Whitepaper

The Human Effect: Why People Still Matter in Service Interactions

Mariano Tan

Founder and CEO, Prosodica

October 16, 2025

The Uncomfortable Conclusion That's Wrong

For years, customer service strategy has followed a set of tidy, logical rules. Humans handle the complex; automation handles the simple. Older customers prefer people; younger customers prefer machines. Automation scales; humans personalize. Follow that logic to its end and you reach an uncomfortable conclusion—humans have no long-term role in customer service. The problem is, that conclusion is wrong. There's a deeper reason humans remain indispensable in service interactions: having a real person in the conversation changes the way customers behave. When people perceive that they are being listened to by another human, they respond differently—often more politely, more patiently, and with greater openness. In some situations, the very fact of interacting with a person is what makes the service experience successful.

Why Do People Behave Differently with Humans?

Psychologists have long shown that anonymity changes behavior. When people feel unseen, they act in ways they never would face-to-face—more blunt, more hostile, less restrained (Suler, 2004). Theories of deindividuation and social identity explain why: anonymity weakens self-awareness and the social norms that guide civility (Reicher, Spears & Postmes, 1995). Customers say things to an IVR that they'd never say to another human being. This is the principle behind why we ask agents to introduce themselves by name—to establish personal accountability. The lesson is simple: people act differently when they know another human is present, even if the cue is subtle.

Anonymity

Weakens self-awareness and social norms that guide civility

Human Presence

Establishes personal accountability and changes behavior

Social Norms

Guide people to act more politely and patiently

Real-world Evidence of the "Human Effect"

This principle extends directly into customer service. Consider Alorica's AloriCares program, a recruiting initiative launched to hire U.S. veterans and military spouses, providing them with meaningful career opportunities and support as they transition into civilian life. Participants are connected with jobs at Alorica—including remote, workfrom-home positions—and receive paid training, wellness resources, and ongoing coaching. What made the program particularly striking for customers was the way each call began. Before the connection with a representative, an announcement informed the caller that they were about to speak with a U.S. veteran or the spouse of a veteran. This simple cue of identity often changed the tenor of the interaction: callers became noticeably more patient, more polite, and more understanding. By humanizing the representative upfront, the program tapped into social norms of respect and recognition, reshaping customer behavior before a word of the service conversation was spoken.

The Three Factors That Drive Customer Satisfaction

Similar dynamics appear across industries. In Prosodica's analysis of millions of conversations, customer satisfaction is not simply about whether an issue is resolved quickly. Instead, it hinges on three factors:

01

Resolution

Did the customer get what they needed?

02

Effort

How hard was it for them to get it?

03

Conversational Experience

Did the agent engage, empathize, and communicate clearly?

Of these, the human qualities of empathy, engagement, and clarity often prove decisive. Customers are more forgiving of delays or process hurdles when they sense that the person on the other end is engaged and authentic.

Example 1: Patient Scheduling and No-Shows in Healthcare

Missed appointments are a costly, persistent challenge in healthcare. Automated reminders help, but evidence shows that human outreach still outperforms pure automation. A multi-clinic review found that phone calls made by staff resulted in a 13.6% no-show rate, compared with 17.3% for automated reminders (Simbo.ai, 2023).

Systematic reviews confirm the trend: hybrid reminder systems combining automation with human follow-up lower no-show rates and waiting times (Woodcock et al., 2022, BMC Health Services Research). The difference stems from perceived accountability and care—the sense that someone will notice if you don't show up.

Example 2: Hybrid Complaint Handling in Customer Service

AI systems now triage and respond to complaints faster than ever, but satisfaction still depends on human involvement. Studies show that while AI improves efficiency and consistency, customer satisfaction rises significantly when a human is visibly in the loop (Akinyemi et al., 2025, Multidisciplinary Journal). Another comparative study found that hybrid models—where chatbots manage routine queries and escalate emotional cases to humans—deliver the highest satisfaction and loyalty (Mangipudi, 2025, ResearchGate).

AI Triages

Fast, efficient complaint routing

Human Resolves

Emotional, complex cases

Higher Satisfaction

Best of both worlds

Example 3: AI Voice Support with Human Escalation

In a 2025 consumer survey, hybrid "AI-plus-human" voice models achieved 27% faster resolutions and higher satisfaction than fully automated or fully human systems (PhoneCall.bot, 2025). Nearly 90% of respondents still preferred humans for emotionally charged or ambiguous issues. Automation drives speed, but human presence anchors trust.

Faster Resolutions

Hybrid AI-plus-human models

Prefer Humans

For emotional or complex issues

Are There Times When "Less Human" Works Better?

There are indeed contexts where automation outperforms humans precisely because it removes the social dimension. For example, one consumer debt collection operation observed that automated repayment reminders led to higher completion rates than live calls. In those interactions, customers seemed to spend less effort justifying their circumstances or engaging in small talk. Freed from the social pressures of a live conversation, they focused more directly on completing the transaction. This aligns with decades of research in survey methodology: respondents disclose more when interactions are computer-mediated rather than interviewer-led (Tourangeau & Smith, 1996; Kreuter, Presser & Tourangeau, 2008). Without the social pressure of a human audience, people tend to be more open and candid. So while human presence elicits prosocial behavior in many service contexts, its absence can lower barriers in others. The trick is knowing which situations call for each.

Key Insight: Removing human presence can reduce social pressure and increase candor in sensitive transactions like debt repayment or stigmatized disclosures.

