An entrepreneur’s AI playbook: Expert-backed prompts to check before starting a business 

So, what should first-time entrepreneurs actually ask AI before launching a business? FinancialExpress.com spoke to Ankur Saigal, co-founder and CEO of BambooBox; Rajesh Chhabra, General Manager, Large Markets (APAC), Acronis; Gurleen Khurana, co-founder of SimplifyGenAI; and Raj Goodman Anand, founder of AI-First Mindset (AIFM), to understand the prompts aspiring entrepreneurs should use, the questions AI cannot answer and the mistakes every beginner should avoid.

Don’t ask AI if your business idea is good

One of the biggest mistakes first-time entrepreneurs make is asking AI a simple question: “Is this a good business idea?”

Experts say that approach often produces polished but misleading answers because AI is designed to be helpful, not to determine whether a business will actually succeed.

Chhabra says the single biggest error founders make is using AI to confirm an assumption instead of testing it. “A convincing response is not necessarily a commercially viable conclusion. The speed of AI must never be allowed to create false confidence,” he adds. 

According to Saigal, many founders confuse AI’s ability to generate ideas quickly with genuine market validation. In his view, the tool cannot establish whether a real customer has a burning problem, whether that customer is willing to pay for the solution, or whether the business model can scale with healthy unit economics. 

Instead of seeking validation, experts recommend using AI to expose weaknesses in a business idea.

Some prompts they recommend include:

• What assumptions must be true for this business idea to succeed?
• Act as a skeptical investor. What are the top five reasons you would reject this startup?
• Who is most likely to ignore this product, and why?
• What evidence would prove that my business idea is wrong?
• Which competitors have tried solving this problem before? Why did they fail or succeed?

Khurana says founders should go a step further and ask AI to argue against their own ideas, including the case for not building the product at all, which he believes is the most uncomfortable and the most useful output a founder can read. He goes on to suggest asking which companies attempted the same thing and shut down, since that history is publicly available and rarely looked up. 

According to Anand, founders should use AI to identify patterns rather than seek approval. He recommends using it for market sizing and for spotting how other industries have solved similar problems, but never for a verdict on whether the idea is worth pursuing. “AI cannot know your risk tolerance, your network, your stubbornness or your timing,” he says.

AI can’t tell you if customers will actually pay

AI can analyse markets, identify trends and compare competitors within minutes. But experts say it cannot answer the one question that decides the business: will customers actually pay for the product?

According to Saigal, AI can analyse historical patterns and competitive landscapes, but it cannot measure trust, emotions or the decision-making process behind a purchase. “You can ask AI to help you map a CMO’s likely objections, but you must never rely on AI to tell you if that CMO will sign a paid pilot or a Letter of Intent. That requires real-world ground-truthing,” he says.

Chhabra says entrepreneurs should use AI to generate better questions rather than confirm demand or pricing. In his view, the useful prompts are the ones that ask which assumptions must be true, who faces the problem most urgently, what substitutes already exist, why customers may refuse to pay and what low-cost tests could disprove the idea. He cautions that demand, pricing, regulatory compliance and financial viability should never be confirmed on the basis of AI output alone. 

Khurana says AI is most valuable when it helps founders prepare for customer conversations rather than replace them. “AI can tell you a market exists, it cannot tell you your specific customer will take out their card. That only comes from actual conversations and a landing page with real traffic,” he says. 

Before speaking to customers, experts recommend using AI to pressure-test assumptions with prompts such as:

• Who is most likely to buy this product first, and what problem are they trying to solve?
• Why might customers choose an existing competitor instead of my business?
• If acquiring each customer costs three times more than I expect, how would that affect my business model?
• What is the cheapest experiment I can run over the next 30 days to test whether customers are willing to pay?

Anand also cautions against treating AI-generated customer personas and financial projections as facts. He says founders feed the tool their own assumptions and get back neatly formatted forecasts and synthetic personas that feel rigorous simply because they are well structured. “Synthetic customer research replaces the messy, humbling work of actual conversations with actual humans,” he adds.

