Practical AI in SAP Invoice Automation: What OpenText VIM Can Do Today

Practical AI in SAP Invoice Automation: What OpenText VIM Can Do Today

AI is creating new possibilities in accounts payable, but many organizations are still trying to determine what is real, which capabilities are available today, and where it can create meaningful business value.

That was the focus of our recent webinar, Practical AI in SAP Invoice Automation: What OpenText VIM Can Do Today, presented in conjunction with OpenText. Rather than discussing fully autonomous finance or future-state concepts, we focused on practical AI capabilities that are already helping organizations improve invoice processing, reduce manual effort, and strengthen AP operations.

AI's Role in AP: Remove Friction, Not People

One of the biggest takeaways was that AI works best as an augmentation tool, not a replacement for finance teams.

Across the invoice lifecycle, organizations continue to face challenges such as:

• Manual invoice coding and validation
• Exception handling and approval delays
• Inconsistent invoice formats and data quality
• Compliance and fraud risks

The opportunity is to apply AI where the friction exists while keeping people, governance, and business rules firmly in control.

What AI Can Do Today in OpenText VIM

Many of the most impactful capabilities are already available in current OpenText VIM and Core Capture releases, including:

Smarter Capture

• Machine learning-based invoice extraction
• Vendor and business partner identification
• Learning from previously posted invoices
• Enhanced extraction of payment terms and item descriptions

Better Automation

• Smart invoice coding suggestions
• Intelligent field mapping
• Payment-term matching based on supplier contracts
• Automated translation of workflow comments

Stronger Risk Controls

One of the most compelling examples demonstrated during the session was AI-assisted detection of changes to supplier banking information. When invoice data doesn't match what's stored in SAP, VIM can automatically flag the discrepancy for review before payment is released, helping reduce risk while maintaining auditability.

Preparing for AI Success

Technology alone isn't enough. Successful AI adoption starts with strong fundamentals:

• Clean vendor, material, and master data
• Consistent PO and goods receipt processes
• Clearly defined governance and controls
• Measurable pilot use cases
• Platform and release readiness

Organizations that focus on these foundational elements will be better positioned to scale AI successfully.

The Bottom Line

The conversation around AI in finance is rapidly shifting from experimentation to execution. The good news is that organizations don't need to wait for fully autonomous finance to begin realizing value.

Practical AI capabilities are already available today, helping AP teams improve capture accuracy, reduce manual effort, accelerate exception handling, and strengthen operational controls.

The future of invoice automation isn't about replacing people, it's about helping them work smarter, faster, and with greater confidence.͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏  ͏