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AI Data Assist: Intelligent Analysis for CXO Financial Reporting

AI Data Assist is CXO's new intelligent analysis feature that transforms how you interact with financial data in your reports. Powered by insightsoftware's Lineos AI, this feature analyzes table data on demand to generate meaningful insights, identify trends, and create narrative explanations that help you understand the story behind your numbers. Whether you need immediate analysis for decision-making or compelling narratives for stakeholder reports, AI Data Assist delivers powerful, AI-driven insights that enhance your financial reporting workflow.

AI Data Assist represents a significant advancement in intelligent financial reporting. By combining the analytical power of Lineos AI with CXO's robust reporting platform, we're enabling finance professionals to generate deeper insights and more compelling narratives with unprecedented efficiency and accuracy.

Note: The CXO application server needs to connect to the internet to be able to make the API call to the Lineos AI service. Please contact your Customer Success Manager or Account Manager to obtain the necessary API key and to obtain further instructions on how to enable Lineos AI. You only need to activate the API key once to use all Lineos AI features. Besides, Lineos AI needs to be enabled in the Configurator Settings before you can use AI Data Assist.

What AI Data Assist Does

AI Data Assist leverages advanced artificial intelligence to provide comprehensive table analysis within your CXO reports. The system processes your financial data to generate insights about patterns, trends, anomalies, and key drivers affecting your business performance. Beyond simple data summarization, AI Data Assist creates contextual narratives that explain what the numbers mean and why changes are occurring.

The feature incorporates multiple data layers into its analysis, including primary table numeric data, expanded drill-down information available in your reports, and any existing line narratives you've already created. This comprehensive approach ensures that AI-generated insights are informed by the full context of your data structure and existing analytical work.

Comprehensive Data Analysis

What Gets Analyzed

AI Data Assist examines three critical components of your table data:

Primary Table Data: All numeric values, calculations, and metrics visible in your table are processed to identify trends, variances, and significant changes across time periods or business dimensions.

Expanded Drill-Down Data: When users open drill-down layers before running AI Data Assist, the system analyzes these expanded data views and recognizes relationships between high-level summary data and underlying detail. This provides insights that go beyond surface-level numbers to understand underlying performance drivers.

Existing Line Narratives: Any current narrative content on your tables is incorporated into the analysis, allowing AI Data Assist to build upon your existing explanations and provide enhanced context.

Strategic Implication

This comprehensive analysis capability makes well-designed tables with relevant drill-downs significantly more valuable to your reporting process. Tables that include meaningful hierarchical structures, appropriate time-series comparisons, and logical drill-down paths will generate richer, more actionable AI insights when users proactively expand the drill levels they want analyzed. Organizations should consider their table design strategy as an investment in AI-powered analysis quality, while users should strategically open relevant drill-downs before running AI analysis to maximize insight depth.

Interactive Analysis Workflow

Initial Analysis

When you activate AI Data Assist on an eligible table, the system provides a comprehensive first-pass analysis that examines all available data layers. This initial analysis typically includes trend identification, variance explanations, key performance highlights, and potential areas of concern.

Follow-Up Capabilities

The true power of AI Data Assist emerges through its interactive capabilities. After receiving your initial analysis, you can engage in follow-up conversations to:

  • Focus on Specific KPIs: Direct the AI to analyze particular metrics or business drivers in greater detail

  • Request Advanced Analytics: Ask for statistical analysis including correlation calculations, seasonality identification, and trend forecasting

  • Explore Data Relationships: Investigate connections between different metrics or business dimensions

  • Deep-Dive Analysis: Examine specific anomalies, outliers, or performance variations with targeted questions

This interactive approach transforms AI Data Assist from a simple analysis tool into a collaborative analytical partner that can adapt its insights to your specific business questions and reporting needs.

Current Scope: Tables Only

Why Tables First

Our initial release focuses exclusively on tables because they represent the most data-dense elements in financial reports. Tables contain structured, quantitative information that allows AI Data Assist to deliver maximum analytical value and generate the most meaningful insights for narrative creation.

The interactive capabilities of AI Data Assist work particularly well with tabular data, where users can easily reference specific cells, rows, or columns when asking follow-up questions. Additionally, the drill-down capabilities inherent in CXO tables provide the AI with rich contextual data layers that enhance analysis quality.

Future Expansion

Charts, graphs, and other visualizations will be added to AI Data Assist scope in future releases. Our development roadmap includes extending AI capabilities to analyze trends in line charts, patterns in bar graphs, and other advanced visualizations.

Table Eligibility Requirements

Supported Tables

AI Data Assist currently works with tables that meet the following criteria:

  • Standard Single-Source Tables: Tables that draw data from a single data source or connection

  • Visible Column Headers: Tables with clear, accessible column headers that provide context for data interpretation

  • Static Tables: Tables with fixed structure that don't depend on external control inputs for their data display

Currently Excluded Tables

To ensure analysis accuracy and system stability, the following table types are temporarily excluded from AI Data Assist:

  • Multisource Reports: Tables that combine data from multiple sources may present data integration complexities that could affect analysis quality

  • Hidden Column Headers: Tables with concealed headers lack the contextual information necessary for accurate AI interpretation

  • Control-Dependent Tables: Tables that listen to other report controls for input create dynamic data scenarios that require additional development consideration

These exclusions are temporary limitations as we continue to enhance AI Data Assist capabilities. Future releases will expand support to include these more complex table configurations.

