AI Contact Center

The AI Contact Centercategory focuses on leveraging artificial intelligence to enhance communication, support, and operational efficiency within healthcare contact centers. Patient-Facing AI Phone Callsautomate outreach and follow-ups, handling appointment reminders, prescription refills, and patient inquiries to improve engagement and satisfaction. Payer-Facing AI Phone Callsstreamline communications between providers and payers by automating prior authorization requests, claims status inquiries, and issue resolution.

AI Conversational Chatprovides real-time support through chatbots, assisting patients or staff with frequently asked questions and routine tasks. AI Contact Center Agent Assistantsenhance agent productivity by offering real-time suggestions, knowledge retrieval, and automated documentation during calls. AI Contact Center Intelligencesolutions analyze interactions to uncover insights, optimize workflows, and improve service delivery through predictive analytics. These tools collectively reduce operational costs, enhance the customer experience, and improve the efficiency of healthcare contact centers by automating repetitive tasks and supporting informed decision-making.

Market Map
AI Contact Center Agent Assistants
Market Map
AI Contact Center Assistants are enablers for contact center agents, managers and others such as nurse triage. They are not autonomous and are built for human-in-the-loop workflows. They are intended to make existing agents or others handling contacts more efficient and/or more effective. Capabilities of these vendors include: - Call summaries or transcripts - Management of follow up tasks from phone calls - Surfacing care gaps and tasks for follow up during a contact - Surfacing relevant policies and procedures during a contact - Real time QA and feedback delivery to agents Many companies offering these solutions also offer fully autonomous solutions. Many will also have AI powered analytics and intelligence solutions.
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AI Contact Center Intelligence
Market Map
AI Contact Center Analytics and Intelligence solutions use AI to evaluate contact center performance and to provide solutions to improve contact center performance or efficiency. These vendors typically emphasize strong capabilities in analyzing large volumes of voice and text contact center data. Use cases include: - Agent performance evaluation and measurement, and generation of feedback - Analysis of encounter content and generation of solutions to address customer needs - Customer sentiment analysis
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AI Conversational Chat
Market Map
AI Conversational Chat encompasses the next generation of chatbots. These companies are using more advanced NLP, machine learning and gen AI to tackle full “front desk” functionality and create a personalized experiences through text, voice, and web-based messaging in functions including: - Scheduling and appointment management - Prescription refills - Triage and call routing - Intake - Billing Further, some conversational chat solutions are increasingly focused on clinical capabilities to better engage patients and extend the reach of care teams: - Patient engagement and education - Care navigation and care management - Medical interviewing and risk analytics
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Patient-Facing AI Phone Calls
Market Map
Patient-Facing AI Phone Calls includes products that enable AI-based interactions with patients over the phone. Most products in this space are focused on inbound calls, but there are some outbound call capabilities for appointment reminders and other administrative tasks. Some products will also have web- and chat-based capabilities as well. Companies in this category are differentiated by conversational capabilities powered by advanced AI included NLP, generative AI and machine learning. Vendors in this category have varying coverage of use cases, including: - Appointment scheduling - FAQ for hours, location, parking, etc. - Prescription Refill requests - IT Helpdesk for patient-facing IT - Department and Provider Search - Patient billing Differentiation in this space tends to come from factors including: - Ability to manage complicating factors like background noise, varied accents, and off-track conversations  - Fluid conversational ability with a human-sounding AI, unlike traditional IVR call trees - Support for multiple languages, especially for a wider set of patient demographics - Fallback support with human agents when the AI isn’t getting the job done - Technical considerations including data privacy, security, and EHR integration quality - Analytics capabilities to help track success rates, errors, and unknown FAQs.
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Payer-Facing AI Phone Calls
Market Map
Payer-Facing AI Phone Calls includes products that enable AI-based interactions with payers over the phone. Generally, payer-facing companies will tend to be making outbound phone calls, but there may be some inbound-calling capabilities as well. Some of the common use cases for products in this category include: - Eligibility and verification of benefits - Prior authorization - Claims status checks - Denied claims appeals - Credentialing and provider management Because the payer environment is generally much more controlled than a patient-facing environment, some of the differentiating factors in this space include: - Fallback support with human agents when the AI isn’t getting the job done - Technical considerations including data privacy, security, and EHR integration quality - Caller dashboard to enable requesting outbound calls and viewing call results. - Analytics capabilities to help track success rates and potential errors across calls. - Payer-specific modules to handle the IVR tree and agent script, or - Low-code script builder to enable customized calling procedures
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