Supplementary Materials for "An Architectural Pattern for Conversational and Agentic BPM with Model Context Protocol, Generative AI, and Defense in Depth: A Validated Instance and Formative Study"

Supplementary materials supporting the IEEE Access manuscript on a validated instance of an architectural pattern for AI-Augmented Business Process Management Systems (ABPMS). Materials are organized in nine logical packages (A–I) covering: component benchmarks across six LLM models (A); stochastic ablation of ten defensive layers (B); LLM-real multi-provider ablation of pre-LLM layers L1+L2 across five models in two capability tiers — tier small/fast (Anthropic Claude Haiku 4.5, OpenAI GPT-4o-mini, Google Gemini 2.5 Flash) and tier large (Anthropic Claude Sonnet 4, OpenAI GPT-4o) — totalling 1,000 LLM calls (C); formative study with N=25 lay users recruited via Prolific BR — anonymized data, briefing, and Apps Script form (D); statistical analysis including bootstrap BCa confidence intervals, Kruskal–Wallis omnibus test with exact permutation, MDE sensitivity analysis under observed dispersion, and robustness analyses (E); production engineering metrics during the pilot window (F); operational characterization of the 54 process versions generated by participants (G); per-agent layer mapping (H); and the detailed protocol of the structured state-of-the-art mapping including search strings, PRISMA-style flow, the I1–I4 inclusion criteria and E1–E4 exclusion criteria table, and the extraction template (I). All Prolific participant identifiers have been replaced with sequential pseudonyms P01..P45 (the 45 unique respondents effectively represented in the deposited dataset); the internal mapping is retained by the authors under documented request for audit purposes.