What is the business case for investing in trustworthy AI design?
Quick Answer: 70% of AI initiatives fail due to poor user adoption and trust issues, not technical flaws. Investment of $400K-$2.5M annually prevents $2-5M revenue loss from customer churn. Top clients now demand proof of trustworthy AI implementation in procurement, especially in regulated sectors.
- 70% of customers will switch brands after a single poor AI interaction
- Australia's AI trust dropped 16 points below global average (KPMG)
- Trust Equation: Competence + Reliability + Transparency + Value Alignment
- Most organizations lack comprehension, agency, and failure-mode testing protocols
A government contract was lost when an agency failed to demonstrate transparency guarantees. Banking executives now demand explainability and compliance proof before procurement. The Four Design Pillars (Human Agency, Trust Formation, Bias Mitigation, Comprehensive Testing) address these requirements.
Frequently Asked Questions
What is the Trust Equation for AI?
Trust = Competence + Reliability + Transparency + Value Alignment. All four components must be present for users to trust AI systems.
What testing do most organizations lack?
Most organizations lack comprehension testing (do users understand?), agency testing (can users control?), and failure-mode testing (what happens when AI fails?).