Enhancing Asset Management with AI-Driven Solutions: A Maximo Implementation Case Study

January 21, 2026
301A
Optimizing Plant Performance

Utilities are under growing pressure to manage increasingly complex generation assets with precision, scalability, and efficiency. Evergy, along with 1898 & Co., is demonstrating how advanced technologies can transform asset management. By enhancing its IBM Maximo deployment with generative AI, optical character recognition, computer vision and semantic parsing, Evergy has streamlined its asset onboarding, improved data fidelity and reduced manual workloads.

This session will walk through how structured data was extracted from engineering documents—including P&IDs, one-lines, equipment lists and DCS I/O files—to deliver a more accurate, automated asset capture. Attendees will gain insights into how utilities and operators can leverage AI to improve asset quality, reduce risk and build a stronger foundation for long-term reliability.

Chairperson
Kevin Riner
Kevin Riner, Sr. Manager Reliability - Evergy, Inc.
Speakers
Kim Hart
Kim Hart, Lead Reliability Analyst Lead Reliability Analyst - Evergy
Chris Wiles
Chris Wiles, AI Solutions Architect - 1898 & Co.