Two Primary Use Cases

1. Interactive Analysis Consumption

Use AI Data Assist as your analytical partner for immediate insights and decision-making support. Review the initial AI-generated analysis to quickly understand key trends, performance drivers, and areas requiring attention. Engage in follow-up conversations to explore specific business questions, validate assumptions, or investigate unusual patterns in your data.

This use case is particularly valuable during monthly closes, board preparation, or when you need to quickly understand performance variations across different business dimensions.

2. Manual Narrative Enhancement

Transform AI-generated insights into compelling report narratives by copying relevant analysis content and pasting it into your desired CXO narrative fields. Whether you need content for key messages, line narratives, annotations, or main comment sections, AI Data Assist provides professionally written explanations that you can customize to match your organization's tone and reporting requirements.

The manual copy-paste approach gives you complete control over which insights to include, how to position them, and how to integrate AI-generated content with your existing narrative strategy.

Getting Started

Prerequisites

  • AI Data Assist enabled at installation level

  • User or user group permissions granted for AI Data Assist access

  • Access to CXO reports with eligible tables

  • Familiarity with CXO narrative fields and reporting workflow

  • Understanding of your data sources and business context

Recommended Initial Approach

  1. Start with your most data-rich, well-structured tables.

  2. Begin with simple analysis requests before exploring advanced features.

  3. Compare AI insights with your existing understanding to calibrate expectations.

  4. Gradually incorporate AI-generated content into your regular reporting process.

Support Resources

  • Best practices documentation for table design and drill-down optimization

  • Technical support for troubleshooting and advanced use cases

Administrative Controls & Access

Installation-Level Configuration

AI Data Assist can be enabled or disabled at the CXO installation level, giving organizations complete control over feature deployment. This allows IT administrators to manage AI capabilities across their entire CXO environment based on organizational policies, security requirements, or rollout strategies.

User and Group-Level Permissions

Within CXO applications, AI Data Assist access can be granted or restricted at both individual user and user group levels. This granular permission structure enables organizations to:

  • Control which teams have access to AI capabilities

  • Manage feature rollout by department or role

  • Align AI access with existing security and governance frameworks

  • Customize deployment based on user training and readiness

To enable AI Data Assist at the user or user group level, select Access AI Data Assist in the Permissions page for the specific users or user groups.

The Permissions page with the Access AI Data Assist option for enabling AI Data Assist at the User or User Group Level

User Workflow

AI Data Assist follows a simple workflow designed to ensure users remain fully in control of the narrative content. It also allows users to process multiple eligible tables in a report at once.

  1. Expand all drills to maximize the data scope available to AI.

    Important: Drills cannot be expanded after AI Data Assist has been activated. Be sure to set up the exact view you want analyzed before engaging the feature.

  2. Click the Lineos icon on the toolbar at the top right.

    Note: The Lineos icon is available when you have the Access AI Data Assist permission and the current report contains at least one eligible table.

  3. All eligible tables are automatically selected and highlighted in light purple.

    You can deselect any table by clicking it directly. Deselected tables appear with purple borders — distinct from both selected tables and non‑eligible components — making them easy to locate if you want to reselect them later.

    The bottom bar (left side) displays the number of selected components for your reference.

  4. If column headers are hidden using the "Hide Column Headers" parameter, you can make them visible again by deselecting Hide Column Headers in the report settings. This ensures that AI Data Assist can deliver meaningful and accurate analysis.

  5. Select Start AI Analysis on the bottom bar to receive comprehensive insights.

    You can resize the Lineos window or reposition it anywhere on your screen to make browsing the content easier.

  6. Review the initial analysis and ask follow-up questions as needed.

  7. Choose relevant portions of the AI-generated analysis for your reporting needs.

  8. Transfer selected content into appropriate CXO narrative fields, like the key message box, line narratives, annotations, and the main comment section.

    Note: To preserve text formatting when copying content from Lineos, please use Ctrl + V manually instead of clicking the Copy icon.

    Example 1: Copy to Comments:

    Example 2: Copy to the main comment section:

  9. Modify the content to match your organization's tone, style, and specific requirements.

Workflow Considerations

  • Drill-Down Preparation Required: Users must manually open desired drill-down layers before running AI Data Assist; the AI analyzes only currently visible data.

  • Manual Integration Required: AI Data Assist does not automatically populate narrative fields; users must manually copy and paste content into desired locations.

  • User Discretion: Users are responsible for selecting appropriate content for each narrative field and ensuring contextual relevance.

  • Content Customization: Generated content should be reviewed and edited to match organizational standards and specific reporting contexts.

AI Considerations

  • Human Review Essential: All AI-generated content requires human validation for accuracy, relevance, and appropriateness before use in final reports.

  • Domain Expertise Critical: While AI provides valuable insights, human expertise remains essential for strategic interpretation and business context.

  • Best Practices: Treat AI-generated content as a starting point for narrative development rather than final output.

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