Intro.
#The Bottom Line — Using AI Isn't the Problem, the 'AI Tell' Is
No government grant program or investment review bans writing a business plan with AI. Reviewers use AI too. The problem isn't the tool — it's the output. Polished-but-empty sentences AI generates, market sizes with no source, generalities that apply to any business — these 'tells' are the real reason points get docked.
| Category | Doesn't Lose Points | Loses Points |
|---|
| Sentences | Clear sentences polished with AI | Hollow, flowery filler generated by AI |
| Market size | An AI draft that you verified against sources | Fabricated figures or fake statistics AI made up |
| Problem definition | Structured by AI + your own experience and interviews | A generic pain point AI invented |
| Solution | Clarified with AI + a real MVP and real data | A list of features AI imagined |
TIP
What matters isn't whether you used AI — it's whether real data and experience sit behind it. That's what reviewers are looking for.
02
#The 5 Signals Reviewers Use to Detect an 'AI Tell'
Reviewers read hundreds of business plans every year. AI's distinctive writing patterns show up within a few paragraphs. Here are the 5 most common detection signals.
- Overly smooth generalities — sentences like 'We will lead the market with an innovative solution' that anyone could write
- Big numbers with no source — a figure like 'TAM of ₩10 trillion' appearing with no basis or reference year
- Execution plans with no specifics — verbs like 'scale up in phases' with no numbers or timeline attached
- A gap in competitive analysis — either 'we have no competitors' or a list of only abstract advantages
- A disconnect between problem and solution — the problem reads as a generality, the solution as a feature list, and the two never logically connect
주의
It's uncommon for a review process to run an AI-detection tool and dock points for '% AI-written.' Reviewers judge based on how real the content feels, not a score — an AI tell is ultimately just a symptom of missing substance.
03
#When It Genuinely Hurts You — Submitting Without Verification
AI writing genuinely becomes a disadvantage in the following situations. What they share in common is skipping the human verification step.
| Risk Scenario | What Happens |
|---|
| Citing fake statistics | A source AI invented, like 'Statistics Korea 2024,' gets caught instantly during Q&A at a pitch presentation |
| Ignoring industry-specific realities | AI misses regulations, licensing requirements, or domain conventions it doesn't know about → feasibility gets questioned |
| Your own experience disappears | Your founding motivation and pain points get replaced with generalities → your Problem (P) score collapses |
| Numbers stop being consistent | AI generates different market sizes or revenue estimates in different sections → credibility drops |
The risk is especially high for programs with a pitch presentation round (Pre-Startup Package, Early Startup Package, TIPS, etc.). You can't defend a sentence you didn't actually write yourself during Q&A. If you can't answer 'what's the basis for this market size,' even a high written score can get overturned.
04
#Typical Weakness Patterns in AI-Written Business Plans
AI is good at generating a 'plausible average.' So it also tends to produce average, safe, and therefore undifferentiated sentences in a business plan. Common weaknesses include:
- Differentiation filled with abstract keywords like 'technical strength,' 'expertise,' or 'customer-centric'
- A big top-down number presented with no bottom-up revenue calculation (customer count × price × conversion rate)
- Risk analysis limited to textbook items like 'market volatility' or 'intensifying competition'
- Team credentials that read as a list of résumés, never connected to 'why we're the ones who can solve this'
TIP
These weaknesses aren't a limitation of AI — they're the result of skipping the verification step. Layer your own first-party data on top of an AI draft, and most of these get resolved.
05
#How to Use AI Without Losing Points — AI Drafts, Human Verification
Used properly, AI actually raises the quality of your business plan. The key is dividing the labor — let AI handle structuring and polishing sentences, and let a human handle the data, experience, and verification.
| Stage | What to Hand to AI | What a Human Should Fill In |
|---|
| Problem definition | Logical structure, sentence cleanup | Firsthand experience and customer interviews |
| Market size | Framing TAM/SAM/SOM | Verifying sources and reference years |
| Solution | Clarifying feature descriptions | An actual MVP, prototype, or data |
| Revenue estimate | A calculation template | Real prices, conversion rates, customer counts |
| Final review | A first pass on typos and consistency | A re-read from the reviewer's point of view |
After drafting with AI, ask yourself paragraph by paragraph: 'Is there real data of mine behind this sentence?' A sentence with no data behind it is a sentence with an AI tell — and that's where you lose points.
06
#The 3 Things AI Can Never Fill In
The following 3 things can never be generated by AI, no matter how good it is. If these are missing, you'll lose points no matter which AI you used.
- First-party customer data — interviews you personally conducted, a pre-signup list, or a letter of intent (LOI) to purchase
- Evidence of execution — a working MVP, design mockups, PoC results, or a patent filing
- The founder's unique context — why this problem, why now, why you specifically are positioned to solve it
주의
This is exactly where reviewers most quickly decide pass or fail. AI can help you express things, but it can't manufacture substance.
07
#A Pre-Submission 'AI Tell' Self-Check Checklist
- Does every market-size figure have a source and a reference year attached?
- Does your problem definition start from your own experience and interviews (not generalities)?
- Is your differentiation a verifiable fact, not an abstract keyword?
- Is your revenue estimate built from a bottom-up calculation?
- Are your market-size and revenue figures consistent across sections?
- Can you personally defend every sentence during pitch Q&A?
If even one of these 6 comes back 'no,' that's where your AI tell is showing. Before you submit, go back and refill that section with your own data.
Summary.
#One More Pass Through a Reviewer's Eyes
Once you've reinforced your AI draft with your own data, the last step is simulating 'how would a reviewer read this.' It's hard to spot the gaps in your own writing by yourself — the writer's perspective and the evaluator's perspective are different.
CTA
OpenSeed has 15 AI reviewers cross-check your business plan from the perspective of market, solution, team, and finances. Before you submit, it catches whether an AI 'tell' is still showing in your draft — sourceless figures and hollow generalities — at a reviewer's level of scrutiny.
Catch the Gaps in Your AI Draft Before You Submit
15 AI reviewers cross-check sourceless figures, hollow generalities, and unverified differentiation from a reviewer's point of view.
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