AI Assistants and the Future of Customer Service

AI Personal Assistants and the Future of Customer Service (2026 Trends)

By Gennadiy Bezko, CEO of MiaRec

Executive Summary: Welcome to the future! The age of consumer-controlled AI is here, and it’s reshaping the front lines of customer experience. Within months—not years—personal AI agents like ChatGPT, Gemini, and Claude will become the first point of contact between people and brands. Customers will no longer navigate websites or sit on hold—they’ll simply instruct their AI to handle it. This seismic shift will challenge every assumption in CX: who initiates the conversation, how service is delivered, and what human interaction is truly worth. As AI agents become more autonomous and privacy-preserving, companies must pivot fast—offering clean integration points, rethinking channel strategy, and embracing the idea that the next “customer” isn’t a person, but a machine acting on their behalf. In this article, we map out the road ahead for CX leaders and explain why the real advantage now lies in speaking fluently to AI.

The call center and customer service landscape is on the cusp of a major transformation. Starting in 2026, generative AI and personal assistant technologies are expected to redefine how consumers interact with businesses. Instead of dialing phone numbers, waiting on hold, or typing into company-provided chat widgets, many customers may simply ask their own AI assistant to handle the task. This shift—from traditional human-to-business communication to AI-mediated interactions—will fundamentally change how service is initiated, delivered, and experienced.

The Rise of ChatGPT-like Interfaces as Primary Channels

Consumers may soon rely on personal AI assistants to interact with businesses on their behalf. In recent years, large language model (LLM) chatbots—like ChatGPT, Google’s Gemini, and Anthropic’s Claude—have demonstrated impressive conversational fluency and growing task execution capabilities. These AI interfaces are set to become the primary communication channel between customers and companies, gradually replacing traditional options like phone calls, emails, and even manual website navigation.

Instead of contacting support directly, a customer might simply say, “Please cancel my flight next Tuesday and book me on an earlier one,” and their AI assistant will handle the task—whether through an API, email, web automation, or chat. This is more than convenience. It’s a fundamental shift in customer behavior: from navigating channels to delegating outcomes.

The same shift extends to digital commerce and information search. Rather than browsing a site or comparison shopping manually, a user’s personal AI will scan options, remember preferences, and execute purchases. Major tech firms—Apple, Google, Amazon, Meta, OpenAI—are racing to build the go-to personal assistant for daily life. As a result, the “chatbot” is evolving into an AI agent deployed not by businesses, but by consumers.

Customer-Owned AI Assistants vs. Company Chatbots

A critical distinction lies in ownership and control. Today, companies offer their own chatbots or self-service tools to manage customer support. But in the emerging model, customers will increasingly use their own AI to interface with brands. These personal agents will act as trusted intermediaries—leveraging user context, preferences, and history to deliver highly personalized service.

To support this, businesses will need to adapt. Forward-looking organizations are beginning to design standardized APIs or machine-friendly interfaces to support direct AI-to-system interactions. These “machine customer protocols” (MCPs) will enable a customer’s AI to, for instance, reschedule a flight, check an order status, or cancel a subscription without human intervention.

Where such integrations are unavailable, AI assistants will resort to fallback methods: generating structured emails, navigating websites like a human, and completing transactions using web forms. Emerging technologies like Anthropic’s “Computer Use” and OpenAI’s “Operator” preview this capability—AI agents that can perform browser-based tasks end-to-end. In this landscape, customer AIs are persistent, multi-modal, and increasingly autonomous.

The implication for businesses is profound: your own chatbot or app may no longer be the first touchpoint. Instead, the customer’s AI will be. And unless your systems are prepared to engage with these agents—directly and efficiently—your customers may experience friction that’s entirely out of your control.

Impact on Traditional Support Channels

As the AI interface becomes the customer’s default gateway, businesses must rethink their service architecture. One immediate impact is a potential surge in support volume—not in human calls, but in AI-initiated requests. When getting assistance becomes as easy as saying “Hey AI, do X for me,” consumers are likely to offload a lot more tasks to their assistants. This could dramatically increase the number of support interactions companies handle, simply because the friction is lower. As one analysis put it, if customers no longer have to sit on hold or struggle through a website, they’ll be more inclined to ask for help whenever they need it. Routine tasks that might have been abandoned due to complexity or time cost will now be completed via AI.

Industry leaders predict that AI assistants will become a major customer service channel, with contact volumes rising 3–5× as a result. Zendesk CTO Adrian McDermott has forecast that AI-driven agents will handle a majority of service interactions in the near future, transforming CX operations end-to-end (source). But these requests won’t necessarily route through human agents. Instead, businesses must be ready for a flood of machine-originated contacts that require backend automation, smart routing, and adaptive workflows.

