0 of 25 answered
Score: 0 / 50
Free Self-Assessment

AI Readiness Assessment
for Manufacturing SMEs

Score your plant across 5 critical categories. Click ✅ Yes, ⚠️ Partial, or ❌ No for each question. Your score updates in real time.

📋 25 Questions ⏱ 15 Minutes 🏭 5 Categories 🆓 Completely Free
Scoring guide: ✅ Yes, in place (2 pts) ⚠️ Partial or inconsistent (1 pt) ❌ No / not started (0 pts) Max score: 50 pts (2 pts × 25 questions)
Section 1 of 5
Data Infrastructure

Without clean, accessible data, AI has nothing to work with. This is where most manufacturers stall.

Section score:
—
1.1
Do your machines/PLCs log production data digitally (not just on clipboards or whiteboards)?
1.2
Can you pull last month's scrap/rework numbers in under 10 minutes?
1.3
Is your production data stored in a central system (ERP, MES, or database) — not scattered across spreadsheets?
1.4
Do you track OEE (Overall Equipment Effectiveness) or similar metrics consistently?
1.5
Is your quality data (defects, inspections, customer complaints) digitized and searchable?
💡 Quick Win

If you scored ❌ on 1.1, start with one line or cell. A $200 sensor + Raspberry Pi logging to a Google Sheet beats a $200K MES you'll never finish implementing.

Section 2 of 5
Process Documentation

AI needs to understand your processes before it can improve them. Tribal knowledge trapped in people's heads is a risk, not an asset.

Section score:
—
2.1
Are your core manufacturing processes documented (SOPs, work instructions)?
2.2
Do operators follow the documented process, or does everyone have "their way"?
2.3
When a process changes, does the documentation get updated within a week?
2.4
Could a new hire learn to run your most critical process from documentation alone (with supervision)?
2.5
Do you document the why behind process parameters, not just the what?
💡 Quick Win

Pick your highest-volume product. Video-record your best operator running it, start to finish. That 20-minute video is more valuable than a 40-page SOP no one reads.

Section 3 of 5
Workforce Readiness

The tech is the easy part. People are the hard part.

Section score:
—
3.1
Do your operators use any digital tools daily (tablets, HMIs, dashboards)?
3.2
Is there at least one person on the floor who's comfortable with Excel/data beyond basic entry?
3.3
Has your team had any exposure to AI concepts (even a lunch-and-learn or article)?
3.4
When you've introduced new technology before, did it stick after 6 months?
3.5
Do your operators trust that new tech is meant to help them, not replace them?
💡 Quick Win

Find your "shop floor champion" — the operator who already tinkers with tech, tracks their own data, or suggests improvements. Buy them lunch and ask what they'd automate first.

Section 4 of 5
Leadership Buy-In

AI initiatives that report to "whoever has time" don't survive Q2.

Section score:
—
4.1
Does your leadership team understand what AI can (and can't) realistically do for manufacturing?
4.2
Is there budget allocated — even $5K–$10K — for a pilot project?
4.3
Has someone been named as the owner/champion of AI exploration?
4.4
Is leadership willing to accept a 3–6 month timeline before seeing ROI?
4.5
Can you articulate one specific business problem you want AI to solve (not just "be more efficient")?
💡 Quick Win

Frame AI in money language. "We lose $X/month to [specific problem]. AI could cut that by 30%." That gets budget meetings scheduled.

Section 5 of 5
Quick-Win Identification

The best first AI project is boring, valuable, and uses data you already have.

Section score:
—
5.1
Can you name a repetitive decision someone makes 10+ times per day that follows a pattern?
5.2
Do you have a quality problem that costs you >$1K/month that you already track data on?
5.3
Is there a scheduling or planning task that takes hours and still doesn't work well?
5.4
Do you have at least 6 months of historical data on any of the above problems?
5.5
Could you test a solution on one line/cell/product without disrupting the whole plant?
💡 Quick Win

The best starter AI project? Predictive quality. If you're already logging machine parameters and defect data, you're sitting on a goldmine.

Your Results Summary

Category Score Out of
Data Infrastructure — 10
Process Documentation — 10
Workforce Readiness — 10
Leadership Buy-In — 10
Quick-Win Identification — 10
Total Score 0 50
Complete the assessment to see your results

Answer all 25 questions above to get your personalized readiness score and interpretation.

Total Score
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1. Data Infrastructure —
2. Process Documentation —
3. Workforce Readiness —
4. Leadership Buy-In —
5. Quick-Win ID —
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