Running a business means making decisions.
Should you enter a new market?
What are your competitors doing?
What do customers actually want?
Should you raise your prices?
Is there enough demand for a new product?
Which suppliers should you consider?
What trends could affect your industry?
Answering these questions properly requires research.
Traditionally, business research could involve hours of searching websites, reading reports, analysing spreadsheets, interviewing customers and trying to make sense of large amounts of information.
Artificial intelligence (AI) can make this process dramatically faster.
AI can help you find information, summarise documents, compare competitors, analyse customer feedback, identify patterns, generate research questions and turn large amounts of information into useful business insights.
But there is a catch.
AI is very good at helping you research. It is not automatically good at telling you the truth.
AI can misunderstand information, use outdated sources, make assumptions or confidently provide incorrect facts.
The best approach is therefore to think of AI as a research assistant, not an unquestionable expert.
Used properly, AI can help a small business owner conduct research that would previously have required considerably more time and resources.
1. What Is Business Research?
Business research is the process of collecting and analysing information to help you make better decisions.
It can involve researching:
- Customers
- Competitors
- Markets
- Products
- Suppliers
- Pricing
- Industries
- Locations
- Regulations
- Technology
- Trends
- Business opportunities
- Customer behaviour
For example, imagine you run a small catering company and are considering offering corporate lunches.
You might need to research:
- How many businesses are in your target area
- What competitors charge
- What menus are popular
- What customers expect
- How often businesses order catering
- Delivery requirements
- Potential profit margins
- Food regulations
- Equipment requirements
AI can help you structure and accelerate much of this research.
2. Why AI Is Useful for Research
Business research often involves three difficult activities:
Finding information → Understanding information → Connecting information
AI can help with all three.
It can help you:
- Generate research questions
- Find relevant topics
- Summarise long documents
- Compare information
- Organise data
- Identify patterns
- Explain technical subjects
- Generate hypotheses
- Analyse customer feedback
- Prepare research reports
Instead of spending hours trying to work out where to start, you can ask AI to help you design the research process itself.
3. Start With a Business Question
Good research begins with a good question.
Don’t simply tell AI:
“Research the coffee industry.”
That’s far too broad.
Instead, ask:
“I’m considering opening a small specialty coffee shop in a suburban area. What factors should I research before deciding whether the opportunity is commercially attractive?”
Now AI can help you create a research framework.
It might suggest investigating:
- Local population
- Customer demographics
- Competitors
- Foot traffic
- Average pricing
- Rental costs
- Customer preferences
- Opening hours
- Delivery services
- Labour costs
- Product mix
- Local development
- Barriers to entry
The research becomes much more focused.
4. AI as Your Research Assistant
Think of AI as an extremely fast junior researcher.
You might give it an assignment such as:
“I’m investigating whether there is an opportunity for a bookkeeping service targeting small construction businesses. Help me develop a research plan.”
AI could break the assignment into areas such as:
- Market size
- Target customers
- Customer problems
- Competitors
- Existing pricing
- Demand indicators
- Barriers to entry
- Customer acquisition
- Profit potential
- Risks
You can then investigate each area individually.
This is often much more effective than asking one enormous question and accepting the answer.
5. Researching Your Target Market
Understanding your target market is one of the most important forms of business research.
AI can help you investigate:
- Who your customers might be
- What they need
- What problems they experience
- How they currently solve those problems
- What they are willing to pay for
- What influences their decisions
- Where they look for information
- What objections they might have
For example:
“Create a research framework for understanding the needs of first-time small-business owners who want help with bookkeeping.”
You could then investigate each question using actual market evidence.
AI can help you organise what you discover.
6. Creating Customer Personas
AI can help turn your research into customer personas.
For example:
Customer Persona
Name: Sarah
Business: Small professional services firm
Employees: 6
Experience: Three years in business
Main problem: Too much administrative work
Goal: Spend more time serving clients
Concern: Cost of outsourcing
Buying trigger: Business growth
Likely objection: “I could do this myself.”
