AI Adoption Employee Anxiety Survey SaaS

2.80

Derivation Chain

Step 1 Expansion of AI-based startups + AI job displacement debate

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Step 2 Employee change management during corporate AI adoption

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Step 3 Pre- and post-AI adoption employee psychology & competency diagnostic tools

Problem

When SMEs (30-200 employees) introduce AI tools, they fail to identify employees' psychological resistance and skill gaps in advance. As a result, 70% of cases see actual usage rates drop below 20% within 6 months of adoption. For HR managers to design and analyze surveys themselves, they must hire external consulting ($3,750-$15,000).

Solution

Provides validated survey templates tailored to three stages—before, during, and after AI adoption (job displacement anxiety, digital competency self-assessment, change readiness). Automatically analyzes responses to generate department-level risk heatmaps and customized training roadmaps.

Target: HR managers and HR team leads at SMEs with 30-200 employees, AI adoption task force leaders (ages 30-45)

Revenue Model: SaaS Monthly Subscription at $44/month per company (up to 100 employees), plus $0.22 per additional employee. 20% discount for Annual Subscription.

Ecosystem Role: Education

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

2.0/5

U Urgency

2.0/5

M Market

2.0/5

R Realizability

4.0/5

V Validation

3.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (74%)

Tech Complexity

29.3/40

Data Availability

24.4/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (53/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

9.0/15

Pick-Axe Fit

7.5/15

Solo Buildability

8.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Frontend [medium] Backend [medium] AI/ML [low]

Dashboard