Tagged articles

enterprise ontology

5 articles · Page 1 of 1

Oct 20, 2026 · Artificial Intelligence

Five-Layer Architecture for Embedding AI into Enterprise Business Processes

This article presents a five-layer architecture for embedding AI into enterprise business processes — infrastructure, AI foundation, capability services, business orchestration, and applications — while emphasizing cross-cutting governance, shadow labor costs, a four-level evolution path from assistance to autonomy, and data flywheels as the true competitive moat.

AI architectureAI evolution levelsAI governance

0 likes · 7 min read

Five-Layer Architecture for Embedding AI into Enterprise Business Processes

Digital Deification

Oct 17, 2026 · Industry Insights

AI Pilots Impress But Stall: The Real Bottleneck Is Organizational, Not Technical

The article argues that enterprise AI transformation fails not due to model limitations but because organizational structures, incentives, and governance don't adapt to human-AI collaboration, detailing five conflict areas and a coupled approach where ontology and organizational redesign must evolve together through iterative, business-led pilots.

AI transformationchange managementdigital transformation

0 likes · 12 min read

AI Pilots Impress But Stall: The Real Bottleneck Is Organizational, Not Technical

Data Bricklaying Diary

Oct 12, 2026 · R&D Management

Start with One Scenario or Build Full Ontology? Preventing Pilot Silos

The article advocates starting enterprise ontology with a verifiable business capability like supplier qualification checks, defining object identity, scope, shared definitions, and maintenance responsibilities upfront, then using a second scenario to test reuse boundaries while tracking dependencies for future changes.

architecture decision recordsdata governancedependency tracking

0 likes · 14 min read

Start with One Scenario or Build Full Ontology? Preventing Pilot Silos

AI Large-Model Wave and Transformation Guide

Sep 10, 2026 · Artificial Intelligence

Enterprise Ontology: Beyond Semantics to Organizational Change for Trustworthy AI

The article argues that enterprise ontology for AI is not merely a technical semantic layer but a catalyst for organizational transformation, requiring continuous governance, cross-functional consensus, and structural changes to prevent silent semantic decay and build trustworthy AI agents.

AI governanceSemantic Decayenterprise ontology

0 likes · 13 min read

Enterprise Ontology: Beyond Semantics to Organizational Change for Trustworthy AI

Digital Deification

Aug 15, 2026 · Artificial Intelligence

Enterprise Ontology: The Missing Foundation for Business-Savvy AI Agents

This article argues that deploying AI agents alone does not achieve true enterprise intelligence; a unified enterprise ontology — defining core business objects, attributes, relationships, and rules — is essential as a semantic layer between systems and agents, enabling AI to reason over business logic rather than just query data.

AI agentsBusiness LogicERP Integration

0 likes · 15 min read

Enterprise Ontology: The Missing Foundation for Business-Savvy AI Agents