The persona isn’t a real customer.
It is a research tool.
Its purpose is to help you think about the type of person you’re trying to serve.
The important thing is to base personas on actual customer evidence, rather than allowing AI to simply invent what customers supposedly want.
7. Researching Customer Problems
One of the most valuable things you can research is customer pain.
Ask:
What problems are customers actually trying to solve?
AI can help you generate possible problems, but you should validate them using real evidence.
Potential sources include:
- Customer interviews
- Reviews
- Forums
- Surveys
- Support enquiries
- Sales conversations
- Social media discussions
- Search behaviour
- Industry reports
For example, if you are considering selling business software, you might discover that customers don’t actually care about having “more features.”
They may care about:
- Saving time
- Reducing mistakes
- Making reporting easier
- Training employees faster
That’s much more useful information.
8. Researching Competitors
Competitive research is another excellent use of AI.
You can investigate competitors’:
- Products
- Services
- Prices
- Target markets
- Websites
- Reviews
- Marketing messages
- Strengths
- Weaknesses
- Customer complaints
- Differentiators
AI can help organise this information.
For example:
| Competitor | Main Offer | Target Customer | Price | Strength | Weakness |
|---|---|---|---|---|---|
| Company A | Basic service | Small businesses | $ | Low price | Limited service |
| Company B | Premium service | Growing firms | $$$ | High quality | Expensive |
| Company C | Specialist service | Industry niche | $$ | Expertise | Smaller range |
The purpose isn’t simply to copy competitors.
It’s to identify opportunities.
9. Competitor Reviews Are a Goldmine
Customer reviews can reveal things that competitors’ marketing doesn’t mention.
A company might say:
“Fast, friendly and reliable.”
Customers may tell a different story.
They might complain about:
- Slow responses
- Complicated ordering
- Poor communication
- Hidden fees
- Difficult cancellations
- Product quality
- Delivery delays
AI can help analyse large numbers of reviews and identify recurring themes.
For example:
“Analyse these 200 customer reviews and identify the ten most common complaints.”
This can reveal opportunities.
If customers repeatedly complain about a competitor’s poor communication, perhaps excellent communication could become part of your value proposition.
10. Researching Market Size
AI can help you understand how to estimate market size.
Three useful concepts are:
TAM — Total Addressable Market
The total potential market if you could theoretically serve everyone.
SAM — Serviceable Available Market
The portion of the market your business could realistically target.
SOM — Serviceable Obtainable Market
The portion you might realistically capture.
For example:
Suppose there are 100,000 businesses in a broad market.
Perhaps 20,000 fit your customer profile.
If you could realistically reach 2,000 of them and expect to capture 100 customers initially, your practical opportunity is much smaller than the headline market.
AI can help you build the model.
But the underlying numbers need to come from reliable sources.
11. Don’t Ask AI to Guess Market Size
This is an important warning.
If you ask:
“How big is the market for mobile dog grooming in Chicago?”
AI may produce a number that sounds convincing.
But where did it come from?
If you cannot identify a reliable source, don’t treat the number as fact.
Instead ask:
“What data would I need to estimate the market size for mobile dog grooming in Chicago?”
Now AI can help you identify the methodology.
You might need:
- Number of households
- Number of dog-owning households
- Estimated percentage using grooming services
- Average annual spend
- Number of competitors
- Service capacity
You can then gather actual data and build your estimate.
AI should help you calculate the answer—not manufacture the evidence.
12. Researching Pricing
Pricing research can be extremely useful.
AI can help you compare:
- Competitor prices
- Different pricing models
- Subscription pricing
- Hourly rates
- Project pricing
- Product bundles
- Discounts
- Premium options
You could ask:
“Create a framework for comparing pricing among ten competitors in this market.”
You can then populate the framework with verified information.