Another critical implication: the traditional “omnichannel” strategy becomes less relevant. Many companies have relied on tactics like hiding contact details or forcing self-service to manage volume. These approaches will be ineffective in an AI-driven world, where digital agents can scrape sites, autofill forms, or auto-email support teams at scale. Companies will need to expose new, standardized interaction formats—like structured data schemas and action APIs—that allow customer AIs to interact with brand systems directly.

From the company side, chatbots and apps won’t vanish, but they’ll shift roles. Instead of acting as front-end experiences for customers, they’ll become backend “business agents” interfacing with external AI clients. Call center infrastructure will need to support both human interactions and machine-to-machine communications—across API calls, structured messaging, and fallback workflows. This means rethinking how authentication, session management, and service logic are handled when the ‘user’ is another intelligent agent.

Businesses that adapt early—offering robust AI endpoints and streamlined data—will deliver faster, more convenient service. Those that don’t will be at the mercy of workarounds: consumer AIs emulating browser behavior, flooding support inboxes, or parsing websites not built for machines.

One of the most powerful aspects of consumer-owned AI is long-term personalization. Unlike today’s bots, which start fresh with each session, personal AIs will remember preferences, travel patterns, payment methods, even family birthdays. That memory enables them to act with precision, speed, and relevance.

But with that capability comes a concern: privacy. Consumers will want assurance that sensitive data isn’t shared indiscriminately across platforms. This is driving a parallel trend: the rise of on-device AI. Already, Apple has announced an on-device LLM integrated into iOS and macOS, enabling AI features to work without sending data to the cloud—boosting both privacy and responsiveness. Other major players and independent researchers are also pushing this shift. Meta’s LLaMA models, along with initiatives from startups like MLC.ai and Nimble, are demonstrating how compact, powerful LLMs can run efficiently on local devices.

As a result, privacy-conscious consumers are likely to run their own AI models for personal assistant use—completely offline and under their sole control. These local assistants reduce latency, eliminate cloud dependence, and offer users full transparency over their data. While still a niche use case in 2026, this approach is gaining traction, especially among tech-savvy or regulated-industry users. The trajectory is clear: as open-source models improve and hardware becomes more capable, consumer-grade AI will shift from the cloud to the edge.

The Value of Human Interaction in the AI Era

Even as routine tasks and information exchanges are offloaded to AI assistants, one question looms: What happens to human-to-human interaction? The consensus is that it will not disappear—in fact, it will become more valuable than ever, precisely because it will be rarer. When AI can efficiently handle basic requests like “reset my password” or “check my order status,” the remaining interactions are more likely to be complex, emotionally sensitive, or unusual. Customers will still want to talk to a real person when it truly matters.

A 2024 Gartner survey found that 64% of customers would prefer companies not use AI in customer service, citing fears that it will become harder to reach a live person. The top concern, shared by 60% of respondents, was that AI would block access to human agents (source). This sentiment reinforces a key principle for forward-thinking companies: automation should never come at the expense of human connection.

Smart brands will design CX systems where live support remains clearly accessible as a fail-safe. Klarna, for example, reversed an AI-only support approach after customer backlash and resumed recruiting human agents, recognizing that transparency and availability build trust (source).

The role of human agents will shift from handling volume to delivering impact. AI might deliver speed, but it lacks empathy, reassurance, and nuanced judgment. The best customer experiences will pair intelligent automation with skilled human intervention. In fact, some brands are already treating access to human agents as a premium feature—reserved for loyalty members or offered as part of a paid upgrade.

As tech entrepreneur David Heinemeier Hansson puts it, "Great customer service isn’t just about getting the right answer. It’s about understanding, reassurance, and human connection—that stuff is gold" (source). In an AI-driven landscape, the human touch becomes a differentiator, not a default. And that shift will define what premium customer experience really means in the years ahead.

Starting in 2026, customer experience will be shaped as much by the customer’s AI as by the company’s strategy. The interface is shifting—from web forms and call queues to intelligent, delegated conversations between machines. This creates new demands on systems, standards, and staffing. But it also opens new opportunities: faster resolution, deeper personalization, and service that truly works around the customer’s needs.

The call center isn’t going away. But its role is evolving—less about managing volume, more about managing complexity, exceptions, and moments that matter. In this new world, brands that build for both AI agents and human empathy will lead the next era of customer experience.