Tech

The Real ROI of an AI Virtual Assistant: Calculating Savings in Technical Support

Angel Niño

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The Real ROI of an AI Virtual Assistant: Calculating Savings in Technical Support

Artificial intelligence is no longer an experimental technology, but a real and proven way to enhance business processes. According to data from SparkCo in 2025 , strategic use of AI increases productivity by 40%.

Any area of your business can be accelerated with artificial intelligence, including customer support. With the right implementation, the ROI of an AI-powered virtual assistant can help unlock growth across other areas of your organization. Here’s the breakdown.

Fixed Costs of a Human Support Team

Direct Talent Costs

Salaries are the most visible cost, but the TCO (total cost of ownership) of a support agent includes taxes, benefits, paid time off, absences, and annual salary increases.

Let’s use the United States as an example. According to Built In , the average annual salary of a customer support representative in the U.S. is USD 54,715. When benefits and labor costs are added, this figure typically rises to USD 65,000–75,000 per year.

Now imagine you have a team of 10 support agents:

  • Average base salary: USD 54,000/year per agent → USD 540,000/year.
  • Benefits, taxes, and insurance: +USD 175,000/year.
  • Bonuses, overtime, and after-hours coverage: +USD 50,000/year.

This means that a relatively small human support team (10 people) can cost around USD 765,000 per year in direct talent alone—before considering infrastructure, tools, and training.

Operational Expenses and Infrastructure

Payroll is only part of what it takes to maintain a human support team. You must also sustain the environment in which that team operates:

  • Office space.
  • Equipment.
  • Software licenses.
  • Security.
  • Connectivity.

Even with hybrid or remote work models, organizations still incur costs for workstations, software, VPNs, collaboration tools, and ticketing platforms.

Returning to our example of 10 support agents:

  • Workstations (laptop, monitor, headset, furniture): USD 2,500 per person → USD 25,000/year.
  • Software licenses: USD 200/month per agent → USD 24,000/year.
  • Office space and administrative overhead: USD 48,000/year.

In infrastructure and operations alone, this hypothetical team adds roughly USD 80,000 per year on top of talent costs, bringing the total to USD 845,000 annually so far.

Employee Turnover Costs

Technical support is one of the departments with the highest turnover rates. According to Insignia Resources , turnover typically ranges between 30% and 45%, with some sources reporting figures as high as 50%.

Turnover introduces constant costs related to recruiting, onboarding, and ramp-up time. Each lost agent represents the cost of replacement, training, and reduced initial productivity.

For this team, annual turnover costs can easily range between USD 30,000 and USD 45,000. At this point, the total cost of maintaining a human support team approaches USD 900,000 per year.

How AI in Support Drives Efficiency and Customer Satisfaction

AI-powered chatbots have rapidly expanded across customer service centers worldwide. According to data from Zuper , only 35% of organizations used AI in 2022. Today, that figure has reached 83%.

Profitability is one of the main factors CTOs evaluate when investing in this technology. Master of Code reports that 28% of business leaders view AI as an effective way to reduce customer support costs.

Faster Response Times

Reducing response time is the foundation of modern support experiences—customers expect answers in seconds, not hours. Meetchatty reports that AI can reduce first-response times by 37%.

  • Autonomously resolve 20%–40% of first-level inquiries.
  • Maintain 24/7 availability and improve SLA compliance during traffic spikes.

Customer Feedback Analysis

An investigation by Zonka found that 81% of CX leaders consider AI-powered feedback analysis a critical priority for the next 12 months.

More Personalized Support Experiences

Data from Salesforce shows that 81% of customer service professionals believe users now expect far more personalized interactions— an expectation AI is uniquely positioned to meet.

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