AI is changing the way people work in contact centers, leading to both job cuts and new responsibilities for existing workers.
It’s also creating challenges for customer service leaders.
“Let's not confuse ourselves,” Neville Letzerich, CMO at Talkdesk, said during a panel at Customer Contact Week Las Vegas last month. “This isn't an operating model change, it's a paradigm shift. If you're saying, ‘I'll just throw AI and humans in there together, it's all going to be fine,’ I think you're looking at it the wrong way.”
Workers feel threatened, according to Letzerich. They are worried that AI will take their jobs, and leaders need to carefully consider how they are handling the introduction and expansion of AI in the call center.
A good strategy includes keeping employees informed about potential cuts or new job opportunities, experts say. Leaders will want to avoid looking at AI in all-or-nothing terms — there may be journeys where starting with AI and ending with human support is optimal.
Every leader needs to think about how their AI plans will affect their workforce regardless of how they plan to move forward, according to Nicole Kyle, managing director and co-founder of CMP Research. Navigating skepticism and keeping frontline morale high are essential for continued success.
“Executives are pressed for time,” Kyle told CX Dive. “How do they balance transforming the tech roadmap of CX with handling people-related challenges? The best CXOs and the best customer contact leaders know you have to be aware of both.”
Be clear with workers from the start
Whether jobs are being lost or new opportunities are opening up, it’s essential that companies are transparent with workers about how AI will affect their call center operations, according to Jessica Gupta, COO at InfoPay, a data technology company.
InfoPay began informing its employees about its AI plans about two years before the company even knew whether there would be cuts, says Gupta. Despite this, its communication included acknowledgement that jobs may be affected.
“I was very upfront about the reality that I will not pretend that this won't change the head count that we need, that it won't change the way that we work,” Gupta said. “But we'll go through it together, we'll go through it carefully, and we'll be fair. We were very clear-eyed because we wanted people to have time to prepare.”
Infopay took a very methodical approach, according to Gupta. The company not only helped prepare its team for potential cuts, but took the people it knew would remain following the advent of AI and started having conversations about what their new roles might look like.
For instance, agents who were particularly knowledgeable about certain subjects became part of an analytics project that helped get its AI program up and running, Gupta said. They came on board early in the process as experts on the aspects of the support experience that matter most. As InfoPay added AI features, those employees have continued working on development and testing.
“We did have to release folks — the cost savings aspect is reality — but we've been able to create teams that are now doing exciting things,” Gupta said. “We've given people careers that didn't exist before.”
A major benefit of this approach is that it helps keep morale high as AI becomes a larger part of contact center operations, according to Gupta. Agents know their jobs are changing, but they feel greater ownership over the technology that is causing the shift.
“I think involving them in that process makes it less scary,” Gupta said. “They're gonna be part of that journey with us as we evolve.”
Remember where people are the best fit
Technology is not automatically the answer, according to Bob Sacunas, VP and strategic industry executive at UiPath, an AI solution provider. Humans remain ideal in cases where judgement is necessary.
In some industries it makes sense to start by connecting customers to AI and handing them off to a human not as an alternative, but part of the standard operating protocol, according to Jonathan Rosenberg, CTO at contact center provider Five9.
“Self-service is not a black or white all-or-nothing thing,” Rosenberg said during a panel. “A lot of interesting use cases are actually to have an AI system do initial data collection, triage and then transfer the call purposefully — not because it failed.”
One example is loan applications, according to Rosenberg. AI can efficiently collect the necessary customer information and then hand the call off to a human loan officer who has the judgement and empathy necessary to make the call less stressful for the customer.
“If you focus on the customer and put them at the forefront, it doesn't mean they don't talk to people anymore,” Rosenberg said. “You can realize cost savings, build great CX and make sure your agents still play a role in what matters.”
Older forms of AI have their application as well, according to Sacunas. Agentic AI is best when some level of interpretation is necessary, but simple deterministic AI is often going to be faster, cheaper and more reliable for simple, repeatable tasks.
“The way you avoid this false promise is really to make sure that you're picking the best tool for the job instead of just over-indexing and trying to apply AI to everything,” Sacunas said.
