**Summary** For organizations to realize significant business advantages from their AI investments, customer trust is essential. Systemic social mistrust in AI can only be overcome if inquiries regarding the technology’s functioning—posed by customers, regulators, and relevant stakeholders—are sufficiently addressed. Employing blockchain-based accountability provides a feasible and practical approach to ensuring both accountability and enforceability. FICO has created a private blockchain that automates the documentation and standards involved in model development. This strategy has accelerated the introduction of AI and analytical innovations while also maintaining the ongoing production of new models; notably, blockchain has decreased support issues and model recalls by over 90%.

Implementing this system proved to be more of a challenge related to people than to technology. They discovered that beginning with clear standards is crucial, followed by the development of the technology; creating a user-friendly interface was imperative; iterating on quick wins was essential; establishing repositories for large AI assets in alternative storage was necessary; and maintaining capable IT teams to manage the system's maintenance requirements was vital. In a remarkably brief timeframe, organizations spanning various industries have integrated artificial intelligence (AI) to make decisions that significantly impact individuals' daily lives. AI often reflects our biases and moral shortcomings, which can lead to unfortunate and even devastating outcomes. Bias is just one of many factors contributing to AI’s perception as a “black box” with a trust issue. A study by Pew Research last year revealed that 52% of Americans feel more concerned than excited about AI in everyday life, while only 10% express more excitement than concern.