Calculate the AI ROI for your customer service

Discover the savings that AI can generate for your customer service.

Access the calculator

Discover your potential savings with AI.

Access the calculator

Discover your potential savings with AI.

Calculate the ROI that AI can generate for your customer service.

Based on the studies from McKinsey, BCG, and Bain, this simulator provides you with a concrete estimate of the time and savings that AI can generate. Simply indicate the number of agents and their hourly cost.

Based on studies from McKinsey, BCG and Bain, this simulator provides you with a tangible estimate of the time and savings that AI can generate. Simply specify the number of agents and their hourly cost.

This simulator, based on studies by McKinsey, BCG, and Bain, provides you with a concrete estimate of time and costs that can be optimized. Simply enter the number of agents and their hourly rate.

👥 Nombre d'agents💶 Coût horaire moyen (€)

🕒 Temps économisé

15 heures / semaine

💰 Économies estimées

≈ 1,500 € / mois

≈ 9,000 € sur 6 mois

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⚠️ Les résultats sont des estimations indicatives basées sur des études (McKinsey, BCG, Bain). Ils ne constituent pas un engagement contractuel.

📚 Sources & Methodology

The results provided by this simulator are based on a synthesis of data from benchmark studies published between 2023 and 2025. They aim to illustrate the potential gains offered by artificial intelligence in the realm of customer service, without constituting a contractual commitment.

🔍 Sources Used

McKinsey & Company (2023)
The Economic Potential of Generative AI
The study estimates that between 30% and 45% of customer service tasks are technically automatable thanks to generative AI. The simulator adopts a conservative assumption of 20%, reflecting a realistic short-term automation level.
👉 Read the Study

Bain & Company (2025)
Retail Efficiency Rewritten
Bain observes a reduction in operational costs ranging from 17% to 38% among companies that have integrated AI solutions. The simulator uses a weighted average of 28% to reflect a realistic ROI in a customer service context.
👉 Read the Analysis

Boston Consulting Group – BCG (2024)
AI at Work: Friend or Foe?
According to BCG, AI can enable up to 5 hours of weekly savings per agent. The calculator uses a cautious estimate of +3 hours per week, corresponding to a common situation of gradual deployment.
👉 View the Report

📚 Sources & Methodology

The results provided by this simulator are based on a synthesis of data from benchmark studies published between 2023 and 2025. They aim to illustrate the potential for gain offered by artificial intelligence in the field of customer service without constituting a contractual commitment.

🔍 Sources Used

McKinsey & Company (2023)
The economic potential of generative AI
The study estimates that between 30% and 45% of tasks related to customer service are technically automatable thanks to generative AI. The simulator adopts a conservative hypothesis of 20%, reflecting a realistic level of automation in the short term.
👉 Read the study

Bain & Company (2025)
Retail Efficiency Rewritten
Bain notes, in companies that have integrated AI solutions, a reduction in operational costs ranging from 17% to 38%. The simulator relies on a weighted average of 28% to reflect a realistic ROI in a customer service context.
👉 Read the analysis

Boston Consulting Group – BCG (2024)
AI at Work: Friend or Foe?
According to BCG, AI can enable up to 5 hours of weekly savings per agent. The calculator uses a conservative estimate of +3 hours per week, corresponding to a common scenario of gradual deployment.
👉 See the report