Building Confidence for AI Inside OpenText VIM

Interest in applying artificial intelligence within OpenText Vendor Invoice Management continues to grow. Intelligent capture, assisted matching, and guided exception handling offer clear potential to reduce manual effort, and yet many organizations still remain cautious about where and how to begin.

At McCloy Data we see confidence as the critical ingredient. Successful early AI use cases typically share three characteristics:

• They address a well-understood, high-volume pain point

• They rest on reasonably clean data and clear process rules

• They retain meaningful human oversight and clear escalation paths

Rather than pursuing broad transformation claims, we help clients identify contained, low-risk pilots that deliver measurable reduction in exceptions or processing time. These pilots create both operational value and organizational learning that build a foundation for the confidence needed for broader adoption.

This measured approach aligns with our AI philosophy: assess readiness, prioritize use cases that respect existing investments, and introduce capability incrementally. The result is progress that feels sustainable rather than disruptive.

If your team is exploring where intelligent capture or AI-assisted decision support might fit within your current VIM landscape, we would welcome a thoughtful discussion about a practical starting point.