How to Conduct Market Research with AI: Prompts and Workflows 2026

How to get market insights in days instead of months

Why AI is essential for market research today

• Speed: OCR models like Baidu’s Unlimited-OCR process multi-page PDFs and high-resolution images in seconds.
• Scalability: Claude Opus 5-type agents can extract structured data, generate survey questions, and even conduct interviews autonomously.
• Depth: New frameworks like OpenSpace allow agents to evolve over time, learning from user responses and improving insights.

The result is a research cycle that once took months can now be completed in a few days, at a fraction of the cost.

Which AI tools to use for market research

The most effective combination of tools in 2026 is as follows:

1. OCR for data acquisition
2. LLM for insight extraction
3. Agentic AI for automation

These three components together create an end-to-end pipeline that you can replicate for any market niche.

Step-by-step workflow

Use Unlimited-OCR to extract text from reports, industry PDFs, or survey images.

import requests
import json

url = "https://api.baidu-ocr.com/v1/recognize"
headers = {"Authorization": "Bearer YOUR_KEY", "Content-Type": "application/json"}
payload = {
    "image": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA...",
    "pdf": "https://example.com/report.pdf"
}
response = requests.post(url, headers=headers, json=payload)
print(json.loads(response.text)["text"])

Action: Save the extracted text to a cloud bucket (e.g., AWS S3) for later access.

Send the raw text to Claude Opus 5 and ask it to transform the data into structured insights.

prompt = """
Analyze the following market text and provide:
1. Total market size (if indicated)
2. Emerging trends in list format
3. Three growth opportunities for a company entering this space.

Text:
{text}
"""
response = client.chat.completions.create(
    model="claude-5-opus",
    messages=[{"role": "user", "content": prompt}]
)
print(response.choices[0].message.content)

Action: Parse the JSON response and store each insight in a database (e.g., PostgreSQL) for future reporting.

Build an agent that automatically publishes these insights to internal dashboards, generates follow-up questions for interviews, or sends email alerts when new trends appear.

from openspace import Agent, Skill

class MarketInsightAgent(Agent):
    def __init__(self):
        super().__init__(name="MarketInsightBot")
        self.add_skill(PublishDashboardSkill())
        self.add_skill(GenerateSurveySkill())
        self.add_skill(AlertOnTrendSkill())

agent = MarketInsightAgent()
agent.run(trigger="new_insight", data=insight_dict)

Action

Practical prompt examples for market research

Prompt 1: Executive summary

prompt = """
Create a 250-word executive summary for a CMO on:
- Market size (if available)
- Key growth drivers
- Three recommended strategic moves

Use a professional tone and bullet points.
"""

Prompt 2: Interview question generation

prompt = """
Based on the following market trends, generate 8 qualitative interview questions for industry stakeholders.
1. {trend_1}
2. {trend_2}
3. {trend_3}
Provide only the questions, one per line.
"""

Prompt 3: Sentiment analysis

prompt = """
Analyze the sentiment of the following user comments.
Return:
- Positive sentiment: X%
- Neutral: Y%
- Negative: Z%
- Three emerging keywords.

Comments: {comments}
"""

Current trends in 2026 that are shaping market research

• Claude Opus 5: The new agentic model offers programming and computer use capabilities at no additional cost over the previous version, making it ideal for end-to-end automation.
• Baidu Unlimited-OCR: Solves the problem of low-quality image handling and multi-page PDF processing, dramatically speeding up data acquisition.
• OpenSpace: Its lineage-based architecture allows agents to self-evolve, maintaining traceability and reducing operational costs.

Incorporating these tools into your market research stack keeps you ahead of competitors and reduces time-to-insight from months to days.

Concrete actions you can take today

1. â..."... Set up a Baidu Unlimited-OCR account and test extraction on a sample industry PDF.
2. â..."... Sign up for the Claude Opus 5 beta and experiment with the executive summary prompt.
3. â..."... Download the OpenSpace SDK and create an agent that automatically publishes results to your dashboard.
4. â..."... Log the results in a data warehouse and set up alerts for new trends.

These actions will give you an immediate competitive advantage and show you how to conduct market research with AI effectively in 2026.

Conclusion

Market research no longer has to be a costly, slow process. With OCR, LLMs, and agentic AI, you can build an automated workflow that extracts, analyses, and acts on market data in just a few days. Start experimenting with the tools mentioned today and turn raw data into strategic actions based on concrete insights.

**IMPORTANT**: We are in 2026. All temporal references must be current. Do not mention past years such as 2024, 2023, etc. The content must be fresh and relevant to the present. **CURRENT CONTEXT (July 2026)**: Here are some recent trends and news stories to inspire you: - OpenAI Presence sells enterprise AI agents with engineers attached: The newest way to buy enterprise AI agents from OpenAI does not involve buying anything online. OpenAI Presence, announced on July 22, is a managed ... [2026-07-24] - OpenAI pushes ChatGPT into patient health records: OpenAI is deploying a Health feature inside ChatGPT, giving users the option to connect Apple Health data and medical records to the chatbot. Logged-i... [2026-07-24] - Meet the New Claude Opus 5: Frontier-Class Agentic Coding and Computer Use at Unchanged Opus Pricing: Today, Anthropic released Claude Opus 5. It replaces Claude Opus 4.8 as the Opus-tier flagship. Pricing is unchanged at $5 per million input tokens ... [2026-07-24] Use this current information as inspiration to create an original and relevant prompt for 2026.