AI Chatbots in Customer Service: Can They Replace Human?

March 24 2025 Jana Elwan

Artificial intelligence

AI Chatbots in Customer Service: Can They Truly Replace Human Agents?

Since its inception in the late 1990s and early 2000s, artificial intelligence in customer service has advanced significantly (Schwarz, 2024). Initially, the use of AI was limited to simple chatbots that offered assistance based on predefined responses (Schwarz, 2024). By the early 2010s, technology and AI’s capabilities had advanced. More specifically, through natural language processing (NLP) and machine learning (ML), chatbots were now capable of handling consumer inquiries with greater nuance a more human-like manner via email, phone, websites, and social media (Schwarz, 2024). In light of these advancements, Gartner (2023) forecasts that 20–30% of businesses would replace human customer service agents by AI-powered chatbots by 2026. Furthermore, according to a 2022 BCG survey of worldwide customer service leaders, 95% of them expect their customers would be assisted by an AI chatbot in the next three years (Bamberger et al., 2023). This shift to AI chatbots may be explained by the long wait times, inconsistent support, and scalability issues associated with traditional customer service agents (Samson et al., 2021). AI-powered chatbots are revolutionizing the customer service industry by instantly responding to customers, being available 24/7, collecting data, managing a large volume of queries, offering cost-efficiency and scalability (Certainly, 2025). This raises the question of whether these AI chatbots truly replace human agents?

Table of Contents

Advantages vs. Disadvantages of AI chatbots in customer service

Advantages of AI chatbots in customer service

On the one hand, AI chatbots are associated with several advantages.

Firstly, AI chatbots can handle customer service queries efficiently by managing a large volume of standardized questions, providing instant responses, and being available 24/7, unlike human agents who are limited by their working hours (Certainly, 2025). In fact, according to data from over 14,000 merchants who transitioned to AI chatbots, 37% experienced decrease in first response time and 52% decrease in resolution time (Augstin, 2024).

Secondly, through machine learning algorithms (Schwarz, 2024), AI chatbots can effectively collect customer data and feedback, providing ground for companies to personalize and improve their customer experience (Certainly, 2025). This could potentially lead to increased customer retention, as AI chatbots collect and analyze customer interaction data, enabling the company could identify and address pain points, recurring issues, and areas for improvement (ada, n.d.).

Thirdly, AI chatbots are more cost-friendly solution than hiring human agents, especially for businesses aiming to scale their operations (Certainly, 2025). An IBM report indicated that customer service costs could reduced by up to 30% when using AI customer service chatbots (Jobanputra, 2024).

Disadvantages of AI chatbots in customer service

Despite the advantages offered by AI chatbots, they also have some drawbacks.

Firstly, AI chatbots can have limited understanding and problem-solving abilities when it comes to complex queries that need human judgement or expertise. This is mainly due to their dependence on predefined responses, which restrict their ability to address unique customer concerns (Certainly, 2025).

Secondly, AI chatbots can lack emotional intelligence, preventing them from empathizing with customers and understanding human emotions (Certainly, 2025). This often leads to impersonal interactions and customer dissatisfaction (Certainly, 2025).

Thirdly, AI chatbots’ quality and accuracy levels highly depend on the data they are trained on (Certainly, 2025). If the data they are trained on is biased or outdated, AI chatbots will provide inaccurate results (Certainly, 2025).

AI customer service chatbots		Human customer service agents
Advantages	Disadvantages	Advantages	Disadvantages
• Managing a large volume of queries • 24/7 availability • Instant responses • Data collection • Cost-efficient	• Lack of emotional intelligence and empathy • Inability to solve complex problems • Dependency on data quality	• Having emotional intelligence and empathy • Ability to solve complex problems • Ability to build relationships with customers	• Limited availability • Being resource-intensive • Being error-prone

Table 1: Advantages and disadvantages of AI vs. Human customer service agents (Certainly, 2025)

As shown in Table 1, human customer service agents and AI customer service chatbots nearly complement each other in terms of their respective advantages and disadvantages. For instance, while AI chatbots lack emotional intelligence and empathy, human customer service agents possess these qualities. On the other hand, while human customer service agents have limited availability, AI customer service chatbots are 24/7 available. This makes one think whether AI customer service chatbots are better off replacing human customer service agents or not.

