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Applied AI Readiness Assessment — Concept Exploration

November 20, 2025

The Problem​

Business owners and institution leaders hear "you need AI" constantly but don't know:

  1. If it's actually relevant to their situation
  2. Where to start
  3. Whether the ROI is worth it
  4. If they're ready to implement

We need a way to help them self-assess before they talk to anyone—or to qualify them before we spend time on discovery.

Should It Be a Wizard?​

Pros of a wizard:

  • Structured, low-friction entry point
  • Feels actionable ("take this 5-minute assessment")
  • Can capture leads/emails naturally
  • Produces a shareable result ("You're a Stage 2 AI Readiness")
  • Scales infinitely

Cons of a wizard:

  • Can feel gimmicky or like a marketing funnel
  • Misses nuance that a conversation would catch
  • People might not trust an automated recommendation
  • Risk of oversimplifying complex situations

Verdict: A wizard works as a first filter, not a final answer. Position it as "see if Applied AI might be relevant" not "here's your diagnosis." The wizard should end with a human conversation option.

Alternative Approaches to Consider​

1. Simple Checklist ("10 Signs You Need Applied AI")​

  • Lower friction than a wizard
  • Shareable as content marketing
  • No data capture, but builds trust
  • Example: "If you checked 4+, you should talk to someone"

2. ROI Calculator​

  • More concrete: "Enter your hours spent on X, we'll estimate savings"
  • Feels less salesy, more useful
  • Requires knowing what to measure (harder for uninformed users)

3. Pain Point Diagnostic​

  • Start with symptoms, not solutions
  • "What's frustrating you?" → map to AI opportunities
  • Feels more like a consultation

4. Hybrid: Checklist → Wizard → Human​

  • Checklist as blog post (awareness)
  • Wizard as deeper assessment (consideration)
  • Human call as final step (decision)

If We Build a Wizard: Key Design Decisions​

What are we assessing?​

1. Problem Fit — Do they have problems AI can actually solve?

  • Repetitive tasks consuming staff time
  • Communication bottlenecks
  • Data scattered across systems
  • Manual processes that feel outdated

2. Readiness — Are they able to implement?

  • Leadership buy-in
  • Budget availability
  • Technical infrastructure (or willingness to build)
  • Change management capacity

3. Urgency — How pressing is this?

  • Competitive pressure
  • Cost pressure
  • Growth constraints
  • Compliance/regulatory demands

Question Flow (Draft)​

Section 1: Current Pain Points

  1. How much time does your team spend on repetitive administrative tasks per week?

    • Less than 5 hours
    • 5-20 hours
    • 20-50 hours
    • 50+ hours

  2. Which of these describes your biggest operational frustration? (select all)

    • Staff doing manual data entry
    • Slow response times to customers/clients
    • Information scattered across systems
    • Scheduling/coordination headaches
    • Reporting takes too long
    • None of these

  3. Have you tried to solve these problems before?

    • Yes, with software tools (mixed results)
    • Yes, by hiring more people
    • No, we've just lived with it
    • We don't have major problems

Section 2: AI Exposure 4. How would you describe your team's current use of AI tools?

  • We don't use any AI tools
  • A few individuals use ChatGPT or similar
  • We've experimented but nothing stuck
  • We have some AI tools integrated into workflows
  1. What's your biggest concern about AI?
    • It won't actually work for our use case
    • It's too expensive
    • My team won't adopt it
    • Security/privacy concerns
    • I don't know where to start
    • I'm not concerned, I'm ready

Section 3: Readiness 6. Do you have budget allocated for operational improvements this year?

  • Yes, significant budget
  • Yes, but limited
  • No, but could find it for the right solution
  • No budget available

  1. If we found a solution that saved 10+ hours per week, who would need to approve it?

    • Just me
    • Me + one other person
    • A committee or board
    • I'm not sure

  2. How would you describe your organization's appetite for change?

    • We move fast and try new things
    • We're cautious but open
    • We're slow to change
    • We're actively resistant to change

Scoring Logic (Simplified)​

High Fit + High Readiness → "You're a strong candidate for Applied AI. Let's talk." High Fit + Low Readiness → "AI could help, but you may need to build internal readiness first. Here's how." Low Fit + High Readiness → "You might not need AI yet—but here's what to watch for as you grow." Low Fit + Low Readiness → "Focus on other priorities first. Here are some resources to revisit later."

Output Options​

Option A: Score + Recommendation​

  • "Your Applied AI Readiness Score: 72/100"
  • Personalized recommendation paragraph
  • Specific next steps based on their answers

Option B: Archetype Assignment​

  • "You're a Ready Operator" or "You're a Curious Explorer"
  • Makes it shareable/memorable
  • Risk: feels like a BuzzFeed quiz

Option C: Prioritized Opportunity List​

  • "Based on your answers, here are 3 areas where AI could help most:"
    1. Customer communication (high impact, low effort)
    2. Reporting automation (medium impact, medium effort)
    3. Scheduling optimization (high impact, high effort)
  • Most actionable, least gimmicky

Recommendation: Option C feels most aligned with the Applied AI Society ethos—practical, specific, not hype-y.

Technical Implementation Options​

1. Simple Form Tool (Typeform, Tally, etc.)​

  • Fast to build
  • Limited logic/personalization
  • Good for MVP

2. Custom Web App​

  • Full control over UX and logic
  • Can integrate with CRM
  • More work to build

3. AI-Powered Conversation​

  • Chatbot-style assessment
  • More natural, can handle nuance
  • Feels more "Applied AI Society"—eating our own cooking

Recommendation for MVP: Start with Typeform or similar. Test with 20-30 people. Learn what questions matter. Then decide if a custom build is worth it.

Next Steps​

  1. Validate the questions — Run draft questions by 5 business owners. Do they understand them? Do the options feel relevant?
  2. Build MVP — Create in Typeform with basic branching logic
  3. Test and iterate — See what results people get, whether they feel accurate
  4. Decide on output format — Based on feedback, pick score vs. archetype vs. opportunity list
  5. Connect to funnel — High-readiness results → offer a call; low-readiness → offer resources

Open Questions​

  • Should this be gated (email required) or open?
  • Do we show results immediately or email them?
  • Should there be different versions for different industries (schools, services, retail)?
  • How do we prevent people gaming the quiz to get a "good" result?
  • Is "wizard" even the right word? "Assessment" or "diagnostic" might feel less gimmicky.