In the ever-evolving landscape of customer service, the integration of artificial intelligence (AI) has emerged as a subject of considerable interest and debate. While AI offers the promise of enhanced efficiency, scalability, and cost reduction, recent research suggests that an exclusively AI-driven approach may not deliver the comprehensive solution once anticipated. A notable finding from Gartner indicates that, by 2027, half of the organizations that intended to substantially decrease their customer service workforce through AI adoption will reconsider and abandon these plans. This shift highlights a fundamental insight: the most effective customer service strategies depend on a harmonious balance between AI technologies and human agents. This article examines the critical importance of this equilibrium, drawing upon studies from 2025 to explore the respective strengths and limitations of AI and human agents in delivering superior customer experiences.

Emerging research from 2025 provides robust evidence supporting the adoption of a hybrid model in customer service operations. These studies demonstrate that AI is exceptionally proficient in managing routine, repetitive tasks, such as responding to frequently asked questions, tracking order statuses, or providing basic account details. By automating these processes, AI enables human agents to concentrate their efforts on more intricate, high-value interactions that demand empathy, critical thinking, and emotional intelligence. For example, an article published by CMSWire in February 2025 underscores that the most successful customer service frameworks are those in which AI and human agents collaborate seamlessly, with AI addressing straightforward inquiries and human agents resolving more complex issues. This collaborative approach not only boosts operational efficiency but also aligns with the preferences of customers. Data compiled by Salesforce and CMSWire reveal that 64% of customers value the immediacy of AI-driven responses for simple queries, yet 59% prefer engaging with a human agent when faced with complicated challenges. This duality in customer expectations reinforces the necessity of a balanced strategy that capitalizes on the complementary strengths of AI and human agents.

Research in late 2024 investigated the mechanisms sustaining consumer trust in AI chatbots following service failures, integrating Computers As Social Actors (CASA) and attribution theories. With AI chatbots increasingly utilized in customer service, their occasional failures due to limitations in natural language processing can undermine brand trust. The research constructed a model to explore how social interaction cues and anthropomorphic factors influence sustained trust, using an empirical analysis of 462 survey responses. The findings highlighted that CASA factors—perceived anthropomorphic characteristics, empathic abilities, and interaction quality—played a significant role in rebuilding trust post-failure by shaping users’ attributions of the failure’s cause. In other words, anthropomorphic features, like human-like responses and emotional expressiveness, encouraged users to attribute chatbot failures to external factors (e.g., situational errors) rather than inherent deficiencies, thereby preserving trust.

The study also identified that perceived empathic abilities and high-quality interactions mitigated negative perceptions, fostering emotional connections that reduced blame on the chatbot’s competence. Additionally, AI anxiety, a user’s cognitive apprehension toward AI, negatively affected sustained trust and moderated the impact of internal attributions. Users with higher AI anxiety are less likely to maintain trust when they attribute failures to the chatbot’s capabilities, underscoring the importance of addressing user psychological factors in AI design. The practical implications of the study emphasize the need for companies to enhance chatbot anthropomorphism and empathy to maintain trust after service failures – certainly an area within many companies’ roadmaps – including Teleperson’s – but one that remains genuinely (or at least, distributed widely) out of reach today.

The justification for this balanced approach becomes even more apparent when examining the distinct capabilities of AI and human agents. AI excels in processing vast quantities of data rapidly, delivering instantaneous responses, and functioning continuously without the limitations of human fatigue. These qualities make it an ideal tool for managing high-volume, low-complexity tasks that might otherwise overburden human staff. However, AI’s shortcomings are evident in situations requiring emotional depth, contextual awareness, or innovative problem-solving. For instance, when a customer expresses frustration over a service disruption—such as a delayed delivery or an erroneous charge—a human agent’s capacity to empathize, adapt, and devise tailored solutions remains unmatched. Despite progress in natural language processing and sentiment analysis, AI struggles to replicate the nuanced human connection that customers often seek during such interactions. Consequently, a hybrid model ensures that AI efficiently manages scalable, routine operations, while human agents are reserved for scenarios where their interpersonal skills are indispensable.

