Data components display and interact with your records. By adding AI capabilities to components, you can create dynamic, intelligent interfaces that respond to user input, generate content on the fly, and provide contextual assistance. This article covers implementing AI in tables, details, and other data components.

Table components show lists of records. AI can enhance tables by:

• Generating content for displayed records
• Providing quick actions for AI operations
• Creating dynamic summaries
• Intelligent categorization and tagging

Add AI-powered action links that users can click from table rows.

Common Use Cases:

• "Generate Description" - Create content for records missing descriptions
• "Enhance Content" - Improve existing content
• "Summarize" - Create brief version of long content
• "Categorize" - Auto-assign categories
• "Translate" - Convert to different language

Scenario: Content management table where users can enhance articles with AI.

Table Columns:

• Article Title
• Author
• Draft Content
• Status
• Actions

AI Action Links:

"Generate SEO Title"

Create an SEO-friendly title (60 characters max) for this article:

Content: {Draft Content}
Target Keywords: {Target Keywords}

Make it compelling and click-worthy.

"Improve Readability"

Improve the readability of this content:

{Draft Content}

Make it:
- Easier to understand
- Better structured with clear paragraphs
- More engaging
- Grammatically correct

Maintain the original meaning and tone.

"Generate Excerpt"

Create a compelling 2-3 sentence excerpt for:

{Draft Content}

Make it enticing and summarize the key value.

Allow users to select multiple records and apply AI to all at once.

Implementation:

1. Enable record selection in table
2. Add bulk action link
3. Configure AI to process selected records
4. Show progress and results

Example: Bulk Categorization

Categorize this item into one of these categories:
- Electronics
- Home & Garden
- Clothing
- Sports
- Books

Item: {Product Name}
Description: {Description}

Respond with just the category name.

Details components show individual record information. AI can enhance details by:

• Generating additional insights about the record
• Creating related content dynamically
• Providing contextual recommendations
• Answering questions about the record

Display AI-generated content that updates based on record data.

Use Cases:

• Insights: Show AI analysis of record data
• Recommendations: Suggest related actions
• Summaries: Condense complex information
• Explanations: Explain technical data in simple terms

Scenario: CRM customer detail page with AI-generated insights.

AI Insight Field:

Analyze this customer profile and provide insights:

Customer: {Company Name}
Industry: {Industry}
Total Revenue: ${Total Revenue}
Number of Orders: {Order Count}
Average Order Value: ${Average Order}
Last Order Date: {Last Order Date}
Support Tickets: {Ticket Count}
Status: {Status}

Provide:
1. Customer Health Score (Healthy/At Risk/Churning)
2. Key Opportunities (2-3 bullet points)
3. Concerns or Risks (if any)
4. Recommended Next Actions (2-3 specific steps)

Be concise and actionable.

Display:

Show AI insights in a prominent card on the customer detail page, refreshed when data changes.

Provide AI actions relevant to the specific record being viewed.

Example: Sales Opportunity Actions

"Generate Proposal"

Create a proposal for this opportunity:

Company: {Company Name}
Industry: {Industry}
Requirements: {Requirements}
Budget: ${Budget Range}
Timeline: {Timeline}
Decision Makers: {Contacts}

Include:
- Executive summary
- Proposed solution
- Pricing overview
- Implementation timeline
- Next steps

"Draft Follow-Up Email"

Write a follow-up email for this opportunity:

Company: {Company Name}
Last Contact Date: {Last Contact Date}
Stage: {Stage}
Last Interaction: {Last Notes}

Create a personalized, engaging email to move the deal forward.

The AI Prompt Component is a dedicated component for interactive AI interactions. Users can ask questions or give instructions, and AI responds based on page context and record data.

Setting Up AI Prompt Component

1. Add AI Prompt component to page
2. Configure context (which record data AI can access)
3. Set placeholder text for user input
4. Customize appearance
5. Define scope and limitations

Scenario: E-commerce product page with AI assistant.

