Every few months, another company makes headlines for cutting its customer service team and going all-in on AI.
And every few months, a chunk of those same companies quietly start hiring people back.
Gartner isn’t guessing on this one. They predict that half of the companies that attributed customer service headcount cuts to AI will be rehiring for similar functions, under different titles, by 2027.
If you’ve been holding off on your call center hiring plans because you weren’t sure AI was about to make the whole conversation moot: it’s not. But it is about to change who you should be hiring.
The Rehiring Wave Nobody Saw Coming (Except Gartner)
Gartner’s Customer Service & Support practice surveyed more than 300 service leaders in late 2025 and found something that cuts against the headlines: only 20% had actually reduced agent staffing due to AI.
Most recent workforce reductions were influenced by broader economic conditions rather than automation alone, according to Gartner. AI just made for a cleaner press release.
Here’s the part that matters for your Southern California hiring plans: Gartner’s own analysts predict that half of the companies that did cut service staff and blamed AI will rehire people into similar roles by 2027, just with different job titles.
Their reasoning is straightforward — AI still isn’t mature enough to fully replace the expertise, empathy, and judgment a human agent brings to a genuinely messy customer problem.
Klarna’s the most public example. After making headlines for aggressively shifting customer service work toward AI, the company later acknowledged the limits of an AI-first approach and began bringing humans back into the customer support process.
It’s a pattern other companies are quietly repeating without the headline.
Case Studies: Customer Service Staffing Wins
What AI Actually Does Well in a Call Center
To be fair to the technology: AI has earned its place in the contact center. It’s genuinely good at:
- Handling routine, repetitive requests like password resets, order status, appointment changes
- Deflecting simple tier-1 volume so agents aren’t burning hours on things a bot can solve in seconds
- Surfacing real-time information and suggested responses to agents mid-call, so newer hires ramp up faster
- Flagging quality and coaching signals for supervisors without someone manually reviewing every call
None of that is nothing. It’s just not the whole job.
What It Still Can’t Do
The requests that make customers actually call instead of clicking through a self-serve flow, tend to be the messy ones: billing disputes, service failures, something that doesn’t fit the script, a customer who’s genuinely upset.
That’s the work that still needs a human who can read the room, exercise judgment, and make a call that isn’t in the decision tree. It’s also the work that determines whether a customer stays a customer.
Do You Still Need Call Center Staff With AI?
Yes. AI can handle more routine customer service work, but companies still need human CSRs.
The bigger shift is in who you need to hire. As AI absorbs more routine volume, your human agents will spend more of their time handling the complex calls that require judgment, empathy, and problem-solving.
Skills To Look For When Hiring AI-Assisted CSRs
Gartner’s latest research points in the same direction: 84% of organizations plan to add new skills to frontline positions, while nearly 80% plan to shift at least some agents into new roles.
That’s the new hiring bar: not do you still need people, but what makes a great hire now.
The CSRs and call center reps you hire spend a bigger share of their day on the harder conversations. That changes what you should be screening for:
- Judgment under ambiguity: comfort making a call when there’s no script for it
- Emotional intelligence: reading tone and de-escalating, not just following a flowchart
- Comfort working alongside AI tools: using agent-assist suggestions without being thrown off by them
- Resilience: a heavier share of the calls they take will be the hard ones, by design
That’s a different candidate profile than “can follow a script and hit average handle time.” It’s also a smaller pool to recruit from, which is exactly why speed and a strong sourcing pipeline matter more, not less, in this environment.
And in California, finding those candidates can be especially tough. The state’s labor force has been shrinking, which means employers are competing for fewer people who can handle the judgment, emotional intelligence, and problem-solving these AI-era customer service roles demand.
Why Flexible Staffing Is the Smart Move Right Now
Here’s the trap a lot of companies fell into: they treated the AI rollout as a permanent headcount decision on day one, and now they’re the ones predicted to rehire…after a round of layoffs, a service quality dip, and a reputational hit nobody enjoyed.
A flexible staffing model reduces that risk. Instead of locking in a permanent headcount while AI tools are still being tuned, companies can adjust their staffing as they learn what their operation actually needs, without the PR story that comes with getting it wrong in either direction.
“What I’m hearing from clients is that they’re trying to figure out the right balance,” says Kristina Hayden, Helpmates’ Chief Operating Officer. “They know AI is going to change how their customer service teams work, but they’re still figuring out what that means for the people they need today.
“Some are hesitant to commit to permanent hires when they know the work could look different six months from now. At the same time, they can’t afford to leave customers waiting because they cut too deeply. That’s where flexible staffing can really help.”
If you’re not sure what your customer service team should look like on the other side of your AI initiative, contact Helpmates. We’ll help you staff for where things are right now, without locking in a headcount you might regret in six months.
