How AI Agents are reshaping Service Delivery

Nov 3 / Jean Felix
We are still thinking about AI in dangerously simplistic terms. We see it as just another tool, a faster chatbot, or a more efficient algorithm running in the background. We are wrong. The most significant shift in customer experience isn't a new tool at all; it's an entirely new actor.

These AI agents are not just processing requests; they are becoming active, autonomous participants in the service ecosystem.

This is the arrival of a new, non-human workforce, and it will fundamentally change the rules of engagement for every customer and every company.
The most significant shift in customer experience design is the emergence of new actors within the service ecosystem: AI agents. These are not just tools; they are active participants that will fundamentally change how services are delivered and experienced.

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. An AI agent is a system or program capable of autonomously performing tasks on behalf of a user.

We are likely to see two different types of AI agents emerge in the world of customer experience:
  1. A personal, independent AI assistant to act as a personal advocate and coordinator across multiple services.
  2. An organization-created AI agent built to interface with customers (and their assistants) who need support.


This evolution challenges the foundational assumptions of service design. AI agents will act autonomously or collaboratively with customers, enabling an outcome-oriented approach where the customer specifies a desired result rather than performing all the steps that lead to it.

The AI Agent's Ripple Effect on Services

As AI agents become intermediaries between customers 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 customers 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 the impact of e-commerce on the goods industry. For consumers, e-commerce 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, a 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 not only to human customers and employees but also to the AI layers that represent them.

A Shift in Service Metrics

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.
  • Customer trust: How much the customer trusts the AI actors — theirs or the organizations’.

Balancing AI and Human Potential

The work required to be a best-in-class, customer-centric organization is never over. Technology evolves, and customer expectations continue to rise. That means organizations must iterate on their CX operations, overcome challenges, and replicate best practices in areas still newly established or maturing. This evolution requires attention to three pillars: experimentation and iteration, consistency, and patience.

There is no definitive path from inception to journey-management maturity. Establishing journey-centric operations is just one piece of the puzzle. It takes more to scale and achieve this mandate across entire organizations, particularly if they are large and complex. Lessons learned are opportunities for improvement, not failures. The most successful teams look back at their work with the same scrutiny they apply to planning future efforts.