AI can also help analyse the implications.
For example:
“If competitors charge between $500 and $900 for this service, what factors could justify positioning a new business at $1,000?”
This moves the conversation beyond simply copying competitors.
13. Researching Industry Trends
Markets change.
AI can help you identify topics worth investigating.
For example:
- New technologies
- Changing customer behaviour
- New competitors
- Changing distribution methods
- New business models
- Labour shortages
- Changing costs
- Consumer preferences
- Emerging regulations
You can ask:
“What developments could significantly affect this industry over the next three years?”
Then investigate the suggestions using current, reliable sources.
This is particularly important because AI’s built-in knowledge may not reflect the latest developments.
For current information, use AI alongside up-to-date research sources.
14. Researching Regulations
Businesses frequently need to understand rules and regulations.
AI can help explain complicated regulatory material in simpler language.
For example:
“Explain this regulation in plain English and identify the obligations that appear most relevant to a small business.”
This can be very useful for understanding documents.
However, don’t treat AI as the final authority on legal or regulatory requirements.
Verify important information against official government or regulatory sources.
If the consequences are significant, professional advice may also be appropriate.
15. AI for Document Research
Business research often means reading documents.
These might include:
- Industry reports
- Government publications
- Research papers
- Annual reports
- Competitor documents
- Supplier proposals
- Contracts
- Customer surveys
- Internal reports
AI can help summarise these documents.
For example:
“Summarise this report in 500 words. Then identify the five findings most relevant to a small business entering this industry.”
This can save considerable time.
16. Ask AI to Compare Documents
Suppose you have three supplier proposals.
Rather than reading them independently, you can ask AI to create a comparison framework.
For example:
| Factor | Supplier A | Supplier B | Supplier C |
|---|---|---|---|
| Price | |||
| Delivery | |||
| Warranty | |||
| Payment terms | |||
| Support | |||
| Contract length |
AI can help extract the relevant information.
You should still check the original documents before making an important decision.
17. Researching Suppliers
AI can help you develop a supplier research process.
Investigate:
- Price
- Minimum order quantities
- Delivery times
- Reliability
- Payment terms
- Warranty
- Support
- Location
- Capacity
- Reputation
- Certifications
You can then create a supplier scorecard.
For example:
Price: 25%
Quality: 25%
Reliability: 20%
Delivery: 15%
Support: 10%
Payment terms: 5%
AI can help you calculate and compare scores.
But don’t allow a spreadsheet score to replace judgement.
A supplier that scores well numerically may still have serious practical disadvantages.
18. Researching Locations
Location can make or break certain businesses.
AI can help you determine what information you need to investigate.
For a retail business, this might include:
- Population
- Foot traffic
- Demographics
- Competitors
- Parking
- Accessibility
- Rent
- Nearby businesses
- Development plans
- Customer income
- Local demand
AI can organise the research and help you compare locations.
But again, use current local data rather than relying on AI-generated assumptions.
19. AI for SWOT Analysis
A classic business-research tool is the SWOT analysis.
SWOT stands for:
Strengths
Weaknesses
Opportunities
Threats
AI can help you brainstorm each category.
For example:
Strengths
- Experienced founder
- Strong reputation
- Low overheads
Weaknesses
- Small team
- Limited marketing budget
- Dependence on founder
Opportunities
- Growing local demand
- Underserved customer segment
- New technology
Threats
- New competitors
- Rising costs
- Changing customer preferences
The important point is to distinguish between ideas generated by AI and facts supported by research.
20. AI for PESTLE Analysis
Another useful framework is PESTLE.
It examines:
Political
Economic
Social
Technological
Legal
Environmental
AI can help you brainstorm issues under each category.
For example, if you’re researching the future of home renovation:
Economic: Interest rates and construction costs
Social: Housing preferences
Technological: New building technologies
Legal: Building requirements
Environmental: Energy-efficiency expectations
Political: Government housing policy
This gives you a broader perspective than looking only at competitors.
