workers spend more time on harder tasks. AI also helps schedule better and route calls more efficiently, improving workflow.<\/p>\n

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Studies show automation can raise efficiency a lot. For example:<\/p>\n