Artificial intelligence has a lot of promise, but many service leaders are making a costly mistake: over-focusing on AI's potential for headcount reduction and not enough on AI's potential to transform the workforce. The organizations that get the most value from AI will not simply automate more, they will better prepare their people for the different-in-kind work they'll perform after seeing automation success.
That distinction matters because AI has the potential to change the nature of customer interactions. When routine contacts are automated, the issues that reach human agents will become more complex, more emotional, and more consequential. In this environment, agents need to move beyond basic problem-solving toward value delivery. They must interpret customer needs, apply judgment, and in some cases even identify revenue opportunities. Service organizations that fail to proactively upskill for this shift risk operational disruption and declining customer experience, even if their technology investments are sound.
Upskilling employees on how to drive value is critical for the future success of the service and support organization and the broader enterprise. Customers who perceive value in service interactions are significantly more likely to repurchase, yet only a relatively small share of customers say they consistently receive that kind of value today. That gap should be a wake-up call for service leaders. AI can help reduce friction and improve productivity, but productivity alone does not create loyalty. If organizations want service to become a driver of growth rather than just a cost center, they must equip agents to create value in every interaction.
The challenge is that traditional training models, like classroom sessions or static online modules, are not built for this level of change. That approach is too slow, too brittle, too difficult to scale, and too operationally disruptive. Instead, organizations need a more modern upskilling strategy that helps employees learn and reinforce skills at scale, in the flow of their work.
AI-powered training simulations can create realistic, dynamic practice environments, enabling upskilling at scale without taking the workforce offline. Agents engage in simulated conversations that mirror authentic customer scenarios, powered by conversational AI and real operational data. These platforms provide immediate feedback and performance scoring, allowing agents to safely practice complex interactions and new workflows before engaging with live customers.
At the same time, attempting to train agents on everything is a mistake. Instead, leaders should consider how to supplement needed skills with technology. That support can take several forms: Desktop enablement tools can surface the right context at the right time, reducing the burden on memory and helping agents focus on the human side of the interaction. Agent-assist tools can provide real-time prompts, next-best action recommendations, and behavioral guidance during live conversations. These technology solutions reduce the need for employees to memorize constantly evolving procedures, policies, and product details and instead focus on developing skills that are not programmable, like relationship-building or advocacy.
And finally, to support their upskilling efforts, leaders need to measure the right outcomes. Traditional service metrics such as average handle time are not enough to assess whether employees are succeeding in an AI-enabled environment. Organizations need better ways to evaluate whether agents are demonstrating new skills, improving customer outcomes, and contributing to broader business goals. AI-powered quality assurance and coaching tools can help by analyzing interactions at scale, identifying skill gaps, and giving supervisors more targeted insight into where coaching is needed. But even with better technology, human coaching remains essential. Managers must be trained to reinforce new behaviors and encourage lasting behavioral change.
The winners in customer service's AI era will not be defined by how aggressively they automate. They will be defined by how effectively they combine automation with human capability. AI might reduce the volume of simple interactions, but it raises the stakes on every interaction that remains. That means the future of service depends not only on smarter technology but on smarter investment in the workforce. Leaders who prioritize upskilling now will be better positioned to improve customer outcomes, strengthen loyalty, and turn service into a more strategic engine of value.
Kathy Ross is a vice president analyst at Gartner. Emily Potosky is a senior director analyst at Gartner.