The problem these days is that everyone’s chasing “AI-ready data,” but no one’s asking if users can actually find what they need. Enterprises spend months building clean datasets, training models, and implementing the next big AI feature, only to discover that employees still search, click, and give up. That’s not an AI failure. That’s a findability failure.
The truth about data
Data makes AI smart, but structure makes it usable. ServiceNow has made huge leaps with tools like RaptorDB and Workflow Data Fabric, creating a unified layer where AI can finally connect data across systems.
But here’s the catch, if your taxonomy, labels, and content don’t make sense to humans, AI can’t help them either. You can’t automate chaos.
Findability beats volume
Studies show that 47% of employees still say it’s “difficult or very difficult” to find internal information quickly (IDC, 2024). That’s what kills ROI, not a lack of data, but a lack of connection between data and design.
When users can’t find what they need, adoption flatlines. AI predictions go ignored. And every renewal conversation gets harder.
How ServiceNow bridges the gap
With the Data Fabric, ServiceNow connects real-time data across platforms, while RaptorDB delivers performance for AI queries at enterprise scale.
Together, they form the perfect data foundation. But the user still needs to know where to start. That’s where UX design turns raw data into usable intelligence.
Monochrome’s approach
We start with the human layer:
- Audit your data taxonomy to see if it matches how people search, not how systems store.
- Tune search to optimise synonyms, relevance, and natural language.
- Rewrite content to use intent-based titles and clear action language.
- Measure findability to track search exits, failed terms, and click depth.
Because when your people can find what they need, AI finally performs.
Just-deployed checklist
- RaptorDB connected
- Workflow Data Fabric active
- Search analytics reviewed weekly
- Taxonomy aligned with top user tasks
- Content written for intent, not hierarchy
- AI can’t think clearly if your users can’t
See how we structure ServiceNow for findability. Take a look at our Employee Center Examples.
Frequently asked questions
Why does ServiceNow AI fail before deployment?
Because users can’t find or trust the data behind it. Good UX bridges that gap through clear taxonomy and tuned search.
What’s the quickest way to improve findability?
Start with AI Search tuning and content rewriting, both show measurable ROI in weeks.
What’s RaptorDB used for in ServiceNow?
It’s an AI-optimised database that delivers faster queries and unified access for large-scale enterprise data.