5 posts tagged “AI Assist”
What the Maximo Assistant actually is, the IBM watsonx.ai foundation models that power it, and the Maximo AI Service that connects the two. A grounded introduction to generative AI in MAS 9 — including an honest map of what it does and, just as importantly, what it does not do.
Surendra KattaJul 16, 2026Part 1 of 8
The feature people mean when they say 'AI in Maximo.' How the Maximo Assistant drafts a work order from a plain-English description, replaces filter queries with natural-language asset search, and recommends field values — priority, work type, failure codes, craft — each with a confidence score you can accept, modify, or reject.
Surendra Katta
A grounded eight-part series on the watsonx-powered Maximo Assistant and the AI features of MAS 9.1 and 9.2 — the watsonx.ai foundation, natural-language work guidance, knowledge capture, guided troubleshooting, the AI Service deployment path, governance and AppPoints, supply chain (querying items, inventory, and PRs natively vs building item-creation, PR-drafting, and similarity tools on the 9.2 MCP server), and an October 2026 capability map. Written for teams who want to know what generative AI in Maximo actually does, and what it does not.
How the watsonx-powered Maximo Assistant and AI Service handle natural language queries and field recommendations — plus Optimizer's constraint-based scheduling with route optimization. Also covers Civil Infrastructure and Parts Identifier.
Posam LakshminarayanaMar 17, 2026Part 14 of 25
A complete technical breakdown of every MAS 9 suite add-on that impacts supply chain operations — AI Assist (intelligent search, WO material recommendations, failure-to-parts mapping, document summarization), Parts Identifier (photo-based identification, catalog cross-reference, stock level checks), Health (scores driving demand predictability, replacement procurement, criticality stocking), Predict (failure timing to pre-position parts, RUL-based reservations), Monitor (condition-based orders, IoT consumption tracking, usage pattern analytics), and Optimizer (material-aware scheduling, multi-constraint coordination). The complete AI-to-parts pipeline.
Posam LakshminarayanaMar 17, 2026Surendra Katta