Implementing this balanced approach, however, presents several challenges. A primary obstacle is the need to train human agents to work effectively alongside AI systems. According to a Zendesk report from February 2025, only 45% of customer service agents have received training on AI tools, and many of those report dissatisfaction with the quality of the instruction provided. This training deficiency can result in operational inefficiencies and agent frustration, potentially negating the advantages of a hybrid model. Agents lacking proper preparation may find it difficult to leverage AI effectively, leading to suboptimal performance and diminished customer experiences. Moreover, ensuring smooth transitions from AI to human agents is vital to maintaining customer satisfaction. Customers frequently cite irritation when they become ensnared in repetitive chatbot exchanges without an option to escalate their concerns to a human representative. Establishing well-defined escalation protocols is therefore essential to deliver a seamless customer journey. Additionally, ethical considerations play a pivotal role in sustaining customer trust. AI systems must be engineered to minimize biases, safeguard privacy, and operate with transparency. A Cisco news release from May 2025 emphasizes that 99% of customers prioritize strong governance to ensure the ethical deployment of AI, underscoring the importance of addressing these issues within organizational strategies.

The growing significance of AI in customer service is further evidenced by its expanding market presence. A market report from March 2025 projects that the AI customer service sector will increase from $12.06 billion in 2024 to $47.82 billion by 2030, reflecting a compound annual growth rate of 25.8%. This rapid expansion signals AI’s enduring role in transforming customer service, yet it also suggests that organizations must integrate it judiciously to avoid over-reliance on technology at the expense of human interaction. The report highlights that while AI-powered chatbots and virtual assistants are reshaping service delivery, human oversight remains crucial for addressing intricate situations requiring personalized attention. This aligns with the broader trend observed across 2025 research: AI is a potent instrument, but its efficacy is maximized when it enhances, rather than supplants, human agents.

Beyond operational benefits, the hybrid model also positively influences agent satisfaction and performance. An IBM article from June 2025 reports that organizations with advanced AI adoption experience 15% higher agent satisfaction and 17% higher customer satisfaction compared to those with less mature strategies. These improvements stem from AI’s capacity to automate repetitive tasks, offer real-time guidance, and summarize interactions, enabling agents to engage in more rewarding work. Furthermore, AI can reduce the cost per contact by 23.5% and boost annual revenue by 4% on average through conversational technologies. These statistics illustrate that, when strategically implemented, AI enhances both employee and customer experiences. Success, however, hinges on positioning AI as a supportive tool rather than a substitute for human expertise.

Customer perspectives provide additional validation for the hybrid approach. A Cisco survey conducted in May 2025 predicts that by 2028, 68% of customer service interactions will be managed by AI, yet 89% of customers emphasize the value of human connection alongside AI to optimize their experiences. Moreover, 96% of customers consider human relationships essential when interacting with B2B technology partners. These findings indicate that while customers appreciate AI’s efficiency, they continue to cherish the trust, empathy, and individualized care that human agents provide. Organizations that embrace a hybrid model are thus better equipped to fulfill these expectations and foster enduring customer loyalty.

In conclusion, the future of customer service does not lie in an exclusive reliance on either AI or human agents but in leveraging the distinct strengths of both. AI’s proficiency in handling routine tasks efficiently complements the empathy and problem-solving abilities of human agents, resulting in a customer service framework that is both scalable and responsive to customer needs. As organizations address the complexities of incorporating AI into their strategies, they must focus on comprehensive training, streamlined escalation processes, and ethical governance to ensure the success of this hybrid approach. By doing so, they can satisfy the dual customer demands for speed and personal connection. Looking forward, it is evident that companies adept at achieving this balance will be best positioned to provide outstanding customer experiences and secure a competitive advantage in the marketplace.

As you evaluate the role of AI within your own customer service framework, consider how your team might adopt this hybrid approach to improve both customer satisfaction and operational efficiency. The future of customer service is not a choice between AI and human agents—it is a synergy of the two, working in unison to deliver exceptional results.

Jesse Hollander

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