21. Researching Business Opportunities
AI can be useful for generating business ideas.
But don’t stop at:
“Give me 20 business ideas.”
That’s easy.
A better approach is:
“Identify ten potential business opportunities that address recurring problems faced by small businesses. For each opportunity, explain the customer problem, potential solution, likely competitors, barriers to entry and questions I should research before investing.”
Now AI becomes a research partner rather than an idea generator.
You can then investigate the most promising opportunities.
22. AI for Scenario Analysis
Business decisions rarely have only one possible outcome.
AI can help you explore scenarios.
For example:
“What could happen to this business if sales increased by 20%, remained unchanged or declined by 20%?”
You could then examine:
Scenario A — Strong growth
Higher revenue
More staff required
Higher inventory
Greater cash-flow requirements
Scenario B — Flat sales
Stable operations
Pressure on margins
Limited expansion
Scenario C — Sales decline
Reduced revenue
Possible cost reductions
Greater financial pressure
This doesn’t predict the future.
It helps you think about it.
23. AI for “What If?” Questions
This is one of the most useful research applications.
Ask:
“What if our main supplier increased prices by 15%?”
“What if our biggest customer left?”
“What if we doubled our sales?”
“What if a new competitor entered the market?”
“What if labour costs increased by 10%?”
AI can help identify the consequences you should investigate.
This can reveal risks that you might otherwise overlook.
24. Researching Customer Feedback
If you’ve collected hundreds of customer comments, AI can analyse them.
It can identify:
- Common complaints
- Popular features
- Customer frustrations
- Frequently requested improvements
- Positive experiences
- Product problems
- Service problems
For example:
500 customer comments
→ 32% mention delivery
→ 24% mention product quality
→ 18% mention customer service
→ 14% mention pricing
→ 12% other
You now have a much clearer picture of what customers are talking about.
25. Turning Research Into Business Decisions
Research isn’t useful unless it changes something.
After completing your research, ask:
“So what?”
For example:
Research finding:
Customers strongly value fast delivery.
Possible business decision:
Offer guaranteed next-day delivery for premium customers.
Research finding:
Customers dislike complicated onboarding.
Possible decision:
Create a simplified onboarding process.
Research finding:
Competitors are expensive but offer poor customer support.
Possible decision:
Position the business around responsive service.
This is where research becomes strategy.
26. Ask AI to Challenge Your Assumptions
One of the most powerful uses of AI is as a devil’s advocate.
Tell it:
“I believe this is a good business opportunity. Challenge my assumptions and identify the strongest reasons I might be wrong.”
This can be surprisingly useful.
AI might identify:
- Unproven demand
- Overestimated market size
- Strong competitors
- High startup costs
- Regulatory barriers
- Customer-acquisition difficulties
- Weak margins
You can then investigate those risks.
This is much better than using AI simply to confirm what you already believe.
27. Use Multiple Perspectives
Don’t ask AI only:
“Why will this business succeed?”
Also ask:
“Why could this business fail?”
Then:
“What would an experienced competitor say?”
Then:
“What would a skeptical investor question?”
Then:
“What evidence would prove or disprove these assumptions?”
This creates a much more balanced research process.
28. AI for Research Reports
Once you’ve completed your research, AI can help organise the findings into a report.
A simple business research report might contain:
Executive Summary
The key findings.
Research Objective
What you were trying to discover.
Market
Size, characteristics and trends.
Customers
Needs, behaviour and preferences.
Competitors
Main competitors and positioning.
Pricing
Typical market pricing.
Opportunities
Potential gaps in the market.
Risks
Major threats and uncertainties.
Recommendations
What the research suggests you should do next.
This can turn a collection of notes into a professional business document.
29. Separate Facts, Assumptions and Opinions
This is one of the most important habits when using AI for research.
