We know that companies right now are heavily investing in customer service technologies with embedded artificial intelligence. This is because AI is really good at making operations more efficient, like summarizing customer history, guiding reps through process flows, surfacing knowledge and next-best actions, or automating post-call wrap-up work. This frees up reps to better engage with customers to deliver great customer experiences.
Of course, the more you automate your customer service operations, the more you will have to rethink your team structures and skills. You will have to work through questions like What customer service roles will change? How will they change? What will staffing look like two years from now, or five years from now? And what new skills do I need to plan for?
You also have to understand what the U.S. customer service labor market looks like today. I tried to do this by diving into data from several sources, including the database sponsored by the U.S. Department of Labor (the primary source of occupational information in the United States) as well as data from the U.S. Bureau of Labor Statistics to track the demand for customer service jobs within different industries and growth in salaries.
Here are some of our findings:
- Customer service job postings, already in decline, will contract even more. According to Indeed Hiring Lab data published via the U.S. Federal Reserve Economic Data database, U.S. customer service job postings are now roughly 10 percent below pre-pandemic levels. This decline stands in sharp contrast to overall U.S. job postings, which remain above pre-pandemic levels. This means that the customer service industry is under-hiring relative to the broader economy.
- Customer service salaries are stagnating. Salary growth for customer service jobs has stagnated since May 2025. Customer service salaries are significantly smaller than average across all operations. Customer service wages have shown modest but uneven growth since 2020. Since 2023, wage growth has slowed back to low single digits as hiring demand stabilizes and automation reduces pressure to expand headcount.
- Companies invest in AI over customer service headcount. Indeed's sector-level data shows that customer service job postings continue to lag compared to all other U.S. job postings. This indicates that there is a continued reduction in customer service hiring rather than a temporary freeze because of the economy. In addition, signals indicate that companies are hiring technologists to automate service work instead of adding incremental customer service reps.
- AI decouples customer service inquiry volumes from headcount growth. The need for customer service is not going away. AI is now handling more of the customer service work. It means that customers can get faster and better answers from self-service and from customer service reps that are assisted by AI.
- AI changes the nature of work in customer service organizations. Tactically it means that organizations need fewer entry-level roles. However, they need more reps with specialized skills to handle the more complex and more empathy-heavy work. They also need front-office staff with technical skills to help create automations, supervise AI, and optimize AI. They need front-office staff that can extract insights from conversations and do complex root-cause analysis.
- Beware! Estimates for job shrinkage are all over the place. Many customer service organizations will not reach a high degree of automation. They won't be ready to automate workflows where regulatory, safety, or financial liability is involved, as the cost of failure is high. Others won't have knowledge available or integrations to back-office systems. Some industries will also have process variability where exception-handling logic is harder to automate.
AI will reshape every aspect of your customer service operations. You must understand the skills for each job to be done. Think through what your staffing levels will be as you automate more and more customer inquiries. Think through how you will reskill and upskill your reps, your organizational structures, and the organizational ownership of AI operations.
Kate Leggett is a vice president and principal analyst at Forrester Research.