Collaborative intelligence

Interestingly, Wilson & Daugherty (2018) explained that AI is not here to replace humans but rather to augment their capabilities and enhance each other’s strengths through intelligent collaboration, through the concept of collaborative intelligence. Through their research implicating 1,500 companies, they found that firms perform significantly better when humans work together AI chatbots (Wilson & Daugherty, 2018). According to them, human must assist AI machines by performing the following roles: training and sustaining AI chatbots as well explaining their behavior in evidence-based industries (e.g., medicine and law). However, in the case of AI customer service chatbots, the first two are the only relevant roles.

Train: As previously mentioned, AI chatbots are only as good as the data they are trained on, which is where the role of humans comes in (Certainly, 2025). Human involvement is crucial in ensuring that the data used to train these is of high quality, both in terms of accuracy and in shaping the desired personality for the customer service agent (Certainly, 2025; Wilson & Daugherty, 2018). For instance, if empathy is an important trait for the chatbot, humans must ensure that the AI is specifically trained to show empathy to its users (Wilson & Daugherty, 2018).

Sustain: Humans can ensure that these AI chatbots are working smoothly, safely and responsibly (Wilson & Daugherty, 2018).

Having outlined, AI customer service chatbots’ advantages and disadvantages as well as how it can be leveraged using humans, it is now relevant to explore some real-life examples of AI customer service chatbots in a few industries.

Case Studies in different industries

Retail industry: H&M

H&M, the global fashion retailer, uses AI chatbots in customer service across multiple platforms, including their website, mobile applications and social media channels, to handle a wide range of customer inquiries (Filipsson, 2025). Specifically, these chatbots manage tasks such as order tracking, providing product information, processing return and, and even offering fashion advice (Filipsson, 2025).

Insurance industry: Allianz

Allianz, the leading global insurance company, developed its AI customer service chatbot, “Allie”, which is integrated into the company’s website, customer portal, Allianz Engage app and Facebook (IBM, n.d.). Integrated with NLP and trained on hundreds of real-life scripts, Allie interacts in a very human-like manner (IBM, n.d.). It handles 80% of inquiries, including even the most complex ones, such as policy inquiries and policy changes (IBM, n.d.). Through Allie, Allianz is better meeting its customer needs, as nearly 50% of customer inquiries handled by Allie are outside of call center working hours (IBM, n.d.). Furthermore, since its launch, the company’s Net Promotor Score (NPS) has been steadily increasing (IBM, n.d.).

Telecommunications industry: Vodafone

Vodafone, a global leader in telecommunications, improved its customer experience through its AI customer service chatbot TOBi (IBM, n.d.). A big advantage of this chatbot is that it can answer customers in 14 different languages (IBM, n.d.), TOBi handles around 1 million interactions per month and holds a 70% first-time resolution rate (Coombes, 2025). Furthermore, if human intervention is needed, the chatbot summarizes the previous conversation, enabling the agent to immediately address the issue without needing to ask the customer to repeat what went wrong, consequently, completing and augmenting the human agent’s capabilities (Coombes, 2025).

Banking industry: DNB

DNB, the leading Norwegian bank, developed a customer service AI chatbot using a “chat-first” strategy (2025). This strategy is based on the principle that customers should interact first with the AI chatbot and should only be directed to a human agent if necessary (boost.ai, 2025). Among approximately 80,000 customer service interactions per month, the bank’s AI chatbot automates over 50% of them (boost.ai, 2025). This AI chatbot augments employees’ capabilities by freeing them up from simple and repetitive tasks consequently allowing them to focus on more complex ones (Dialzara, 2024). Notably, the training of this AI chatbot is managed 15 full-time employees (Dialzara, 2024).

Conclusion

In conclusion, while AI chatbots have proven to be a useful tool in customer service, providing advantages like 24/7 availability, instant responses, and cost efficiency, they cannot currently fully replace human agents. This is a result of their limitations, which include their struggles to tackle complex problems as well as their lack of emotional intelligence and empathy. As demonstrated through the concept of collaborative intelligence, an optimal strategy for businesses could be for AI and human agents to collaborate as they are more successful when they complement and enhance one another rather than when one replaces the other.