{"id":13551,"date":"2026-07-10T10:19:23","date_gmt":"2026-07-10T10:19:23","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=13551"},"modified":"2026-07-10T10:19:24","modified_gmt":"2026-07-10T10:19:24","slug":"unlocking-power-of-agentic-ai-for-customer-service","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/eu\/blog\/unlocking-power-of-agentic-ai-for-customer-service\/","title":{"rendered":"Unlocking the Power of Agentic AI for Customer Service"},"content":{"rendered":"\n

Organisations rushed to pilot generative AI chatbots and case summarisation tools to support customer service. Small and medium-sized businesses felt the efficiency gains the most \u2013 they could finally offer scaled customer support with relative ease \u2013 but today, there\u2019s a new paradigm for AI in customer service<\/a>.<\/p>\n\n\n\n

In 2026, the focus is agentic service, <\/em>powered by teams of AI agents<\/a> independently taking action alongside human service representatives.<\/p>\n\n\n\n

Customer experience (CX) chiefs are on board. According to our latest State of Service Report<\/a>, nearly eight in 10 service leaders (79%) believe investing in AI agents is fundamental to meeting today\u2019s business demands.<\/p>\n\n\n\n

It\u2019s all a part of the dawn of the Agentic Enterprise<\/a>, where autonomous agents<\/a> are embedded in service teams to reason, plan, and solve customer challenges.<\/p>\n\n\n\n

Our research found that organisations are pulling ahead by building a seamless ecosystem of human and AI service agents, backed by a single, unified data strategy. Here\u2019s what you need to know about AI\u2019s evolving role in customer service.<\/p>\n\n\n\n

The autonomous agent is the new service MVP<\/strong><\/h2>\n\n\n\n

Generative text tools captured the early headlines, and for a brief window, were the only AI-powered customer service solution that organisations were willing to invest in. But the technology has evolved, and so has AI maturity within the business.<\/p>\n\n\n\n

Currently, 69% of service professionals report that their organisation uses at least one form of AI, and 39% say they\u2019re deploying autonomous agents.<\/p>\n\n\n\n

Unlike generative chatbots, autonomous agents use advanced reasoning to execute tasks independently, such as processing a return or offering hyper-personalised product recommendations based on a customer’s purchase history.<\/p>\n\n\n\n

Our State of Service: AI Agents Edition<\/a> research revealed that service teams using AI agents are largely deploying them in both customer-facing and internal capacities. Popular use cases on the customer side include proactive outreach, personalised product recommendations, and multichannel case resolution.<\/p>\n\n\n\n

From an operational perspective, teams are using agents to handle case routing and knowledge retrieval.<\/p>\n\n\n\n

The commercial potential is profound. Service leaders expect agents to deliver an average 20% reduction in service costs, 20% reduction in case resolution times, and a 20% reduction in customer wait times.<\/p>\n\n\n\n

Leaders who fail to integrate autonomous agents risk being outpaced by competitors operating at greater speed for a fraction of the cost.<\/p>\n\n\n\n

Strong data foundations power successful service agents<\/strong><\/h2>\n\n\n\n

One large blocker is preventing organisations from rushing to agentic AI. AI agents for customer service are only as smart as the data that powers them, and at many firms, that data lacks clarity and quality. <\/p>\n\n\n\n

Nearly half of service leaders (44%) admit that fragmented systems and tech silos within their organisations have delayed or limited their AI projects.<\/p>\n\n\n\n

Our findings prove that a strong foundation breeds success. Organisations that integrate their service channel data into a single, unified platform are 1.4x more likely to rate their AI implementations as \u201cvery successful\u201d compared to those stuck with disparate systems.<\/p>\n\n\n\n

Another part of the challenge is the multimodal nature of modern customer service, spread between voice, text, chat, and visual inputs. To turn these touchpoints into natural conversations, true multimodal AI must be able to handle all kinds of output within a singular architecture.<\/p>\n\n\n\n

Currently, 88% of service leaders are prioritising tech integration to support AI initiatives. A unified data foundation is key to stopping AI systems from hallucinating or losing sight of the full customer context.<\/p>\n\n\n\n

For instance, if a customer has exchanged a faulty device at a retail store, only for a siloed email agent to send a \u201creturn overdue\u201d notification an hour later, the customer\u2019s experience suffers.<\/p>\n\n\n\n

Gaps in data integration can turn a smoothly executed resolution into a friction point that alienates the buyer \u2013 and needlessly extends their service interaction. Good data is a prerequisite for good agentic service.<\/p>\n\n\n\n

Eliminate silos and build a future-proof data foundation for your agents with Data 360<\/a>.<\/em><\/p>\n\n\n\n

The service rep\u2019s new value proposition<\/strong><\/h2>\n\n\n\n

Agents equipped with full customer context can hugely accelerate service workflows. Unfortunately, their potential is leading some CX professionals to pull back from agentic service out of fear they\u2019ll be replaced. <\/p>\n\n\n\n

Autonomous agents aren\u2019t a threat to human service departments. In fact, our data shows they can help frontline workers avoid burnout.<\/p>\n\n\n\n

Most service professionals (82%) agree that customer expectations are higher than ever. Yet, the average representative spends less than half of their week (46%) actually working with customers. The rest of their time is consumed by low-value tasks, including:<\/p>\n\n\n\n