AI will significantly reshape frontline roles, with more than 80% of organizations planning to expand human agent responsibilities.

Customer service and support leaders are facing increased executive expectations to invest in AI, according to a survey by Gartner. Ninety-one percent of service and support leaders surveyed reported pressure from executive leadership to implement AI — marking a sharp increase in urgency for AI-enabled transformation.

The survey of 321 customer service and support leaders conducted in October 2025 found leaders identified improving customer satisfaction, operational efficiency, and self-service success as their top priorities for 2026. Many are now turning to AI to support first-contact resolution, reduce customer effort, and guide customers through more seamless service journeys, evolving beyond traditional use cases focused solely on back-office efficiency.

Service organizations are entering a period where AI and human expertise must work in tandem. Organizations are not simply deploying AI technologies; they are redesigning service models to ensure that technology enhances the customer experience while human agents continue to provide context, empathy, and judgement during more complex interactions.

Frontline Roles Are Evolving Alongside AI Adoption

Service and support leaders also expect to significantly reshape frontline roles, with nearly 80% of organizations planning to transition at least some agents into new responsibilities. This shift is being driven by the expected automation of routine tasks and the growing need for human expertise in complex or emotionally sensitive interactions. Additionally, 84% of leaders plan to add new skills to the agent role and adjust hiring profiles to support this transformation.

As organizations continue scaling self-service capabilities, leaders are also prioritizing improvements in knowledge management. The survey showed 58% of service leaders aim to upskill agents into knowledge management specialists, acknowledging the need for accurate and continually updated content to support both AI systems and customer self-service interactions.

The findings reflect a broader shift within customer service operations, where AI adoption is increasingly tied to customer experience outcomes rather than solely cost reduction initiatives. Organizations are placing greater emphasis on balancing automation with human engagement to improve service quality, strengthen operational efficiency, and deliver more personalised support experiences.

AI investments are also becoming more closely aligned with long-term workforce planning. As automation handles repetitive processes, organizations are reassessing how frontline teams can contribute higher-value expertise across customer interactions. This includes supporting escalation management, resolving emotionally sensitive cases, maintaining knowledge ecosystems, and ensuring service continuity across digital and human-assisted channels.

The growing reliance on AI-driven customer support systems is accelerating the demand for adaptive workforce models. Service leaders are increasingly expected to modernise operations while maintaining customer trust and service consistency. As a result, organizations are investing in training, skills development, and operational redesign to ensure employees can work effectively alongside AI-powered systems.

The survey findings further indicate that AI adoption within customer service environments is no longer viewed as a future initiative but as an immediate operational priority. Executive leadership teams are applying increased pressure on service departments to demonstrate measurable value from AI initiatives, particularly in areas such as efficiency gains, customer satisfaction improvements, and self-service optimisation.

Organizations expanding AI within service operations are also recognising the importance of maintaining high-quality data and knowledge management frameworks. Accurate information repositories are becoming essential to enabling AI systems to deliver relevant responses and consistent customer experiences. This is contributing to a growing focus on knowledge governance, content accuracy, and continuous information updates across support ecosystems.

As customer expectations continue evolving, organizations are expected to further integrate AI technologies into frontline operations while redefining the role of human agents. The future service model increasingly depends on collaboration between intelligent automation and skilled human professionals capable of delivering empathy, contextual understanding, and complex decision-making.