AI projects often fail when they overlook user experience. Learn how applying Service Design principles can create intuitive, valuable AI agents and workflows that users genuinely benefit from.
Many AI projects fail not because of technology limitations, but due to poorly designed interactions That come from over engineered technical solutions.
Proposing new workflows and processes within highly technical engineering teams can be challenging. Time-and-time again I’ve seen too many input parameters and deep technical explanations used to explain what should be a straightforward solution.
If we continue with engineer-led designs, as we move to augmenting our engineers with co-pilots and AI Agents, I fear it will lead to even worse designs.
The problemIn these cases?
The engineers prioritized technical implementation over user experience.
Service Design helps prevent this by aligning AI capabilities closely with real user needs from the start.
Service Design is a holistic methodology focused on creating services that provide meaningful experiences and outcomes for users.
When applied to AI, it ensures technology meets user needs effectively.
Imagine Service Design as choreographing a seamless performance: each user interaction with the AI agent is intentionally designed to feel intuitive, relevant, and valuable.
Step 1: Empathize and Research
Step 2: Define the User-Centric Problem
Step 3: Ideate Solutions
Step 4: Prototype AI Interactions
Step 5: User Testing and Feedback
Step 6: Deploy and Continuously Monitor
“The most powerful AI systems aren't just technically advanced; they're thoughtfully designed around real human needs.”
Here's a detailed technical stack to apply Service Design effectively in AI workflows:
User Research:
Experience and Journey Mapping:
AI Prototyping and Conversational UX:
Implementation and Analytics:
NatWest’s collaboration with OpenAI
In March 2025, NatWest became the first UK bank to partner with OpenAI to improve their digital assistants and customer support processes.
This initiative aimed to enhance customer experience, reduce costs, and combat financial fraud.
By integrating OpenAI’s technology, NatWest improved their customer-facing chatbot, Cora, leading to a 150% improvement in customer satisfaction levels and a reduction in the need for human advisers.
This strategic move reflects NatWest’s commitment to digital innovation, as approximately 80% of their retail customers bank entirely digitally.
One common pitfall is assuming initial user requirements remain static. In reality, user expectations evolve. Continuously revisiting user research and conducting iterative testing is crucial. Additionally, organizations often underestimate the time and resources needed for thorough prototyping and testing.
Allocating sufficient resources early ensures long-term success.
Integrating Service Design into your AI workflows dramatically improves user experience and business outcomes.
To begin, select one workflow or AI agent and apply this framework—start small, iterate often, and focus deeply on user feedback.
The key is to find the one business use case that can justify the use of AI agents on its own. Do not get caught up on what would be possible only design for what brings value today.
Education:
Related Embeddings:
External:
AI Agents:
Case Study:
