The Most Valuable AI Use Cases for Customer Service and Support
Across industries and company types, senior executives are pressuring service and support leaders to leverage artificial intelligence in their operations and are even allocating budget to it, Gartner found in a recent survey.
In fact, 77 percent feel the pressure, and 75 percent report increased budgets for AI initiatives compared to last year. And the typical leader is planning to add five new full-time-equivalent roles in the next 12 months to manage these investments.
Vendors are scrambling to meet the demand for AI, Gartner adds, citing “a mad dash of feature availability across big suites as well as new players building AI-native products to compete with the established competitors.”
“Service and support leaders are looking to AI for a wide variety of goals—efficiency, better [customer experience] lead generation, and delivering other value back to the business,” says Keith McIntosh, senior research principal in the Gartner Customer Service & Support practice. “The most impactful use cases are fourfold: those that enable assisted agents, empower customers through self-service, automate operational support, and introduce agentic AI across their stack.”
Gartner’s four basic use cases for AI are as follows:
1. Agent enablement. AI-powered agent assist tools can provide generative AI-driven content summaries, quick answers, real-time customer data insights, and next-best-action recommendations, saving agents significant time without compromising accuracy. They enable agents to deliver more personalized, effective support by allowing them to focus on connecting with customers instead of spending time searching for answers. They also help avoid the need for customers to repeat themselves.
2. Low-effort self-service. AI-enabled chatbots, intelligent virtual assistants, and advanced search capabilities provide customers with high-quality answers quickly and independently using natural language and without having to sift through mountains of resources. These AI tools not only enhance customer satisfaction by providing immediate answers but also reduce the volume of routine inquiries reaching human agents.
3. Automation of operation support. AI helps service organizations increase efficiency in analytics, knowledge management, and quality assurance.
Of these, Gartner says customer service analytics is the most valuable AI use case, allowing nontechnical users to sift through mountains of data using natural language conversation. These tools can also look at the solutions agents provide to customers, identify whether other content related to that query already exists, and then generate additional relevant self-help content, which can be reviewed by a knowledge expert before it is published.
AI helps with quality assurance by analyzing customer contacts across channels to examine whether human or AI agents followed the required processes or issued the appropriate reminders.
AI can also automate workflows in a wide variety of service and support domains and even enable applications to take actions on users’ behalf. By automating repetitive tasks and providing actionable insights, these tools help organizations optimize resource allocation, maintain consistency, and scale their operations efficiently, Gartner concludes.
4. Agentic AI. Emerging agentic AI solutions are taking automation a step further by autonomously handling complex workflows and multi-step service requests. This new class of AI is poised to transform both employee-facing and customer-facing functions, potentially driving significant efficiency gains and enabling new service delivery models.
“Organizations that prioritize these high-impact use cases will be best positioned to achieve operational excellence, deliver superior customer experiences, and stay ahead in the rapidly evolving AI landscape,” McIntosh adds.