Smart Form with AISuggest
Combines AI models and cloud-based services to simplify and improve accuracy in manual data collection
I crafted the design of Enablon AISuggest smart form as the first step to achieving high data quality in manual data collection. It combines Enablon's in-house AI models with cloud-based services to enhance data accuracy during data collection.
Situation
Form fatigue was compromising data quality and safety reporting. Lengthy forms led to inaccurate entries ("dirty data") and high abandonment rates.
This created a disconnect between EHS managers, who required precise data, and field operators, who needed a fast, mobile-friendly way to report incidents without disrupting their workflow.
Key Processes
User testing
GDPR compliance
My Role
UX Designer
UX tester
Teams Involved
Data Lab
Product management
Pain Points
Field operators struggled with exhaustive input fields and competing time pressures.
Data Integrity: 26% of corporate data is "dirty," with 60% of those errors caused by human entry.
Financial Cost: Poor data quality costs the average business $15 million annually.
Friction: Overly complex forms resulted in significant underreporting of field incidents.
Objectives
Reduce Friction: Streamline the data capture process to increase reporting frequency.
Enhance Accuracy: Address data quality issues at the point of entry.
Ensure Compliance: Automate GDPR protection by identifying Personally Identifiable Information (PII).
Operational Value: Provide EHS departments with reliable, actionable insights.
Solution
I integrated generative AI into the AISuggest framework, utilizing in-house deep learning models trained on extensive event databases.
Automated Classification: The AI analyzes free text to assign risk categories instantly.
Intelligent Suggestions: Predicts answers and pre-populates fields based on context.
Human-in-the-Loop: Users retain final authority, choosing to accept or reject AI suggestions.
Continuous Learning: The model improves accuracy by learning from user feedback and corrections.
Mapping insights on the impact-effort matrix after user testing
Smart Form uses step-by-step guide to assist users in filling out the form
Impact
AISuggest transformed the reporting experience across three main pillars:
Speed & Accessibility
Efficiency: Reduced form completion time to just 2–3 minutes.
Mobility: Fully responsive design optimized for seamless field use.
Data Quality
Consistency: Automated suggestions eliminated manual entry errors and improved data completeness.
Lifecycle Integrity: Prevented the propagation of "dirty data" into the larger ecosystem.
Advanced Capabilities
Explainable AI: Highlights the specific text informing each AI suggestion for transparency.
Security: Automated PII flagging ensures robust GDPR compliance.
