OpenText Core Experience Insights - Azure AI Document Intelligence Integration and Automation

Common Integration Use Cases Between OpenText Core Experience Insights and Azure AI Document Intelligence

1. Measure adoption of AI-driven document processing workflows

Data flow: Azure AI Document Intelligence ? OpenText Core Experience Insights

Organizations can use Azure AI Document Intelligence to extract data from invoices, forms, claims, or onboarding documents, then send workflow and usage events into OpenText Core Experience Insights. This allows business and operations teams to track how often document automation is used, where users still intervene manually, and which document types create the most friction.

• Identify low-adoption departments or regions
• Measure reduction in manual data entry over time
• Spot process bottlenecks by document type

Business value: Improves automation governance and helps teams prioritize process redesign based on actual usage patterns.

2. Analyze employee interaction with document review and exception handling screens

Data flow: Azure AI Document Intelligence ? OpenText Core Experience Insights

When extracted data requires human review, OpenText Core Experience Insights can capture how users interact with validation screens, correction steps, and approval tasks. This is especially useful in accounts payable, claims processing, and compliance review workflows where exceptions are common.

• Track time spent correcting extraction errors
• Measure completion rates for review tasks
• Identify screens or fields that cause repeated user drop-off

Business value: Reduces processing delays and improves the design of exception-handling workflows.

3. Optimize document intake channels based on user behavior

Data flow: OpenText Core Experience Insights ? Azure AI Document Intelligence

OpenText Core Experience Insights can reveal which document submission channels users prefer, such as portal uploads, email intake, or mobile capture. These insights can be used to adjust Azure AI Document Intelligence processing rules, classification models, and intake routing logic for the most common document sources.

• Prioritize high-volume intake channels for automation tuning
• Adjust extraction models based on document source quality
• Route low-quality submissions to manual review earlier

Business value: Improves extraction accuracy and reduces rework by aligning document processing with real user behavior.

4. Correlate content engagement with document-driven process outcomes

Data flow: Bi-directional

In customer onboarding, procurement, or HR workflows, documents extracted by Azure AI Document Intelligence can be linked to content and application usage metrics in OpenText Core Experience Insights. Teams can then correlate whether users who engage with specific forms, policy documents, or instructions complete processes faster or with fewer errors.

• Compare completion rates across different document sets
• Measure whether guidance content reduces exceptions
• Identify content that improves self-service success

Business value: Supports continuous improvement of both document processing and user guidance content.

5. Monitor compliance workflow effectiveness for regulated documents

Data flow: Azure AI Document Intelligence ? OpenText Core Experience Insights

For regulated processes such as KYC, vendor onboarding, or contract intake, Azure AI Document Intelligence extracts key fields from submitted documents while OpenText Core Experience Insights tracks how users complete compliance steps. Compliance teams can see where users abandon tasks, which documents trigger the most exceptions, and whether policy updates are being followed.

• Track completion of mandatory compliance steps
• Measure exception rates by document category
• Identify training needs for specific teams

Business value: Improves audit readiness and reduces compliance risk through better visibility into process execution.

6. Improve customer service case handling with document and interaction analytics

Data flow: Azure AI Document Intelligence ? OpenText Core Experience Insights

In service operations, Azure AI Document Intelligence can extract data from customer-submitted forms, claims, or supporting documents. OpenText Core Experience Insights can then measure how service agents interact with the resulting case records, knowledge articles, and workflow tools. This helps identify whether document automation is actually reducing handling time and improving agent productivity.

• Compare average handling time before and after automation
• Track agent usage of extracted data in case resolution
• Identify training gaps when agents bypass automated fields

Business value: Enhances service efficiency and ensures automation delivers measurable operational gains.

7. Continuously improve document templates and user journeys

Data flow: Bi-directional

Azure AI Document Intelligence can surface extraction errors tied to specific document templates, while OpenText Core Experience Insights shows how users navigate the related submission or review journey. Together, these platforms help teams refine both the document templates and the surrounding user experience.

• Detect which form fields cause repeated extraction failures
• Identify user steps that lead to incomplete submissions
• Prioritize template redesign based on actual process friction

Business value: Creates a closed-loop improvement cycle across document capture, processing, and user experience.

8. Support enterprise reporting on automation ROI

Data flow: Azure AI Document Intelligence ? OpenText Core Experience Insights

Business leaders can combine extraction volumes, exception rates, and processing outcomes from Azure AI Document Intelligence with engagement and adoption metrics from OpenText Core Experience Insights to build a more complete view of automation ROI. This is useful for finance, operations, and transformation teams managing multiple document-heavy initiatives.

• Quantify manual effort reduced by document automation
• Track adoption of new digital workflows across teams
• Measure whether process changes are improving user engagement

Business value: Provides executive-level visibility into the impact of automation investments and supports better prioritization of future initiatives.