Data · dataset · 2026
Cognitive Business Autonomous Intelligence (CBAI): A GenAI‑Driven AIoT Framework for Unified Workforce Analytics, Predictive FinOps, and Circular Economy Marketplaces
Listed in Teesside University Research Data Repository
The convergence of Artificial Intelligence of Things (AIoT) and Generative AI (GenAI) represents a paradigm shift toward autonomous enterprise systems.
Description
Current implementations remain siloed: AIoT provides assistive insights while GenAI operates in cognitive domains, disconnected from real-time physical operations. This paper introduces Cognitive Business Autonomous Intelligence (CBAI)—a holistic framework integrating GenAI-powered autonomous agents with pervasive AIoT sensor networks to create self-managing enterprise ecosystems.
CBAI enables simultaneous optimization across three critical domains: (1) autonomous workforce analytics through real-time biometric sensing and dynamic task allocation; (2) predictive financial operations (FinOps) via continuous AIoT data streams for forecasting and risk mitigation; and (3) tokenized circular economy marketplaces for automated material reuse and sustainability compliance. We evaluate CBAI using a multi-agent simulation environment benchmarking against conventional ERP systems.
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Results demonstrate: workforce productivity improvements of 15–30%, financial forecast error reductions of 10–25%, and material reuse increases of 20–35%. A Blockchain-based governance layer ensures transparency, auditability, and ethical compliance. CBAI establishes both a technical architecture and research agenda for next-generation autonomous enterprises that simultaneously optimize economic, human, and environmental outcomes
Links
Where it is published
- DOI doi.org/10.17632/xxcv866gmw.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/xxcv866gmw.1 | 14 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |