AI to Resolve Half of Service Calls Within 2 Years, Survey Finds
▼ Summary
– 79% of service leaders consider AI agent investment essential to meet business demands, with 50% of service cases expected to be resolved by AI by 2027.
– Service teams face AI adoption challenges including security concerns, talent shortages, and siloed systems, though integrated platforms increase AI success likelihood by 1.4x.
– AI agents are improving efficiency, decision-making, and customer satisfaction, with users anticipating a 20% reduction in service costs and resolution times.
– Conversational and agentic AI are reshaping customer interactions through self-service and seamless human handoffs, while field service AI addresses inefficiencies and safety.
– Human-AI collaboration in service roles enhances productivity, job satisfaction, and skill development, with 83% of service reps reporting better career prospects due to AI.
A new industry survey reveals that artificial intelligence is poised to handle half of all customer service inquiries within the next two years, marking a dramatic acceleration in the adoption of automated support systems. This rapid integration reflects a broader shift toward AI-driven efficiency, cost reduction, and improved user experiences across the service sector.
According to recent research drawing from insights provided by over 6,500 service professionals globally, four out of five service leaders now consider investment in AI agents essential for keeping pace with rising business demands. The mounting pressure to deliver higher-quality customer interactions, coupled with persistent talent shortages and operational constraints, has made AI adoption not just advantageous but necessary for competitive survival.
Service teams today confront a complex array of challenges, including meeting elevated customer expectations, managing higher operational costs, and overcoming difficulties in hiring and retaining skilled staff. A striking 82% of service professionals acknowledge that customer standards are significantly higher than in previous years. At the same time, service representatives report spending less than half of their time actually engaging with customers, with the remainder absorbed by administrative duties and internal tasks.
This operational inefficiency carries a real cost: 43% of consumers say that a single poor service experience will deter them from making future purchases. In this high-stakes environment, AI offers a promising solution. However, adoption is not without its hurdles. Security concerns represent the foremost challenge, with more than half of service leaders citing fears over data protection as a factor that has delayed or limited AI initiatives. Additional barriers include questions around AI accuracy, a shortage of in-house expertise, high implementation costs, and resistance from some customer segments.
Integration emerges as a critical factor for success. Organizations that consolidate their service channel data within a unified platform are 1.4 times more likely to rate their AI implementation as highly successful compared to those working with fragmented systems. A full 88% of service leaders are now prioritizing technological integration to support their AI strategies.
The term “AI agent” encompasses predictive, generative, and agentic AI systems designed to deliver faster, more accurate, and personalized customer interactions. Currently, 69% of service organizations use at least one form of AI, with 39% already implementing agentic AI. The benefits are tangible: companies using AI agents anticipate an average 20% reduction in both service costs and case resolution times.
Perhaps most importantly, the future of customer service is shaping up to be a collaborative effort between human agents and AI. This partnership doesn’t replace people, it empowers them. Eighty-three percent of service representatives working alongside AI report better career prospects, while 82% say it has helped them develop new skills. They also note higher productivity, reduced stress, and greater job satisfaction.
Looking ahead, service professionals predict that AI will resolve 30% of cases by 2025, climbing to 50% by 2027. Common use cases include handling frequently asked questions, managing order inquiries, summarizing conversations, retrieving knowledge for human agents, and offering personalized product recommendations.
Field service technicians also stand to gain significantly, estimating that AI could automate 35% of their administrative workload, saving an average of 14 hours per week.
For organizations charting their path forward, the research outlines a maturity model for agentic AI, progressing from basic knowledge retrieval to transactional reasoning and eventually full system orchestration. This evolution promises to transform customer service from good to great, enabling fully autonomous handling of routine issues while providing intelligent support for more complex human-led interactions.
(Source: ZDNET)
