Building Scalable Notification Experiences: AI-Assisted Design for Enterprise Fintech

When designing for enterprise fintech, notifications aren't just simple pop-ups – they're critical communication tools that need to handle countless scenarios while maintaining clarity and consistency. Here's how I used AI to tackle the complexity of creating a universal notification system.

The Challenge

I needed to design a notifications drawer with scalable tile components for enterprise fintech software. The tricky part? I knew all the data ingredients that needed to be included, but there were countless variations of alerts possible – from transaction updates to compliance notifications to system alerts.

The structure had to be flexible enough to handle every scenario while maintaining a consistent user experience across the platform.

The AI-Powered Approach

Instead of sketching endless variations manually, I decided to let AI help me explore the structural possibilities.

Tool Stack:

• Figma Make for AI-generated design iterations
• Figma for high-fidelity refinement using our design system

The Process:I jumped straight into Figma Make with a clear brief: the data points that needed to be included and the various notification scenarios we needed to account for. This direct approach let me focus on exploring structural solutions rather than getting bogged down in visual details early on.

The AI generated multiple tile variations, each handling the data differently and accommodating various content lengths and alert types.

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The Breakthrough

What made this approach so effective was the speed of iteration. Within hours, I had multiple clickable prototypes that I could share with the team for immediate feedback. This rapid prototyping phase revealed structural insights I might have missed with traditional design methods.

Once I identified the strongest structural approach, I recreated the designs in high-fidelity using our established design system, ensuring consistency with the broader platform.

Key Takeaways

AI excels at structural exploration. When you know your content requirements but need to explore how to organize them, AI can rapidly generate variations you might not have considered.

Clickable prototypes accelerate feedback cycles. Getting working prototypes in front of stakeholders early in the process saves countless revision rounds later.

AI gets you to refinement faster. The real design work happens when you take AI output and elevate it with proper design systems and user experience principles.

The Results

The final notification tile system successfully handles the full spectrum of enterprise fintech alerts while maintaining visual consistency. More importantly, the AI-assisted design process saved significant research and design time, allowing for faster team collaboration and iteration.

This project reinforced that AI isn't about replacing design thinking – it's about amplifying our ability to explore solutions quickly and get to the refinement stage faster.

Want to see more examples of AI-assisted enterprise design? Let's connect and discuss innovative design workflows.