Available Context:

• Product Name, Description, Specifications
• Price, Availability
• Reviews and Ratings
• Related Products

System Prompt:

You are a helpful product assistant. Answer questions about this product based on the available information:

Product: {Product Name}
Description: {Description}
Specifications: {Specifications}
Price: ${Price}
Rating: {Average Rating} ({Review Count} reviews)

Provide helpful, accurate answers. If information isn't available, say so. Keep responses concise and friendly.

Example Questions:

• "Is this suitable for outdoor use?"
• "How does this compare to similar products?"
• "What's included in the box?"
• "Will this work with my existing setup?"

Dynamic Questions use AI to generate contextual questions or prompts based on the current record and user interactions. This creates adaptive, intelligent user experiences.

Scenario: Onboarding questionnaire that adapts based on customer type.

AI Logic:

Based on this customer information:

Company Size: {Company Size}
Industry: {Industry}
Use Case: {Primary Use Case}
Current Question: {Last Question Answered}

Generate the next most relevant question to understand their needs better. Make it specific to their industry and use case.

Format: Just the question text, no explanation.

Result:

For a healthcare company, AI asks about HIPAA compliance. For retail, asks about inventory volume. Each path is dynamically personalized.

Similar to tables, but with card-based layout. AI can:

• Generate preview summaries
• Create dynamic descriptions
• Provide quick actions
• Generate card titles/subtitles

AI can enhance calendar views by:

• Generating event summaries
• Creating descriptions from minimal data
• Suggesting optimal scheduling
• Generating meeting agendas

Example: Meeting Agenda Generator

Create a meeting agenda for:

Meeting: {Meeting Title}
Duration: {Duration} minutes
Attendees: {Attendees}
Purpose: {Purpose}
Previous Meeting Notes: {Last Meeting Notes}

Generate a structured agenda with:
- Time allocations for each topic
- Clear objectives
- Action items from last meeting to review

Format as bulleted list.

Use AI to create text descriptions of chart data and trends.

Example: Sales Chart Narrative

Analyze this sales data and provide insights:

Total Sales: ${Total Sales}
Sales Growth: {Growth Percentage}%
Top Product: {Top Product Name} (${Top Product Revenue})
Worst Performing: {Worst Product Name}
Month-over-Month Trend: {Trend}

Provide:
1. Brief summary (2-3 sentences)
2. Key insights (3 bullet points)
3. Recommendations (2 specific actions)

Keep it executive-level and actionable.

Generate executive summaries for data dashboards.

Implementation:

1. Add text component to dashboard
2. Configure AI to analyze page data
3. Generate summary on page load
4. Update when filters change

AI that understands the full context of what's on the page.

Available Context:

• Current record data
• Connected record data
• Page filters and parameters
• User information
• Related records displayed

Use This For:

• Comprehensive analysis
• Intelligent recommendations
• Contextual help
• Smart defaults

Start with basic data, progressively enhance with AI as user explores.

Pattern:

1. Page loads with basic record data
2. User clicks "Show AI Insights"
3. AI generates additional analysis
4. User can dig deeper with follow-up questions

Benefit:

Fast initial load, AI only when needed, reduced costs.

Cache AI-generated content to avoid regeneration.

Implementation:

1. Generate AI content
2. Store in dedicated field
3. Display cached version
4. Regenerate only when source data changes
5. Show "Updated X minutes ago" timestamp

Let users rate AI output to improve quality.

Implementation:

• Add "Was this helpful?" buttons
• Collect feedback
• Track which prompts work best
• Refine prompts based on feedback
• Show improved results over time

You now understand how to implement AI in various data components. The next article covers page-level AI features including page assistants and smart search.

Hands-On Exercise (To Be Added)

Exercise placeholders will include practical activities such as:

• Adding AI action links to a table component
• Creating an AI insights field in a details component
• Setting up an AI Prompt component for user Q&A
• Building dynamic questions that adapt to user input

Knowledge Check (To Be Added)

Quiz questions will test understanding of:

• Best use cases for AI in different component types
• Implementing AI Prompt components
• Performance optimization for component AI
• User experience best practices