Organizations are rapidly adopting AI, yet many initiatives struggle because they focus on technology before trust.
The Trust Acceleration Index™ (TAI™) and N-Tier Transparency Exchange™ (NTX™) provide a practical framework for strengthening AI Guardrails by measuring trust readiness, managing controlled data sharing, and establishing the governance needed for responsible AI.
Leaders will learn how trust, transparency, reciprocity, and controlled information exchange create the foundation for AI systems that are explainable, accountable, secure, and trusted across the enterprise and supply network.
Agenda
1. Why AI Needs Trust
2. Understanding AI Guardrails
3. The Trust Acceleration Index™ (TAI™)
4. N-Tier Transparency Exchange™ (NTX™)
5. Fortifying AI Guardrails with TAI™ and NTX™
6. The AI Trust Flywheel
TAI™ → NTX™ → Trusted AI → Better Decisions → Higher Adoption → Greater Trust
Deliverables
1. A framework for assessing AI trust readiness using TAI™.
2. A model for implementing AI Guardrails through NTX™.
3. Tools for identifying trust, governance, and transparency gaps.
4. Practical approaches for responsible AI deployment.
5. Design principles for creating trusted AI-enabled enterprises and ecosystems.
Presenters
► Greg Schlegel, CPIM, CSP, Jonah
CEO & Founder, The Supply Chain Risk Management Consortium
► Jim de Vries, LSS MBB, CSCP
CSO, The SCRM Consortium | Founder & Managing Partner, Enhance International Group
Key Takeaways
AI is only as trustworthy as the environment in which it operates.
By combining TAI™ and NTX™, organizations can establish the trust, governance, transparency, and controlled collaboration necessary to transform AI from a technology initiative into a sustainable competitive advantage.
Trusted AI requires trusted data, trusted relationships, and trusted governance.
