AI Knowledge Assessment Survey
A 30-question, concept-scored survey that baselines an organization's AI literacy.
The Problem
Understanding the business challenge.
Organizations adopting AI struggle to gauge their team's actual AI literacy before investing in training.
Generic surveys don't map responses back to specific AI concept areas.
Manual scoring and reporting for AI-literacy assessments is time-consuming.
The Solution
Our AI-powered approach.
A 30-question, Likert-scale survey spanning 6 AI concept areas (AI, ML, Deep Learning, Generative AI, AI Agents, MCP), with automated concept-based scoring and a 5-tier knowledge classification.
6-Concept Assessment
30 questions across AI, Machine Learning, Deep Learning, Generative AI, AI Agents, and Model Context Protocol.
Concept-Based Scoring
Automated scoring up to 25 points per concept (150 total), with a 5-tier classification from Limited to Expert.
Analytics Endpoints
Backend analytics aggregate response data for organizational insight.
Secure Auth Infrastructure
Spring Security and JWT-based authentication protecting survey and response data.
Cross-Platform Delivery
React frontend on Cloudflare Pages backed by a Spring Boot API over a Cloudflare Tunnel.
Technical Architecture
Enterprise-grade technology stack.
Security & Compliance
Privacy-first implementation.
- Spring Security with JWT-based authentication
- PostgreSQL in production, with H2 used only for local development
- Backend exposed via a Cloudflare Tunnel rather than a directly open port
Implementation Workflow
Structured deployment process.
Concept Framework
Defined 6 AI concept areas and authored 30 Likert-scale questions.
Scoring Engine
Built concept-based scoring with a 5-tier knowledge classification.
Full-Stack Build
Implemented a Java Spring Boot API with a React frontend.
Analytics Layer
Added response analytics endpoints for aggregate organizational insight.
Business Impact
Measurable outcomes.
Target Industries
Versatile application across sectors.