Service design is all about creating seamless interactions between humans and services. The ultimate goal of service design is to streamline experiences, enabling people to achieve more in less time and with less effort.
Traditionally, companies invested significant time and resources into making user journeys as easy as possible. Before the AI revolution, this was achieved through digitalization and automation of routine operations. But in the era of AI, the focus is shifting — from automation to AI agents. In this article, I’ll discuss how service design will evolve in this new era.
Evolution of the concept of automation
Well-crafted automation is an integral part of any effective workflow. By automating processes, organizations can save users many hours of manual human labor and minimize the risk of human error.
However, traditional automation has one major limitation — fixed rules. These rules define the pathways that a system follows when serving a user. As the number of rules grows, the system becomes increasingly complex and difficult to manage. Eventually, organizations often need a dedicated specialist (or even a team) to maintain and adjust those rules to fit changing realities.
Another limitation is hard-coded determination. Traditional automated systems can be predictable, but they lack the ability to evolve or quickly adapt to new circumstances.
AI agents represent a fundamental shift in how we think about automation. Many people even avoid using the term automation when referring to AI agents, because AI is not just an automation tool — it’s an active participant in the ecosystem we build for users. AI agents can perform tasks autonomously on behalf of both users and organizations. This fundamental difference will reshape how services are designed and delivered.
How AI-powered service design looks like
AI-driven service design introduces 5 distinct characteristics:
1. Independence of AI agent
An AI agent is an independent program designed to achieve outcomes rather than just execute pre-defined instructions. Unlike traditional automation, AI agents don’t require explicit step-by-step guidance. They can dynamically define the steps needed to achieve a goal based on the current context. All you need to do is clearly articulate what you want to accomplish.
This approach has a tremendous impact on user experience.
Imagine you’ve just moved to a new neighbourhood and need to register your child at a new school. Depending on the country, this can be a time-consuming process involving research and form-filling.
With AI, things change dramatically. A well-configured AI agent could handle much of this on your behalf — communicating with educational institutions, filling out necessary details, and managing the process from start to finish.
2. Orgs integrate AI agents
Because of this convenience, more and more organizations will focus on making their services accessible to AI agents. We’ll increasingly see AI-to-AI interactions, where a user’s AI communicates directly with an organization’s AI to achieve results.
As a result, AI agents will gradually assume roles across service ecosystems. This is already happening — for example:
- Customer support: AI agents managing and responding to support tickets, analyzing past interactions, and extracting insights.
- Internal operations: Agents handling data management and workflow optimization within organizations.
- Personal assistance: Agents prioritizing messages, organizing schedules, or managing daily tasks.
In the near future, services will be evaluated by how well they integrate AI to help users achieve their goals.
3. Evolution of the traditional GUI
Because AI agents often operate on the data layer — using APIs and system connections — many interactions between users, organizations, and AIs will happen “behind the scenes.” This means 3 things:
- Fewer UI screens will be needed. For example, dedicated success or error screens may become obsolete because users won’t directly interact with those processes anymore.
- Interfaces will focus more on intent articulation. Instead of multi-step workflows, the emphasis will shift toward defining goals and constraints for AI systems.
- Rise of GenUI: Generative UI represents a new paradigm in interface design — interfaces created by AI in real time to meet the specific needs of each user. Instead of relying on static, predefined layouts, AI agent dynamically generates screens, components, and interactions based on a user’s context, goals, and behaviour. This marks a fundamental shift from the traditional “one-size-fits-all” approach toward a model of continuous, adaptive personalization. In a GenUI world, no two users experience the exact same interface — each one sees a tailored environment that evolves with their actions, preferences, and intent. The result is a level of personalization and efficiency that traditional design systems could never achieve.
4. The process of creating AI agent will be straightforward
Even today, building an AI agent isn’t complex. Depending on the platform, you can create one in minutes, for instance, using tools like ChatGPT
Why and how to use AI agents in product design: a practical ChatGPT tutorial
or spend slightly more time (when you’re using tools like n8n or OpenAI Agent Builder)
Introduction to OpenAI Agent Builder
In the future, the process will become even more straightforward as companies like OpenAI release ready-to-use templates for common use cases — both for individual users and organizations.
5. Importance of guardrails
Since AI agents can act autonomously, it’s essential to integrate safety mechanisms that prevent them from making harmful or unintended decisions. These mechanisms are known as guardrails.
A well-designed guardrail system includes state checks — moments when the AI must seek human confirmation before proceeding. This step is not only crucial for minimizing errors but also serves a psychological purpose: humans need to feel a sense of control over the systems they use.
From a service design perspective, organizations will face an interesting challenge — finding the right balance between AI autonomy and human oversight.
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Service Design in the Era of AI Agents was originally published in UX Planet on Medium, where people are continuing the conversation by highlighting and responding to this story.