12 Days of AI Use Cases Day 8: Business Card Extraction

Welcome to the 12 Days of AI Use Cases, 2025 Edition! Today: Business card extraction

In this series, we’ll be looking at different use cases for AI – in particular, generative AI and large language models, the software that powers tools like ChatGPT, Google Gemini, and Anthropic Claude. Each day, we’ll look at the use case through the lens of the Trust Insights 5P Framework to see the role AI plays in achieving real, tangible outcomes.

We designed these use cases not only for reading but also as context you provide to generative AI tools as part of a prompt to help you achieve the outcomes you’re after. Ask the generative AI tool of your choice to help you implement this use case and copy/paste it in as part of the Trust Insights RACE AI prompt framework – this goes in the Context portion of our prompt framework.

Let’s dig in!

Purpose

We extract contact information from multiple business cards simultaneously using vision language models to accelerate data entry into CRM systems. Sales professionals and event attendees collect dozens of business cards at conferences and trade shows, and they need to transfer this information quickly without manual data entry. This use case eliminates the need for specialized scanning hardware or tedious card-by-card transcription. We use smartphone photography combined with AI vision models to process multiple cards at once, converting analog contact information into structured digital formats. The outcome is faster lead follow-up and reduced administrative burden for sales teams.

People

Sales professionals, business development representatives, and account executives perform this use case after attending trade shows, conferences, networking events, or client meetings. They capture business card information in bulk and prepare it for immediate upload to their CRM or contact management systems. These professionals prioritize time efficiency because they need to focus on relationship-building and sales activities rather than data entry tasks.

Sales operations teams, marketing operations professionals, and CRM administrators receive the extracted contact data for quality validation and system integration. They ensure the imported records meet data governance standards and correctly map to existing fields in the organization’s systems. These stakeholders benefit from receiving structured data that requires minimal cleanup or reformatting.

Prospective clients and business contacts whose information appears on the business cards represent the external audience impacted by this use case. They expect timely follow-up communication after sharing their contact information at events. The speed and accuracy of the extraction process directly influences how quickly they receive relevant outreach from the sales professional.

Process

1. Collect business cards from networking events, trade shows, conferences, or client meetings throughout the day or event period
2. Select up to 20 business cards to process in a single batch for optimal camera capture and AI processing efficiency
3. Arrange the business cards on a flat, neutral-colored surface (such as a light table, floor, or large sheet of paper) with all cards oriented in the same direction
4. Ensure adequate lighting conditions exist to minimize shadows and glare on the card surfaces
5. Use a smartphone camera set to its highest resolution setting to photograph the arranged business cards from directly above
6. Review the captured image to verify that all text on all cards appears clear, legible, and in focus before proceeding
7. Upload the photograph to a vision language model such as ChatGPT (GPT-4 with vision), Google Gemini, or Anthropic Claude
8. Provide a prompt instructing the AI to extract specific data fields from each visible business card, including first name, last name, job title, company name, phone number, email address, physical address, and any other relevant fields
9. Specify the desired output format (CSV, JSON, or structured table format) that matches your CRM import requirements
10. Review the AI-generated output for accuracy, checking for any OCR errors, missing fields, or misinterpreted information
11. Make manual corrections to any fields the AI misread or failed to capture completely
12. Download or copy the structured data file in your specified format
13. Import the formatted contact data into your CRM, email marketing platform, or contact management system using the platform’s standard import functionality
14. Verify that the imported records appear correctly in your system with all fields properly mapped
15. Archive or dispose of the physical business cards according to your organization’s data retention and privacy policies

Platform

• Vision-capable AI models (ChatGPT with GPT-4 Vision, Google Gemini, or Anthropic Claude with vision capabilities)
• Smartphone with high-resolution camera (minimum 12 megapixels recommended)
• CRM system (Salesforce, HubSpot, Microsoft Dynamics, Pipedrive, or similar contact management platform)
• Neutral-colored flat surface for card arrangement (poster board, table, or floor with solid background)
• Adequate lighting source (natural light, desk lamp, or overhead lighting to eliminate shadows)
• CSV or JSON import capability in target CRM or contact management system
• Physical business cards collected from events, meetings, or networking activities
• Data validation process or checklist to verify accuracy before system import
• Internet connection for uploading images to AI models and downloading extracted data

Performance

We measure success when sales professionals reduce business card data entry time from approximately 2-3 minutes per card to under 30 seconds per card using batch processing. The extracted contact data achieves 95% or higher accuracy rates for standard business card formats, requiring minimal manual correction before CRM import. Sales teams complete post-event follow-up activities 50-75% faster because they spend their time crafting personalized outreach rather than typing contact information.

1. Time saved per business card: Measure the reduction in minutes spent on data entry by comparing manual entry time (baseline 2-3 minutes per card) against AI-assisted extraction time (target 30 seconds or less per card including quality review)
2. Data accuracy rate: Calculate the percentage of correctly extracted fields across all business cards processed, targeting 95% or higher accuracy for name, title, company, phone, and email fields
3. Follow-up response time: Track the reduction in hours or days between event attendance and first contact outreach to new leads, targeting at least 50% improvement in time-to-first-contact metrics

We hope this use case is clear and helpful. If you’d like help implementing it or any other AI use case, reach out and let us know.

Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.