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AI Readiness Checklist|logistics

AI Readiness Checklist for Logistics & Supply Chain

Assess your organization's readiness to adopt AI in logistics & supply chain. This comprehensive checklist evaluates 40 critical areas across 5 categories — from SAP TM / SAP IBP data infrastructure to executive alignment — giving you a clear score and actionable roadmap.

Understanding Your Score

Strategic interpretation of your readiness results

0-20%

Just Starting

You need foundational work before AI adoption

21-40%

Building Foundation

Focus on data infrastructure and team building

41-60%

Getting Ready

You're making progress. Address gaps in governance and skills

61-80%

AI Ready

You're well-positioned for AI. Start with pilot projects

81-100%

AI Leader

You're ready for enterprise-scale AI deployment

Recommended Next Steps

Actionable path forward based on your readiness assessment results.

Current Readiness0%
1

Identify Your Top Logistics & Supply Chain AI Use Case

Review your checklist gaps and select the AI use case with the highest impact-to-effort ratio. Focus on addressing "Fuel and labor costs consuming 60 - 70%..." as a starting point.

2

Assess and Close Data Gaps

Ensure your SAP TM / SAP IBP data is clean, accessible, and governed before investing in AI models. Data readiness is the most common bottleneck.

3

Build or Acquire AI Talent

Determine whether to build an internal team, partner with an AI consultancy, or use a hybrid approach. Logistics & Supply Chain domain expertise combined with AI skills is critical.

4

Start with a Pilot Project

Launch a focused pilot targeting On-time delivery rate with an 8-12 week timeline and clear success criteria.

5

Establish Governance Early

Put AI policies and FMCSA (Federal Motor Carrier Safety Administration) frameworks in place before scaling. Governance is much harder to retrofit after deployment.

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