The Human Effect in Action

Scenario Best Approach Why It Works Illustrative Outcome
High-stakes service recovery (e.g., resolving a serious billing or medical error) Human-led interaction Empathy, apology, and adaptive communication rebuild trust; scripted automation would feel dismissive. Customers who received direct callbacks from senior reps reported 40% higher satisfaction and 5% lower attrition (CX Benchmark, 2024).
Sensitive or stigmatized transaction (e.g., debt repayment or delinquency notice) Automation-led interaction Removing social judgment reduces defensiveness and increases follow-through. Automated systems allow customers to focus on resolution rather than justification. Automated repayment reminders achieved higher completion rates than live calls (Prosodica Field Observation, 2024; Tourangeau & Smith, 1996; Kreuter et al., 2008).
Complex but repeatable process (e.g., telecom plan change or loan application) Hybrid: AI frontend + human escalation Automation handles data intake and validation; humans intervene for negotiation, empathy, or exceptions. Hybrid routing reduced average handle time by 22% and improved NPS by 11 points (Mangipudi, 2025).
Emotionally nuanced conversation supported by AI (e.g., healthcare benefit appeal or financial hardship counseling) Human-led, AIassisted Real-time agent assist provides consistency and compliance while preserving empathy and tone. Agents using live AI prompts maintained 95% compliance accuracy and improved empathy scores by 18% (Prosodica Internal Analytics, 2024).

How Should Organizations Design for Humanness?

Smart service organizations will stop asking only "What can AI automate?" and start asking "How does activating my customer's humanness improve outcomes?" That reframing yields distinct design principles:

Amplify human presence where it matters most

Use visible names, warm voice cues, or identity announcements (as in the AloriCares program) to humanize agents in high-stakes interactions.

Be deliberate about reducing human cues where privacy matters

For debt repayment, sensitive health disclosures, or complaint logging, offer bot-led flows or anonymous self-service channels that make it easier for customers to act without embarrassment.

Hybridize, don't polarize

The best outcomes often come from blended models: AI handles the routine, humans step in for critical moments, and both work together to reduce effort while preserving humanity.

Bring automation's strengths into human interactions

Real-time agent-assist tools deliver consistency, accuracy, and instant recall inside conversations—without removing the human from the loop.

Conclusion: The Irreplaceable Role of People

The future of service isn't about choosing between humans and AI. It's about understanding that the presence or absence of a human changes how customers behave. Sometimes that presence elicits patience, trust, and cooperation; sometimes removing it encourages candor and efficiency. Organizations that learn to design for both will outperform those that don't. Automation can scale and streamline4but only humans can make interactions feel accountable, empathetic, and fair. That's the real competitive edge. AI will continue to take on tasks at scale, but it will never erase the human effect. And for the moments that matter most, that effect remains vital.

"AI will continue to take on tasks at scale, but it will never erase the human effect. And for the moments that matter most, that effect remains vital."

References

  • Suler, J. (2004). The Online Disinhibition Effect. CyberPsychology & Behavior.
  • Reicher, S., Spears, R., & Postmes, T. (1995). A Social Identity Model of Deindividuation Phenomena. European Review of Social Psychology.
  • Bateson, M., Nettle, D., & Roberts, G. (2006). Cues of Being Watched Enhance Cooperation in a Real-World Setting. Biology Letters.
  • Ernest-Jones, M., Nettle, D., & Bateson, M. (2011). Effects of Eye Images on Everyday Cooperative Behavior. Evolution and Human Behavior.
  • Woodcock, T., et al. (2022). Reducing Missed Appointments: Systematic Review of Reminder Systems. BMC Health Services Research.
  • Akinyemi, A., et al. (2025). Artificial Intelligence in Complaint Management Systems. Multidisciplinary Journal.
  • Mangipudi, S. (2025). AI-Powered Chatbots vs. Human Agents: A Comparative Study on Customer Satisfaction. ResearchGate.
  • Tourangeau, R., & Smith, T. (1996). Asking Sensitive Questions: The Impact of Data Collection Mode. Public Opinion Quarterly.
  • Kreuter, F., Presser, S., & Tourangeau, R. (2008). Social Desirability Bias in Surveys Administered by Computer vs. Interviewer. Public Opinion Quarterly.
  • PhoneCall.bot Consumer Survey, 2025.
  • Prosodica Internal Analytics (2024). Conversation Outcomes Dataset.

About the Author

Mariano Tan is the Founder and CEO of Prosodica, an AI-powered speech and interaction analytics platform that helps organizations create better conversations. With more than three decades of experience in customer operations and enterprise technology, he draws on Prosodica's technology and data from millions of analyzed conversations to explore the intersection of AI, workforce transformation, and the human side of service. At Prosodica, Mariano leads a mission to make professional conversations more empathetic, data-driven, and effective across industries.

This article was featured in The Insights Hub4Prosodica's destination to unlock deeper insights and explore expert perspectives on AI, customer experience, and the future of conversations.

Related Topics
Getting Fined for UX Design: Why Amazon's $2.5B Prime Settlement Proves Businesses Need Automated Complaint Detection
Whitepaper
October 14, 2025
Keep Call Centers in America: A Boon for Workers or a Blow to AI?
Whitepaper
August 29, 2025
Leveraging Generative AI for Enhanced Customer Insight Extraction in Telephony
Whitepaper
August 10, 2025