Neuro-symbolic AI for enterprise systems: Transforming CRM & ERP through logical and statistical AI integration

Neuro-Symbolic AI (NSAI) represents a paradigm shift in enterprise software by integrating deep learning capabilities with symbolic reasoning frameworks to address critical limitations in current AI implementations for Customer Relationship Management and Enterprise Resource Planning systems. This hybrid approach combines the pattern recognition strengths of neural networks with the logical inference capabilities of symbolic AI, creating intelligent systems that offer enhanced explainability, improved reasoning, and more transparent decision-making processes. By bridging statistical machine learning with rule-based symbolic processing, NSAI enables enterprises to develop AI solutions that simultaneously learn from data while respecting explicit business rules and regulatory constraints. The integration facilitates advanced applications across sales optimization, compliance monitoring, risk management, customer service automation, and supply chain intelligence, ultimately delivering enterprise systems that balance adaptability with accountability while maintaining human oversight in critical business processes.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-05-09
DOI
https://doi.org/10.30574/wjaets.2025.15.2.0491
Citations
1
Primary Topic
Advanced Research in Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
1.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Neuro-symbolic AI for enterprise systems: Transforming CRM & ERP through logical and statistical AI integration

Siva Prasad Sunkara
1 citations
World Journal of Advanced Engineering Technology and Sciences
Advanced Research in Systems and Signal Processing
1.21
article

Neuro-symbolic AI for enterprise systems: Transforming CRM & ERP through logical and statistical AI integration

Siva Prasad Sunkara
article en
1 citations

Abstract

Neuro-Symbolic AI (NSAI) represents a paradigm shift in enterprise software by integrating deep learning capabilities with symbolic reasoning frameworks to address critical limitations in current AI implementations for Customer Relationship Management and Enterprise Resource Planning systems. This hybrid approach combines the pattern recognition strengths of neural networks with the logical inference capabilities of symbolic AI, creating intelligent systems that offer enhanced explainability, improved reasoning, and more transparent decision-making processes. By bridging statistical machine learning with rule-based symbolic processing, NSAI enables enterprises to develop AI solutions that simultaneously learn from data while respecting explicit business rules and regulatory constraints. The integration facilitates advanced applications across sales optimization, compliance monitoring, risk management, customer service automation, and supply chain intelligence, ultimately delivering enterprise systems that balance adaptability with accountability while maintaining human oversight in critical business processes.

World Journal of Advanced Engineering Technology and SciencesVol. 15(2)
Openalex Percentile: Top 22%
Advanced Research in Systems and Signal Processing
1.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Neuro-symbolic AI for enterprise systems: Transforming CRM & ERP through logical and statistical AI integration — Siva Prasad Sunkara · World Journal of Advanced Engineering Technology and Sciences (2025) | TGRS Research Map | TGRS