The prompt matters more than the answer

Experts say the quality of AI’s response depends largely on the quality of the prompt. A vague question produces a generic answer, while a detailed prompt with real business context is far more likely to generate practical insights.

Khurana says many founders simply type, “Give me a business plan,” and accept the first response. “A generic prompt gives you a generic business, and the market doesn’t pay for generic. The founders who get real value are the ones who argue with AI, give it their actual numbers and treat the first answer as a rough draft,” he says. 

He also advises founders to stop treating prompts like search queries, and suggests dictating them instead of typing — speaking to the tool the way one would brief a professional consultant, with full context. 

According to Khurana, founders should include details such as their target customer, available budget, competitors, business constraints and even previous failures. Sharing what has already been tried, and why it failed, helps AI avoid obvious suggestions and generate more relevant recommendations.

For example, instead of writing: “Give me a marketing plan.” He recommends asking: “Our target customer is early-stage retail businesses. We have a marketing budget of Rs 50,000. We tried Instagram ads but generated very few qualified leads. Suggest one customer acquisition channel founders in a similar situation often overlook. Explain why they miss it and what assumptions I should test before investing money.”

Saigal believes prompts become even more useful when founders assign AI a specific role before asking a question.

For example: “Act as a conservative enterprise chief marketing officer whose software budget has been cut by 20%. What are the top five reasons you would reject my product and continue using your existing solution?”

He also recommends PCCOC framework while writing prompts:

• Persona – Who should AI act as?
• Context – What’s the business situation?
• Constraints – What limitations exist?
• Objective – What outcome do you want?
• Counter-argument – Ask AI to challenge its own recommendation before giving an answer.

Anand suggests one simple prompt before asking AI anything else: “Help me ask you a better question about this decision.” “That’s often the fastest way to learn how to use AI well because the tool teaches you its own optimal use,” he says.

Rajesh Chhabra recommends prompting AI to acknowledge uncertainty instead of sounding confident about every answer. Founders should ask it to distinguish verified facts from assumptions, identify missing information, cite reliable sources where possible and clearly state, “I could not verify this,” whenever evidence is insufficient.

Use AI to improve decisions, not replace judgment

While AI can dramatically speed up research and planning, experts caution against handing over critical business decisions to a chatbot without independent verification.

One area where founders often over-rely on AI is financial planning. AI can generate revenue forecasts, customer acquisition costs and investor-ready spreadsheets within minutes, but those numbers are only as reliable as the assumptions behind them.

“People put AI-generated numbers straight into a deck and pitch investors without checking a single assumption, and an investor catches that in about a minute,” Khurana says.

He also advises entrepreneurs not to depend on AI for legal advice, company structure or regulatory compliance because laws differ across countries and incorrect information can become expensive mistakes.

Chhabra says market sizing, competitor research and customer trends should also be independently verified. “The output may combine outdated figures, weak sources or businesses that are not genuinely comparable, yet still appear authoritative,” he says. “Every critical claim should be traced back to the original source and tested through customer interviews, transaction data or a market pilot,” he says. 

Saigal believes founders make a similar mistake while defining their ideal customer. “AI gives you a map of the territory, but local buyer conversations give you the actual terrain,” he says.

Instead of asking AI to make decisions, experts recommend using it to compare alternatives and challenge assumptions.

Some useful prompts include:

• Based on my target customer, budget, competition and expected customer acquisition cost, compare three possible go-to-market strategies. List the advantages, risks and assumptions behind each option.
• Challenge my financial projections. Which assumptions appear unrealistic and what additional data would I need before presenting this business plan to investors?
• If this startup fails within the first two years, what are the five most likely reasons, and how can I test each risk before launching?

Anand says founders should understand the difference between using AI to generate content and using it to improve decision-making. “Content generation is asking AI to produce an output such as a blog post, an email or a slide deck. Decision-making is asking AI to structure your thinking about an output you still need to produce yourself. The first produces a document. The second produces clarity,” he says. 

For first-time founders, experts say AI works best as a thinking partner rather than a decision-maker. It can challenge assumptions, organise information and help entrepreneurs explore different possibilities, but validating ideas, speaking to customers and making the final business decision remain human responsibilities.