4 Models of Human-AI Collaboration in Customer Service: Which One Should Businesses Choose?

There are four common models of human-AI collaboration in customer service: Assistive AI, Human-in-the-Loop, Sequential Handoff, and Multi-Step Process. Each model defines a different way of distributing responsibilities between AI and human agents, helping businesses leverage automation while maintaining human expertise and empathy to improve customer experience.

Artificial Intelligence (AI) is increasingly being used in customer service to automate tasks such as handling inquiries, answering frequently asked questions, retrieving information, and supporting operational processes. However, increasing automation does not always lead to better customer experiences.

At VIDEX Cambodia 2026, Mr. Pham Manh Hung, Deputy Director of Customer Experience at Viettel Customer Service (VCX), emphasized the message "More AI ≠ Better CX", highlighting that deploying more AI does not necessarily translate into better customer experiences.

From this perspective, businesses need to clearly define which tasks AI should handle, when human intervention is necessary, and how both can work together to resolve customer requests effectively.

1. What Is Human-AI Collaboration in Customer Service?

Human-AI collaboration in customer service refers to an operational approach in which AI systems and human agents work together to handle customer requests, with responsibilities assigned according to specific tasks or stages of a service process.

AI is typically used to collect information, handle repetitive inquiries, retrieve data, and automate routine tasks. Human agents, meanwhile, focus on activities requiring professional judgment, decision-making, and personalized interactions in complex situations.

Human-AI collaboration offers three key benefits:

• Improved handling efficiency: AI automates common tasks, reducing the manual workload for customer service agents.

• Optimized operational resources: Human agents can focus on requests that require expertise, judgment, and problem-solving skills.

• Enhanced customer experience: Businesses can combine AI's speed and efficiency with human flexibility and empathy.

Depending on their operational requirements, businesses can adopt one model or combine multiple approaches within the same customer service system.

2. Four Models of Human-AI Collaboration in Customer Service

2.1. Assistive AI – AI Supporting Human Agents

Assistive AI is a model in which artificial intelligence acts as an assistant, helping customer service agents retrieve information, analyze data, and suggest solutions, while human agents remain responsible for customer interactions and final decisions.

In this model, AI does not replace human agents. Instead, it reduces the time spent on supporting tasks such as searching for service policies, retrieving operational procedures, and reviewing customer interaction histories.

For example, when a customer contacts a call center to ask about the eligibility requirements for a service package, AI can retrieve relevant policies and suggest an appropriate response. The human agent then verifies the information, makes adjustments if necessary, and communicates directly with the customer.

Assistive AI is particularly suitable for contact centers that manage extensive knowledge bases, frequently update service policies, or aim to improve agent productivity while maintaining direct human interaction.

Key characteristic: AI supports information processing, while human agents retain control over customer interactions and decisions.

2.2. Human-in-the-Loop – Human Oversight of AI

Human-in-the-Loop is a model in which AI automatically performs tasks or parts of a process, while human agents monitor, review, and intervene when verification or decision-making is required.

Unlike Assistive AI, Human-in-the-Loop allows AI to independently perform tasks within predefined boundaries. Human agents do not need to participate in every action but remain responsible for overseeing critical stages.

For example, in a refund request process, AI can collect customer information, check eligibility conditions, and classify requests. Cases that fully meet predefined criteria may be processed automatically according to approved procedures. Requests involving exceptions or unclear information are referred to human agents for review and decision-making.

This model is suitable for processes with relatively clear operational rules that still require human oversight to minimize errors and ensure compliance.

Key characteristic: AI executes tasks autonomously within defined limits, while humans maintain control over important decisions and exceptional cases.

2.3. Sequential Handoff – Transferring Requests from AI to Human Agents

Sequential Handoff is a model in which AI handles initial customer interactions and transfers requests to human agents when issues exceed its capabilities or require specialized support.

A critical element of this model is the ability to transfer relevant customer information and interaction history, ensuring a seamless service experience.

For example, a customer uses a chatbot to report an internet connectivity issue. AI collects the necessary information, identifies the type of problem, and guides the customer through basic troubleshooting steps. If the issue remains unresolved, the system transfers the request, along with the conversation history, to a technical support agent.

As a result, customers do not need to repeat their problems, and human agents can continue the resolution process using information already collected by AI.

Sequential Handoff is particularly suitable for businesses handling high volumes of customer inquiries, where many simple requests can be resolved automatically but complex cases still require human assistance.