Label information as:
Fact
Supported by reliable evidence.
Assumption
Something you currently believe but haven’t confirmed.
Interpretation
Your understanding of what the evidence means.
Opinion
A judgement or recommendation.
For example:
Fact: Competitor A charges $500.
Assumption: Customers will pay $600 for better service.
Interpretation: There may be room for premium positioning.
Recommendation: Test a $600 package with a small group of customers.
This distinction makes your research much stronger.
30. Check the Sources
Whenever research matters, ask:
Where did this information come from?
Good sources may include:
- Government agencies
- Industry associations
- Academic research
- Company filings
- Reputable research organisations
- Official company websites
- Reliable statistical databases
- Primary customer research
Be cautious with:
- Unsourced blogs
- Anonymous posts
- Outdated articles
- AI-generated statistics
- Unverified claims
- Websites copying information from other websites
AI can help you find information, but you are responsible for deciding whether the evidence is trustworthy.
31. Don’t Let AI Create Fake Evidence
This is one of the biggest risks.
You might ask:
“Find five studies proving customers prefer this type of product.”
AI may produce impressive-looking references.
If you cannot verify those studies, don’t use them.
Instead ask:
“What evidence should I look for to determine whether customers prefer this product?”
Then conduct the research properly.
A plausible-looking citation isn’t the same thing as reliable evidence.
32. Use Primary Research Whenever Possible
AI can help you analyse information, but it cannot replace talking to your customers.
Consider conducting:
- Customer interviews
- Surveys
- Product tests
- Focus groups
- Sales interviews
- Feedback sessions
Then give the results to AI for analysis.
For example:
“Here are 100 survey responses. Identify the five strongest themes and provide examples of the types of responses supporting each theme.”
Now AI is analysing your actual customer data rather than guessing what customers think.
33. AI and Competitive Intelligence
Competitive intelligence means systematically monitoring your market and competitors.
You might monitor:
- New products
- Pricing changes
- New locations
- Hiring
- Marketing campaigns
- Partnerships
- Customer reviews
- New technology
- Company announcements
AI can help summarise changes.
For example:
“Compare these competitor updates with last quarter and identify significant changes.”
This can turn competitor research into an ongoing process rather than a once-a-year exercise.
34. Build a Research Dashboard
For important markets, create a simple research dashboard.
It might track:
| Area | What to Monitor |
|---|---|
| Customers | Needs and complaints |
| Competitors | Products and prices |
| Market | Size and growth |
| Technology | New developments |
| Costs | Major cost changes |
| Regulations | New requirements |
| Suppliers | Availability and pricing |
| Opportunities | New market gaps |
AI can help summarise updates across these categories.
This gives you an early-warning system for changes that could affect the business.
35. AI for Strategic Planning
Once you’ve completed your research, AI can help turn it into strategy.
You could ask:
“Based on this research, identify five strategic options for the business.”
Then ask:
“Compare these options based on potential revenue, cost, risk, complexity and likely time to implement.”
Finally:
“What assumptions would need to be true for each option to succeed?”
This creates a structured decision-making process.
36. AI Doesn’t Make the Decision for You
This is crucial.
AI can help answer:
“What does the available information suggest?”
It shouldn’t automatically answer:
“What should I do?”
The final decision belongs to the business owner.
You understand things AI doesn’t fully understand:
- Your risk tolerance
- Your finances
- Your relationships
- Your capabilities
- Your goals
- Your personal circumstances
- Your knowledge of the market
AI can improve your thinking.
It shouldn’t replace it.
37. A Practical AI Business Research Workflow
A useful research process looks like this:
Step 1: Define the decision
What are you actually trying to decide?
Step 2: Define the research questions
What do you need to know?
Step 3: Identify reliable sources
Where can you obtain the evidence?
Step 4: Gather information
Collect reports, data, customer feedback and other relevant material.
Step 5: Use AI to organise it
Summarise, classify and compare information.
