Summary:
AI will force the transformation of service design by introducing new actors, shifting user dynamics, and redefining success metrics.
Service design is the activity of planning and organizing a business’s resources (people, props, and processes) in order to effectively deliver the intended experience. As products and services grow in sophistication, so does the need to intentionally design how they are delivered. This is already a complex task when the primary actors are humans (users and support agents); it becomes even more so as AI integrates, replaces, and acts on behalf of users and the organization.
AI Agents as Actors
The most significant shift brought by AI in service design is the emergence of new actors within the ecosystem: AI agents. Traditionally, service design has focused on orchestrating experiences for and between human actors — customers and employees. However, with the integration of AI, we now face a new paradigm, where these systems are no longer mere tools but active participants.
Here’s the definition of an AI agent according to Anna Gutowska from IBM:
An AI agent is a system or program capable of autonomously performing tasks on behalf of a user.
It’s likely we’ll see two different types of AI agents emerge in the world of service design:
- A personal, independent AI assistant to act as a personal advocate/coordinator across multiple services
- An organization-created AI agent built to interface with customers (and their assistants) who need support
AI actors will perform diverse functions across the service ecosystem: from representing users to supporting agents, from analyzing data to making decisions. They will execute tasks and interact with other systems, fundamentally altering how services are delivered and experienced.
This evolution challenges the foundational assumptions of service design. AI agents will act autonomously or collaboratively with users, enabling outcome-oriented design, where the user specifies a desired result rather than performing all the steps that lead to it.
Users Delegating Tasks to Personal AI Assistants
As AI begins to replace or augment human roles in the ecosystem, service designers must consider how to design for these new actors. This requires a fundamental rethinking of both frontstage, user-facing interactions and backstage, internal-facing operations.
AI assistants are emerging as a practical and scalable solution, providing a bridge between fully autonomous systems and human-centered workflows. These specialized AI agents help users complete tasks, provide information, and manage interactions within a specific organization or service.
Unlike fully autonomous AI agents, AI assistants operate interactively, requiring user input, preferences, or approval throughout the process. This interactivity allows users to retain control and oversight over decisions while benefiting from AI’s efficiency and intelligence.
For example, imagine you want to optimize your retirement investments. You could delegate this goal to your AI assistant. The assistant, acting on your behalf and checking in with you along the way, could:
- Ask about your retirement goals and analyze your current finances
- Develop a tailored plan that adapts to your spending patterns
- Log into your retirement-fund portal and execute portfolio adjustments after receiving your approval
- Suggest ongoing changes based on your life events
Perplexity’s Booking Assistant, is an example of such an assistant for travel tasks. Other such assistants will likely emerge in more complex domains, like healthcare and finance.
Personal AI Assistants Acting for Users
Imagine getting a routine lab test, like blood work. The goal is to ensure you’re healthy and get additional consultations if needed.
Today, to do this, you have to navigate a series of touchpoints (like web portals, booking forms, and phone calls) both within and outside your medical provider’s system. This journey includes everything from scheduling an initial consultation to setting up a lab appointment once you have the order.
In the future, an AI assistant acting on your behalf like a (human) personal assistant. This assistant would be independent of the organizations you regularly do business with and answer only to you. With enough contextual knowledge about you and your preferences, your AI assistant could process your request and then communicate on your behalf with providers via the same support channels that exist today.
AI Agents Acting for Organizations
Users’ personal AI assistants may eventually interact directly with organizations through new programmatic interfaces, alongside traditional channels designed for human users. However, such direct system-to-system interactions would need to address significant privacy and security considerations.
On the organization’s side, it’s likely that AI agents will gradually augment or replace traditional support staff and interact directly with users’ personal AI assistants.
AI will also transform internal operations, with organizations deploying AI agents to perform various tasks related to service design:
- Customer–support automation: Handling inquiries and service requests
- Internal IT support: Troubleshooting technical issues and managing system access
- Scheduling and coordination: Organizing meetings and aligning team schedules
- Data analysis and reporting: Providing insights from operational data
- Procurement and supply-chain management: Automating inventory and vendor management
- Compliance monitoring: Ensuring adherence to regulations and flagging issues
It’s hard to predict how quickly these internal transformations will occur, especially within complex systems. We suspect AI assistants working for users will be available before enterprise AI agents fully transform internal organizational processes.
The AI Agents’ Ripple Effect on Services
As AI agents become intermediaries between users and organizations, the rules of competition in service design will be disrupted. The interaction between businesses and consumers will increasingly shift to an AI-to-AI dynamic, where assistants act on behalf of users to evaluate, choose, and engage with services, and agents provide them on behalf of the organizations. This new dynamic will force organizations to rethink how they deliver experiences.
There are many parallels with ecommerce’s impact on the goods industry. For consumers, ecommerce revolutionized access, pricing, and convenience. For businesses, it created intense competition, commoditized experiences, and gave concentrated power to distribution platforms.
AI agents will have a similar impact on how businesses deliver their services. The traditional levers of differentiation — a beautifully designed app, seamless website, or flawless human processes — may no longer matter to AI systems focused on efficiency and data compatibility. This new paradigm will push organizations to cater to human users and employees, as well as to the AI layers that represent them.
While this new paradigm won’t affect every category or market uniformly, we anticipate a trend analogous to what we’ve seen in the goods industry.
- Experience commoditization: AI will force a prioritization of efficiency, accuracy, and structured data over traditional UX components like visual design and usability.
- Evolving differentiation strategies: As evaluation, comparison, and decision making move from humans to AI, services will have to shift how they differentiate from each other (i.e., data integrations, superior AI-to-AI compatibility, or specialized outcomes).
- Platform consolidation: The development and control of AI layers by only a few major tech companies will likely concentrate power, forcing organizations to navigate new gatekeepers in the service-delivery landscape.
Service Metrics Will Change
The rise of AI in service ecosystems will redefine how service success is measured. Traditional metrics like satisfaction, operational efficiency, and net–promoter score will remain important, but they won’t paint the full picture. With AI agents mediating interactions and decisions, new key performance indicators (KPIs) will emerge to track the effectiveness of these systems and their broader impact.
For example, organizations may begin to collect measures that reflect:
- AI-to-AI compatibility: How effectively AI systems interact with one another.
- AI-to-employee compatibility: How effectively employees interact with AI systems
- Data accuracy and quality: Ensuring the underlying data driving AI decisions is sound
- Automation effectiveness: The AI’s task-completion success rate
- User trust: How much the user trusts the AI actors — theirs or the organizations’
Balancing AI and Human Potential
As AI becomes an integral part of service design, it brings transformative opportunities alongside significant challenges. The rise of AI agents and assistants as active participants in service ecosystems will redefine how organizations deliver services and interact with users.
However, this evolution also reshapes the roles and experiences of employees, highlighting a critical responsibility for service designers: to ensure that work remains meaningful, satisfying, and joyful for the people who perform it.
Designing services is not just about meeting user needs or maximizing business efficiency — it is also about creating systems where both users and employees can thrive. As we integrate AI, the challenge isn’t just choosing what to automate, but reimagining roles that leverage both human creativity and artificial intelligence in meaningful ways.
Service designers must now evolve their methods and mindsets, leveraging their ability to think both systematically and empathetically. By understanding the granular implications of AI on interactions and their ripple effects across service ecosystems, we can help create a future where AI and human intelligence complement each other meaningfully.