JMP and AI: Where LLM Integration Meets the Analytic Workflow (2026-US-30MP-2955)

Scientists and engineers are being told to incorporate artificial intelligence (AI)-integrated strategies into their workflows. While there are many options available to do this, no one wants to sacrifice rigor or trust in the results just to say they're using AI.

JMP’s value proposition remains unchanged: an interactive, end‑to‑end analytic workflow that supports exploration, modeling, and reporting. JMP shines when problems are complex, multivariate, and new. These are the same places where statistical thinking and human judgment are essential and where pre‑trained AI models fall short because they lack training data.

JMP treats LLMs as accelerators for analytic workflows, not as replacements. LLMs can help new users learn faster, surface advanced capabilities that would otherwise sit unused, and generate custom JMP scripts from plain language prompts. These integrations are grounded in authoritative JMP documentation and executed entirely by JMP, so the results are correct and reproducible.

This presentation provides an overview of JMP's holistic approach to LLM integration, giving organizations multiple options to include JMP in their AI strategy. Together, JMP and LLM integration will improve efficiency while preserving rigorous scientific and engineering decisions.