Step 6: Identify patterns
Look for recurring themes and significant differences.
Step 7: Challenge the findings
Ask AI to identify weaknesses and alternative explanations.
Step 8: Verify important facts
Check significant claims against original sources.
Step 9: Develop options
Turn research findings into possible actions.
Step 10: Make the decision
Use your judgement and the evidence available.
38. A Worked Example
Imagine you own a small landscaping business and are considering adding garden-maintenance subscriptions.
Your initial question is:
“Would customers pay a monthly fee for ongoing garden maintenance?”
You could use AI to develop a research plan.
Research Question 1
Who is most likely to buy?
Research Question 2
What competitors offer subscription services?
Research Question 3
What do they charge?
Research Question 4
What services are included?
Research Question 5
What complaints do customers have about existing providers?
Research Question 6
What would it cost us to provide the service?
Research Question 7
What would customers need to save or gain to make the subscription worthwhile?
You then collect actual evidence.
AI helps analyse the evidence.
Finally, you might discover:
Opportunity: Customers want predictable garden maintenance.
Problem: Existing providers have complicated pricing.
Potential solution: Simple monthly packages.
Risk: Labour availability may limit capacity.
Next step: Test the subscription with 20 existing customers.
That’s a much stronger conclusion than simply asking AI:
“Should I start a garden-maintenance subscription?”
39. Common Mistakes to Avoid
Mistake 1: Asking overly broad questions
Be specific about the decision you’re researching.
Mistake 2: Believing AI-generated statistics
Verify important numbers.
Mistake 3: Using outdated information
Markets change quickly.
Mistake 4: Confirming your existing beliefs
Actively look for evidence that challenges your assumptions.
Mistake 5: Relying only on secondary research
Talk to real customers.
Mistake 6: Confusing correlation with causation
Two things happening together doesn’t necessarily mean one caused the other.
Mistake 7: Ignoring the original source
Whenever possible, read important evidence yourself.
Mistake 8: Doing research without making a decision
Research should ultimately lead to action.
40. Your Practical AI Business Research Project
Now put the process into practice.
Choose one real business decision.
It might be:
- Launching a new product
- Entering a new market
- Raising prices
- Hiring employees
- Choosing a supplier
- Opening another location
- Introducing a new service
- Changing your marketing strategy
Then complete the following process.
Part 1: Define the decision
Write down exactly what you’re trying to decide.
Part 2: Create ten research questions
Ask AI to help you identify the information you need.
Part 3: Identify your sources
Separate reliable primary and secondary sources.
Part 4: Gather evidence
Collect actual information.
Part 5: Give the information to AI
Ask it to organise and summarise the material.
Part 6: Identify patterns
Look for common themes and important differences.
Part 7: Challenge the conclusion
Ask:
“What could make this analysis wrong?”
Part 8: Separate evidence from assumptions
Label facts, assumptions, interpretations and recommendations.
Part 9: Create three options
Develop realistic courses of action.
Part 10: Make your decision
Choose the option that makes the most sense based on the evidence, your resources and your objectives.
Conclusion
Business research used to be a task that could consume days or weeks.
AI doesn’t eliminate the need for research, but it can dramatically improve the process.
It can help you formulate questions, organise information, analyse customer feedback, compare competitors, summarise reports, explore scenarios, identify patterns and challenge your assumptions.
Perhaps most importantly, AI allows a small business owner to approach research more systematically.
But remember the golden rule:
AI can help you find and understand evidence. It does not automatically make the evidence true.
Use reliable sources. Verify important facts. Talk to real customers. Challenge your assumptions. Separate facts from opinions. And don’t allow an impressive-looking AI answer to substitute for genuine research.
The best business researchers aren’t necessarily the people who know everything.
They’re the people who know what they don’t know, ask good questions, find reliable evidence and use that evidence to make better decisions.
AI can make you much better at all four.