Customer support is an indispensable aspect of any successful business. However, traditional support methods can be resource-intensive, involving significant human effort and time. As customer expectations soar, companies face mounting pressure to provide 24/7 support, handle complex queries, and deliver personalized interactions. This is where generative AI comes into play, offering an avenue for cost-effective support without compromising on quality.
Let’s consider a hypothetical example of a mid-sized e-commerce company that handles customer support through traditional methods, employing a team of 30 human agents. The company receives an average of 6,000 customer inquiries per day, including common questions, complex queries, and order-related issues. Each customer support agent works an 8-hour shift, and the company provides 24/7 customer support to meet its global customer base.
Let’s calculate the cost-effectiveness of generative AI in the customer support environment step by step for the hypothetical mid-sized e-commerce company.
Step 1: Calculate Traditional Customer Support Costs
- Salaries and Benefits:
– Average annual salary per customer support agent: $45,000
– Number of customer support agents: 30
– Total annual salary expense: $45,000 * 30 = $1,350,000
- Operational Hours:
– To provide 24/7 support, the company needs to cover three 8-hour shifts per day.
– Total number of working hours per day: 3 shifts * 8 hours = 24 hours
- Average inquiries handled per agent per day:
– Total customer inquiries per day: 6,000
– Average inquiries per agent per day: 6,000 / 30 agents = 200 inquiries
Step 2: Estimate Generative AI Implementation and Maintenance Costs
- Generative AI Implementation Cost:
– One-time cost for implementing generative AI, including AI platform integration and training: $150,000
- Annual Maintenance and Updates Cost:
– Ongoing annual cost for maintaining and updating the generative AI model: $50,000
Step 3: Calculate Cost Savings with Generative AI
- Reduced Salaries and Benefits:
– Assuming generative AI can handle 40% of the daily inquiries (2,400 inquiries), leaving 3,600 complex queries to be handled by human agents.
– Total number of inquiries handled by generative AI per day: 2,400 inquiries
– Average inquiries per agent per day (after generative AI implementation): (3,600 inquiries / 30 agents) = 120 inquiries
– Total annual salary expense after generative AI implementation:
– Salary expense for human agents: $45,000 * 30 = $1,350,000
– Salary expense for reduced human agents: $45,000 * 30 * (120/200) = $810,000
– Salary savings due to generative AI: $1,350,000 – $810,000 = $540,000
Step 4: Calculate Net P/L with Generative AI for 3 years
Year 1 | Year 2 | Year 3 | SUM | |
Traditional Support Cost | 1 350 000 | 1 350 000 | 1 350 000 | 4 050 000 |
Reduced Support Cost | 810 000 | 810 000 | 810 000 | 2 430 000 |
AI Implementation Cost | 150 000 | 0 | 0 | 150 000 |
AI Maintenance Cost | 50 000 | 50 000 | 50 000 | 150 000 |
Profit/Loss | 340 000 | 490 000 | 490 000 | 1 320 000 |
The table provides a concise overview of financial metrics related to implementing generative AI in customer support over a three-year period.
- Traditional Support Cost: The cost of conventional customer support remains constant at $1,350,000 annually for each year. The cumulative traditional support cost over the three years is $4,050,000.
- Reduced Support Cost: With generative AI implementation, the support cost reduces to $810,000 annually for each year. The cumulative reduced support cost over three years is $2,430,000.
- AI Implementation Cost: An initial one-time cost of $150,000 is incurred during the first year for implementing the generative AI solution.
- AI Maintenance Cost: An annual maintenance cost of $50,000 is sustained across all three years.
- Profit/Loss: The difference between traditional support costs and the reduced support costs, along with the AI implementation and maintenance costs, results in a profit or loss. The cumulative profit/loss over three years is $1,320,000, reflecting the financial impact of adopting generative AI.
In essence, the table presents a comparative analysis of costs, profit/loss, and the financial implications of implementing generative AI for customer support across a three-year timeframe.