AI data readiness and governance.
Buyers do not just want AI ideas; they want confidence that LoganAI will protect data, prevent bad automation, and help people actually use the tools. Every engagement is designed with practical controls: permission-aware data access, human review for high-impact actions, measurable evaluation, and continuous improvement.
Six pillars of trustworthy AI
A practical governance model that keeps AI useful and safe, without turning every engagement into a compliance marathon.
Business ownership
Assign use-case owners, process owners, data stewards, technical owners, and approval roles.
Why it matters: AI fails when nobody owns the workflow after the demo.
Risk classification
Classify use cases by business risk, data sensitivity, automation level, and human-review requirements.
Why it matters: not every AI use case deserves the same controls.
Data protection
Define approved tools, data boundaries, retention, access, and permission-aware retrieval.
Why it matters: ERP data includes sensitive financial, customer, supplier, and pricing information.
Evaluation
Create test sets, expected answers, source-citation checks, hallucination checks, accuracy targets, and escalation paths.
Why it matters: production AI needs measurement, not vibes.
Human-in-the-loop
Require approval before material decisions, transactions, master-data changes, or external communications.
Why it matters: human judgment remains critical in ERP-driven operations.
Adoption
Train users by role, redesign workflows, and monitor usage, feedback, and value realization.
Why it matters: AI value comes when work changes, not when a tool is announced.
How we say it: Logan designs AI with practical controls, permission-aware data access, human review for high-impact actions, measurable evaluation, and continuous improvement.
Built on the NIST AI Risk Management Framework
NIST organizes AI risk management around four functions. We use them as an accessible foundation for your AI governance, sized to the risk of each use case.
Govern
Set policy, ownership, and accountability so AI has a home and clear rules before it scales.
Map
Understand context, data, and risk for each use case, and classify the controls it deserves.
Measure
Evaluate accuracy, citations, and drift against test sets and targets, not anecdotes.
Manage
Monitor in production, keep humans in the loop, and continuously improve as work changes.
The five risks we manage in the open
The easiest way to lose trust is to sound like everyone else. Here is exactly how we handle the risks buyers worry about.
| Risk | How Logan addresses it |
|---|---|
| Data privacy | Use approved enterprise tools, define retention, respect permissions, and avoid unmanaged public AI tools for sensitive client data. |
| Hallucination | Use source-grounded retrieval, citations, human review, test sets, and confidence thresholds. |
| Bad automation | Use human approval gates for financial, customer, supplier, master-data, pricing, and external-communication actions. |
| Low adoption | Train by role, embed AI into actual workflows, and track usage and business KPIs. |
| Tool sprawl | Start with architecture, governance, and use-case strategy before adding another point solution. |
What we say
- ERP-aware AI, grounded in your data and business process
- Practical pilots tied to measurable outcomes
- Human-governed automation and AI readiness before AI rollout
- Workflow redesign, not just tool adoption
What we avoid
- AI transformation without a business-process anchor
- Autonomous ERP claims that imply unmanaged posting or commitments
- Generic chatbot language and claims that AI fixes bad data by itself
- Overpromising productivity gains without measurement
Our mantra: AI should make the right work easier, not make the wrong work faster.
Related AI pages
Is your ERP ready for AI?
Start with an ERP AI Readiness Check. In a few weeks we assess your data quality, security constraints, governance gaps, and architecture options, then hand you a clear roadmap before you roll anything out.
Two North Riverside Plaza, Suite 1440, Chicago, IL 60606 · 312-345-8800 · info@loganconsulting.com
