What designers need to understand about the technical side of AI
As designers, we put users first. We think carefully about each step in the user’s journey, ensuring the services we design are practical, helpful, intuitive, and help a user achieve their needs.
When designing AI-driven services, you don’t need deep technical expertise, but you do need a clear understanding of key technical elements.
Having an end-to-end, visual understanding of how technical aspects fit into your design helps you create more effective, user-centred services. It also improves how you collaborate with developers, data specialists, and stakeholders.
Here’s a practical, service-design-focused overview of the technical skills designers should understand, and exactly how they fit into the wider service design process:
Programming basics (JavaScript & TypeScript)
You don’t have to code—but knowing why programming matters in your service can help you design smarter interactions.
Why it matters in design:
Prototyping quickly tests user interactions.
Clarifies your ideas for better communication with developers.
Accelerates iteration and feedback loops.
In service design, programming skills help you clearly see where interactions may require rapid prototyping, enabling you to quickly validate and refine your concepts visually and interactively.
Consider this:
Have you identified specific steps in your service where quick prototyping would significantly improve user outcomes?
APIs & Webhooks: How AI connects to everyday tools
APIs and webhooks let your AI-powered services seamlessly connect and respond to real-life user interactions.
APIs: Connect your service clearly and easily with existing tools users already trust (calendars, payment gateways, databases).
Webhooks: Automatically trigger real-time actions, creating seamless and immediate user experiences.
Understanding APIs and webhooks helps you visually map your service interactions, identifying exactly where and how external integrations enhance user experiences.
Question to clearly ask yourself:
Have you mapped your service end-to-end to see precisely where APIs or webhooks could enhance the user experience
Logic and workflow design: Zooming into the processes
Clear logic and workflow design underpin great service experiences.
Logic: Clearly defines “what happens next” at each decision point.
Workflow: Visually organises these logical steps, making sure each interaction feels smooth and intuitive.
Clearly mapping logic helps you visually spot and correct potential user frustration points early, creating more intuitive AI-driven services.
Reflection:
Have you visually defined every decision and interaction step clearly enough for anyone to follow? Including stakeholders at all levels?
JSON Data Handling: Structuring information clearly across your service
JSON stands for JavaScript Object Notation.
It is a lightweight, human-readable format used to structure and store data. JSON is widely used in web development, APIs, and AI-driven services because it allows information to be exchanged between different systems in a clear and organised way.
JSON is a simple way of structuring data, critical in clearly communicating between the AI, user interfaces, and backend systems within your service.
Clearly structured JSON ensures AI tools deliver clear, accurate, and actionable information to users.
Understanding JSON helps you visually and practically map how data flows through your entire service.
Clearly structured data creates seamless experiences by ensuring information always feels intuitive and valuable to your users.
Question:
Is the flow of data in your service clearly mapped, ensuring the information delivered feels relevant to users at every step?
Hosting and Docker: data storing is key to build trust
Hosting affects the trust and reliability of your AI-driven service.
Cloud-hosting refers to services like AWS (Amazon Web Services), Google Cloud, Microsoft Azure, and similar platforms that provide on-demand computing power, storage, and security features without requiring you to manage physical infrastructure.
Clearly understanding hosting options helps you make informed design decisions aligned with user expectations.
Cloud-hosting: Simple to implement, ideal for rapid deployments, but less privacy control.
Self-hosting (Docker): Offers maximum security, privacy, and trust. Ideal for sensitive user data.
Visually mapping your service end-to-end highlights exactly where user data privacy and security matter most. Clear hosting choices strengthen your users’ trust in your service.
Ask yourself clearly:
Have you visually identified moments in your service where user trust might be significantly impacted by hosting choices?
Clearly understanding AI capabilities and limitations in your service
Integrating AI (like ChatGPT, GPT-4, Grok) means clearly understanding what AI realistically can and cannot do.
Clearly knowing AI’s capabilities helps set realistic user expectations.
Understanding limitations means designing fallback solutions, ensuring a reliable and consistent experience for your users.
Visualising your service end-to-end clearly highlights where AI will excel, and equally important, where human touchpoints are still essential.
Think:
Have you designed clear pathways for when your AI tool reaches its limitations or dead-ends? It’s crucial to ensure people feel supported where AI fails.
Why end-to-end visualisation is crucial in AI-driven service design
Service design is inherently visual, end-to-end, and user-centred.
Clearly understanding these technical basics lets you effectively incorporate AI into your broader service vision, ensuring it genuinely meets real user needs.
Mapping your service visually, from first interaction through to final outcomes, ensures clarity around how technical components enhance the user experience at every stage. This clarity strengthens collaboration, increases stakeholder buy-in, and, ultimately, creates more impactful services.
As a designer, your ability to clearly visualise and integrate these technical aspects directly enhances your effectiveness.
Final note:
Understanding these technical foundations is just the starting point. Designing AI-driven services effectively requires continuous iteration, collaboration, and user validation.
To ensure your AI solutions truly meet user needs:
Run workshops to map the entire service journey and identify where AI adds value.
Apply service design thinking to balance technology with human-centered outcomes.
Start small, test early, and measure success to refine and improve your AI-driven service.
AI is a tool. Not the solution itself. The real success comes from how well it integrates into the wider service experience and improves real-life outcomes for users.