Key characteristic: AI handles initial interactions, while human agents take over when necessary, maintaining continuity throughout the customer journey.

2.4. Multi-Step Process – Human-AI Collaboration Across Multiple Stages

Multi-Step Process is a model in which AI and human agents participate in different stages of a multi-step workflow, with responsibilities assigned according to their respective capabilities and expertise.

Rather than relying on a single handoff from AI to a human agent, this model enables AI and humans to alternate responsibilities throughout the same process.

For example, in a customer complaint resolution process:

1. AI receives the complaint: Collects customer information, identifies the issue, and categorizes the request.

2. Human agents assess the case: Investigate the cause, verify information, and determine an appropriate resolution.

3. AI supports execution: Sends resolution notifications or updates request statuses based on approved decisions.

4. AI supports follow-up: Conducts customer satisfaction surveys after the issue has been resolved.

Multi-Step Process is suitable for workflows involving multiple stages, cross-department coordination, or a combination of automated activities and professional decision-making.

Key characteristic: AI and human agents collaborate across multiple stages to complete an end-to-end customer service process.

3. Comparing the Four Human-AI Collaboration Models

The four models differ in the role of AI, the level of human involvement, and how customer service processes are organized.

The fundamental difference lies in when and how human agents participate in the service process.

Assistive AI keeps human agents at the center of customer interactions. Human-in-the-Loop emphasizes human oversight of automated tasks. Sequential Handoff focuses on transferring requests when necessary, while Multi-Step Process organizes collaboration across multiple workflow stages.

These models are not mutually exclusive. A business may use Assistive AI to support its agents, Sequential Handoff for chatbot interactions, and Human-in-the-Loop for processes requiring additional control.

4. How Should Businesses Choose the Right Human-AI Collaboration Model?

Choosing the right human-AI collaboration model depends on three key factors: the complexity of customer requests, the potential for process automation, and the level of human intervention required.

For tasks involving direct customer consultation and frequent information retrieval, Assistive AI can help agents work more efficiently. If a process can be automated but requires verification or approval at certain stages, Human-in-the-Loop may be more appropriate.

When businesses want AI to serve as the initial point of contact and transfer complex requests to human agents, Sequential Handoff is a practical option. For workflows involving multiple stages, Multi-Step Process enables responsibilities to be distributed between AI and humans throughout the process.

However, effective collaboration also depends on data quality, system integration, and operational procedures. In particular, customer information should remain accessible and consistent when interactions move across channels or between AI and human agents.

Businesses should also monitor performance indicators such as resolution rates, handling time, transfer rates, and customer satisfaction to continuously refine their collaboration models.

5. Viettel Customer Service Supports Businesses in Implementing Human + AI Collaboration Models

With over 22 years of experience in customer service, a workforce of more than 4,000 employees, and experience serving over 120 million customers across more than 10 countries and territories, Viettel Customer Service (VCX) combines operational expertise with technology consulting and development to help businesses improve customer service efficiency.

Through its customer experience technology ecosystem, VCX provides platforms that enable businesses to implement Human + AI collaboration models tailored to their operational needs:

• OmniX: An omnichannel contact center platform that enables businesses to manage customer interactions and maintain consistent customer information across service channels.

• CXBot: An AI Agent solution, including Callbot and Chatbot, that automates the reception, consultation, and handling of common customer inquiries.

• KnowX Hub: An intelligent knowledge management platform integrating AI Search and AI Assistant to help employees quickly retrieve information and access relevant operational knowledge.

The integration of these platforms enables businesses to build customer service workflows in which AI and human agents collaborate across various stages, from receiving inquiries and retrieving information to resolving issues and transferring complex cases.

Rather than adopting a fixed automation approach, businesses can select and adapt collaboration models to suit specific workflows, customer segments, and operational objectives.

Viettel Customer Service is a subsidiary of the Viettel Group, operating in the technology and customer service sector. The company provides a comprehensive ecosystem including services (Contact Center Outsourcing, BPO, Upsale, Customer Experience, Loyalty, Document Processing and Digitization, Warranty & Repair Services) and technology solutions (OmniX, CXBot, KnowX Hub, AI-DMS, vCOC, InsightCI, WorkforceX). 

Contact Viettel Customer Service today for solutions tailored to your business!

Contact Information:

• Hotline: 1800 9397 / Email: dvkh@viettel.com.vn

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