For years, customer service leaders have focused on how artificial intelligence could improve internal operations. Today, a more disruptive shift is underway: AI is moving to the customer side of the interaction. Consumers and business customers alike are increasingly gaining access to personal AI agents that can research options, initiate service requests, make purchases, place phone calls, and complete complex workflows on their behalf. As customer usage of these personal AI agents increases, this raises significant implications for service organizations.
The emergence of customer-controlled AI agents represents a fundamental change in how organizations engage with customers. Rather than requiring customers to navigate websites, contact centers, or mobile applications themselves, personal AI agents will increasingly act as intermediaries. As these technologies become more widely adopted, customer service organizations should expect a sharp rise in interaction volume, new operational challenges, and growing pressure to support machine-mediated engagement models.
The latest generation of AI agents goes beyond answering questions or generating content. They are designed to execute actions autonomously. Examples of this include the following:
- Meta's Muse, which can complete multistep workflows such as shopping, booking travel, and initiating customer service interactions;
- OpenAI's Dots, which can research information, analyze data, prepare documents, and take actions across applications; and
- Google's Call for Me feature, which can place calls on behalf of consumers to check inventory, make reservations, or manage appointments.
While each platform offers different capabilities, they share a common goal: reducing the effort for customers to accomplish tasks. In practice, this means customers no longer need to personally spend time researching solutions, comparing products, waiting on hold, or interacting directly with service representatives. Instead, they can instruct AI agents to handle those activities on their behalf across many companies.
For customer service leaders, this shift is significant because lower effort could lead to higher demand. When customers can delegate a task in seconds rather than investing their own time and energy, they are more likely to initiate interactions. Over time this will lead to a substantial increase in service requests, inquiries, comparisons, and support engagements.
Customer service and support must now prepare to move beyond self-service toward delegated service. Customers are no longer simply serving themselves through digital channels; they are assigning service activities to autonomous systems that work independently.
The Rise of the AI-First Customer
As adoption grows, organizations will encounter customers who expect AI agents to interact seamlessly with their businesses. In some cases, service organizations are already receiving direct outreach from customers using AI agents and are seeing pressure placed on existing resources as a result.
The implications extend beyond volume. AI-mediated interactions might differ substantially from traditional customer contacts. AI customers can operate around the clock, initiate interactions at scale, and rapidly navigate information and processes. Existing service environments that were designed primarily for human interactions might not be optimized to support this new type of engagement.
As a result, service leaders should begin evaluating whether their current processes, technologies, and operating models can effectively support interactions generated not only by people but also by the AI systems acting on their behalf.
Why Blocking AI Agents Is the Wrong Approach
Faced with the prospect of increased interaction volume and new risks, some organizations might be tempted to restrict or block AI agents from accessing service channels. We advise against broadly blocking customer AI agents. Such an approach could ultimately frustrate customers and encourage them to engage with competitors that are better prepared to support AI-assisted interactions.
Instead, organizations should selectively enable AI-driven interactions while implementing appropriate risk mitigation measures. Service leaders should identify the customer intents and processes most suitable for AI-agent engagement and create frameworks that support those interactions safely and efficiently.
This approach recognizes a practical reality: customer adoption of AI agents is occurring outside organizational control. The decision facing service leaders is not whether customers will use these tools but how effectively their organizations will respond when they do.
Brad Fager is a vice president analyst, and Daniel O'Sullivan, Christopher Sladdin, and Devra Struzenberg are senior director analysts in Gartner's Customer Service and Support Practice.