CS & Support in the AI Era
Customer support is changing quickly.
AI can now summarize tickets, suggest replies, route issues, update help centers, and automate simple requests. But customers still want people when the situation is complex, sensitive, or frustrating.
That is the new challenge for support leaders: hire people who can use automation without losing the human side of service.
Gartner reported that 91% of customer service leaders are under pressure to implement AI in 2026, while more than 80% of organizations plan to expand human agent responsibilities. Gartner, Customer service AI survey
That means support roles are not disappearing. They are becoming more demanding.
What AI changes in support
AI is useful for repetitive, high-volume work.
It can help with:
Ticket routing
First-draft replies
Knowledge-base suggestions
Conversation summaries
Sentiment detection
Customer history review
Help-center search
Chatbot handoffs
Quality monitoring
Reporting trends
This can redce manual work and help agents move faster.
But speed alone is not the goal. The goal is better service.
Customers still need human access
AI can help, but companies should be careful not to trap customers in automation.
Gartner found that 87% of customers say companies using generative AI for customer service must provide access to a human agent. Gartner, GenAI customer service human agent access
That is an important hiring signal.
The best support candidates know when to automate and when to step in personally.
Hire for judgment, not just friendliness
Friendly support is useful. Judgment is more valuable.
A strong support hire can decide:
Is this a simple issue or a high-risk case?
Should the chatbot handle it or should a person take over?
Does this reply actually answer the customer’s question?
Is the customer upset because of the product, the process, or the communication?
Does this issue point to a larger product problem?
AI can help surface information. The person still has to make the call.
Interview questions to ask
Use practical questions like:
“How would you use AI to handle a high ticket volume day?”
“When should a support agent avoid sending an AI-drafted reply?”
“How do you know when to escalate a customer issue?”
“Tell me about a time you improved a support process.”
“How would you turn repeated customer questions into help-center content?”
“What customer information should never be entered into an AI tool?”
Good answers will be specific and careful.
Test with real support scenarios
A short work simulation can reveal a lot.
Give the candidate:
A messy customer ticket
A short product context
A draft AI response
A few help-center notes
Ask them to improve the response, explain what they changed, and identify whether the issue should be escalated.
You are looking for clarity, empathy, accuracy, and judgment.
Nearshore support can be a strong fit
Nearshore customer support talent can work especially well for US companies because time-zone overlap supports live service coverage, faster escalation, and closer collaboration with product and operations teams.
For many roles, the right LATAM candidate can provide:
Strong English communication
US-hours availability
Customer service experience
Tool fluency
Process discipline
Cultural familiarity with US customers
The key is to hire for communication and ownership.
The practical takeaway
AI is raising the standard for customer support.
The best support hires can serve customers and improve the system at the same time. They know how to use automation to reduce repetitive work, but they do not let automation replace judgment.
Hire people who can write clearly, think carefully, protect customer trust, and make the support operation better every month.
At Crossbridge, we can help you find great nearshore customer support talent who combine human judgment with AI-powered efficiency. We’ve been building high-performing teams for over twelve years, and we know how to identify and vet the right candidates. See how we do it.