INTERVIEW: Is AI-Driven Customer Service Improving Efficiency at the Expense of Customer Trust?

Despite rapid adoption, IBM research shows that while AI is now embedded in over half of enterprise workflows, fewer than one in three companies say they have achieved “fully reliable” customer-facing automation at scale, underscoring the persistent gap between efficiency gains and customer trust. Even as McKinsey estimates that AI could automate up to 70% of customer operations tasks, Salesforce data shows trust and human responsiveness remain the top drivers of customer loyalty, suggesting efficiency alone is not yet a competitive advantage. With Gartner forecasting that AI agents will handle a growing share of customer interactions this year, recent industry surveys still show trust, empathy and human access consistently ranking above speed as key drivers of retention. While AI adoption in customer service continues to accelerate, Deloitte data shows many firms are still struggling to scale automation without harming experience quality, revealing that the “fully automated customer journey” remains more aspiration than reality.

Artificial intelligence is rapidly transforming how businesses interact with customers. From chatbots and virtual assistants to AI-generated emails and automated support agents, companies across industries are investing heavily in technology designed to reduce costs, increase efficiency and handle growing volumes of customer inquiries. Industry analysts estimate that AI could automate a significant share of customer service tasks, with McKinsey projecting in April that generative AI alone could automate up to 60–70% of employee time in customer operations functions in some sectors.

The trend has accelerated in 2025–2026 as organizations face mounting pressure to improve productivity while managing economic uncertainty and restructuring cycles. Large employers across technology, financial services and retail have announced workforce reductions and reorganizations, with AI frequently cited as a contributing factor in efficiency strategies and operational redesign. Industry surveys consistently show that executives rank AI-driven productivity gains and cost reduction among the top drivers of digital investment.

At the same time, AI adoption in customer experience has surged. Companies are deploying conversational AI tools capable of handling customer inquiries through chat, email, voice and social media channels. According to Gartner, By 2028, at least 70% of customers will use a conversational AI interface to start their customer service journey, with a growing shift toward “AI agents” capable of autonomous task execution rather than simple scripted responses. 

New generations of these systems can schedule appointments, answer questions, resolve routine issues and even conduct sales conversations with minimal human involvement. The emergence of “agentic AI” systems is further accelerating expectations that many customer-facing workflows can be partially or fully automated.

Yet evidence suggests that fully automated customer relationships remain far from a perfect solution.

Recent research indicates that while AI can improve efficiency and shorten response times, customer trust remains a significant challenge. A March survey by IBM found that while enterprises are rapidly adopting AI, concerns around accuracy, transparency and governance remain among the top barriers to scaling AI in customer-facing environments. In parallel, academic and applied research shows that poorly governed AI systems can generate incorrect or inconsistent responses, creating reputational and compliance risks in customer service contexts.

Additional studies highlight a more nuanced outcome: generative AI can significantly improve productivity, particularly for less-experienced employees, but performance gains are not universal. A well-known field study published in Science found that AI assistance improved productivity in customer support teams, especially among lower-skilled workers, but also required human oversight to ensure accuracy and quality control.

For marketers and business leaders, the challenge is becoming increasingly clear: customers may appreciate faster service, but they still value empathy, trust, accountability and strategic guidance when making important decisions. Salesforce’s research consistently shows that trust and experience are now primary drivers of customer loyalty, often outweighing price or product features in competitive markets. High-value purchases, complex business relationships and sensitive customer issues often require human expertise that AI cannot easily replicate.

This shift is creating a new competitive dynamic. While many organizations focus on replacing human interactions with automation, others are pursuing a “human-in-the-loop” model in which AI handles routine administrative tasks while employees focus on relationship building, problem solving and strategic counsel. 

Research from Harvard Business School and MIT Sloan Management Review suggests that hybrid human–AI systems tend to outperform fully automated or fully manual models in complex service environments, particularly where trust and contextual judgment matter.

Michelle Abdow, president and CEO of Market Mentors, sat down with tech editor Faustine Ngila to discuss where AI delivers genuine value, where businesses risk damaging customer relationships through over-automation, and why human connection may become one of the most important differentiators in an increasingly AI-driven marketplace.

Here is the interview excerpt:

1. Many companies are aggressively replacing customer-facing roles with AI to cut costs. At what point does automation begin to damage trust rather than improve efficiency?

Automation begins damaging trust when customers feel there is no real human available during important moments. AI is extremely effective for routine tasks such as scheduling, reporting or answering simple questions, but high-stakes situations still require empathy, judgment and accountability. When customers feel trapped in an automated system instead of supported by people, efficiency starts coming at the expense of trust.

2. Are businesses underestimating how quickly customers can detect AI-generated communication, especially in high-stakes industries such as finance, healthcare, or enterprise services?

Absolutely. Customers may not always know exactly how the content was generated, but they can quickly sense when communication feels generic, scripted or emotionally disconnected. In industries like finance, healthcare and enterprise services, people want reassurance that someone genuinely understands the complexity and seriousness of their situation. AI can support communication, but it cannot fully replace authentic human connection.

3. You argue that human relationships are becoming a competitive advantage. What evidence are you seeing that clients are actively pushing back against over-automated service models?

We are seeing increasing frustration with impersonal service experiences, endless chatbot loops and difficulty reaching empowered decision-makers. At the same time, clients place enormous value on responsiveness, strategic guidance and relationships built on trust. As AI tools become more widely available, technical capabilities are becoming less differentiating. The real differentiator is the quality of the relationship behind the service.

4. Which specific marketing or customer-service functions should never be fully handed over to AI, regardless of how advanced the technology becomes?

Functions involving trust, nuance, and high-stakes decision-making should always involve humans. That includes crisis communications, sensitive customer issues, executive counseling, reputation management, and strategic client relationships. AI can absolutely support those functions by improving efficiency and surfacing insights, but the final interaction still requires human judgment, empathy, and accountability.

5. As generative AI floods inboxes, websites and support channels with synthetic communication, how do brands preserve authenticity and emotional credibility?

Brands preserve authenticity by using AI to enhance communication rather than replace humanity altogether. Customers still want transparency, empathy, and access to real people who understand their concerns. The companies that stand out will be the ones that combine the efficiency of AI with a strong human voice and a genuine commitment to relationships.

6. Could overreliance on AI create a “race to sameness” in marketing, where brands lose differentiation because they rely on similar models, prompts and automation workflows?

Yes, and I think we are already seeing early signs of it. AI is very good at generating polished content, but it often pulls toward predictable patterns and familiar language. If every company relies on similar tools and prompts, brands risk sounding interchangeable. True differentiation still comes from original thinking, creativity, perspective and emotional resonance, which are fundamentally human qualities.

7. What are the long-term reputational risks for companies that reduce headcount too aggressively in favor of AI-driven customer engagement systems?

The long-term risk is that companies unintentionally weaken customer loyalty and trust. Automation may create short-term efficiency gains, but customers remember how brands make them feel during important moments. If companies become too difficult to reach or appear indifferent to customer concerns, that perception can damage both reputation and retention over time.

8. Looking ahead, do you believe the companies that win in the AI era will be those with the best automation systems, or those that strike the best balance between machine efficiency and human judgment?

The companies that win will be the ones that strike the best balance. AI will become standard infrastructure across industries, so technology alone will not be enough to differentiate a business. The real competitive advantage will come from using AI to remove friction while empowering people to focus on strategy, creativity, relationships and trust.

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