How to reduce customer service costs? It doesn’t mean cutting staff or lowering service quality. It means rethinking the operating model, automating what doesn’t generate value, and freeing up resources for activities with greater strategic impact.
AI-powered virtual assistants currently represent one of the most concrete levers for achieving this result.
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Table of contents
How to reduce customer service costs
According to Gartner, AI adoption in customer service is shifting from a concept of mere automation to a strategic use focused on use cases with the highest potential for economic returns and operational efficiency. Analysts predict that by 2028, at least 70% of customers will begin their support journey through AI conversational interfaces, signaling a profound transformation in interaction management and cost reduction through intelligent automation.
Contact centers today face three main pressures:
- Increasing request volumes
- Growing expectations for immediate responses 24/7
- Difficulty in finding and retaining qualified agents
According to McKinsey & Company, over 80% of contact centers have already integrated at least one virtual assistant to ease operational burdens and reduce customer service costs.
Deloitte highlights that automation can generate:
- Up to 70% reduction in operating costs
- -35% in average management time
- -30% in customer satisfaction
The question is no longer whether to adopt AI, but how to do it to maximize ROI.
The impact of Generative AI to reduce costs
With the evolution of advanced language models, virtual assistants are no longer limited to canned responses but can make a difference in reducing customer service costs.
What changes in economic terms?
- Higher first-contact resolution (FCR) rate
- Reduced escalations
- Fewer operational errors
- Reduced need for ongoing staff training
Furthermore, Forrester emphasizes that hybrid human-in-the-loop models are now the best practice: AI handles transactional tasks, while agents focus on high-value cases.
The result: lower operating costs for every euro of revenue managed.
How AI Generates Real Cost Reductions
The areas with the greatest impact where AI can make a difference in reducing customer service costs.
- Automation of first-level requests
Repetitive requests (order status, password reset, invoices, SLAs, policies) represent up to 60–80% of total volume.
Automating them means:
Reducing the number of tickets handled by human operators
Reducing the cost per contact
Reducing the average response time
Each automated interaction has a near-zero marginal cost. - Scalability
During peak periods (onboarding, renewals, campaigns, technical failures), companies traditionally:
Hire temporary staff
Pay overtime
Accept lower KPIs
A virtual assistant scales instantly, without variable costs proportional to volume. - Reduction of AHT (Average Handling Time)
Virtual assistants integrated with CRMs allow you to:
Retrieve customer data in real time
Prepopulate responses
Suggest solutions to agents
This dramatically reduces handling times, even for complex cases.
Use cases with the greatest economic impact in reducing customer service costs
If the goal is to reduce costs, not all use cases are equally important.
Guided technical support
Reduces repetitive tickets and first-level interventions.
Automated order and return management
Lowers the after-sales burden.
CUSTOMERS Onboarding
Reduces time spent by account teams.
Co-pilot for operators
It suggests answers and retrieves information in real time, reducing errors and downtime.
How to Implement AI to Maximize ROI
To reduce customer service costs, it’s essential to follow a structured and strategic approach that goes beyond simply activating a chatbot. The first step is to analyze current costs, evaluating metrics such as cost per ticket, volume by category, average handling time, and escalation rate, to identify the most critical areas. Next, it’s necessary to prioritize identifying high-volume, low-value requests that need to be automated to generate significant economic impact immediately. Integration with existing business systems, such as CRMs and ticketing platforms, is essential to ensure AI operates efficiently and in context. Finally, it’s necessary to continuously monitor financial and operational KPIs, including cost per interaction, reduction in human resources required, quarterly ROI, and payback period, to optimize the investment and ensure measurable long-term results.
Transforming customer service from a cost center to a strategic lever
According to Zendesk’s Customer Experience Trends Report, 79% of agents say AI improves the quality of their work by reducing repetitive tasks.
This means:
- Lower turnover
- Higher staff retention
- Improved internal climate
- Reduction in indirect training and recruiting costs
Cost reduction isn’t just technological: it’s organizational.
ConclusionS
Companies that properly implement virtual assistants with generative AI can achieve:
- Up to 70% reduction in operating costs
- Improved customer satisfaction
- Greater scalability without structural cost increases
The strategic question is not “How to reduce customer service costs?” but:
Can we afford not to optimize our customer service?
FAQs – Reduce customer service costs
ROI is assessed by monitoring both operational and financial KPIs, such as cost per interaction, reduction in required human resources (FTE), first-contact resolution rate, average handling time, and payback period. These indicators allow you to quantify savings and continuously optimize customer service efficiency.
The return can be evident in the first few months if you automate high-volume requests and properly monitor adoption. KPIs such as cost per ticket, average handling time, and reduction in required resources help measure the real savings.
The activities with the greatest financial impact include guided technical support, order and return management, customer onboarding, and co-pilot support for operators. Automating these high-volume, low-value areas yields the greatest savings.
