Executive Summary

In a digitally driven business world, the concept of trust has multiple meanings, and it is heavily influenced by audiences who receive or anticipate digital trust. When trust is discussed in relation to artificial intelligence (AI) and the concerned audience, the intrinsic value of the technology should be emphasized, and trust anchored around the value.

Top performing companies recognize sustainability, reliability, and good governance as a win-win situation and incorporate these dimensions in their planning and strategy from the get-go. They approach safe, secure and reliable dimensions of customer experience that we refer to as AI Trust as revenue-enablers instead of cost center. This is a possibility and a reality. Consequently, this feeds quantifiable high-value data into your ESG initiative.

The trust placed on AI should be prioritized and built around key value chains of impacted users and audience. In order to achieve trust that is worthy of this paradigm, the focus should be on customers first in tandem with organizational stakeholders, external regulators, and society at large, particularly when AI is placed in the market has societal impact.

There is an inflection point in terms of AI Trust that is at the waiting end of regulation, expecting that it will level the playing field. While this is not a bad bargain, it has several disadvantages.  In general, reaction to the passing of legislation is reactive, and our collective experience has demonstrated that it is not in the interest of business to take a proactive role in incorporating compliance-by-design in anticipation of legislation. More importantly, this is not a customer-centric design and often requires reverse engineering to implement customer-specific controls and safeguards.

This whitepaper anchors AI Trust through the lens of customers, and their relationship with business.

The meaning of AI Trust can be conceptualized, but its clarity and definition is evolving topics and its implementation requires intentional, purpose-driven rigor and accountability. The article outlines an end-to-end approach to a well-aligned AI Trust Paradigm inclusive of customer needs, management, and regulatory requirements.

If we want to live in a world where customers feel heard and understood, trust and performance must go hand in hand.

Our AI Trust story starts with Customer. Customers’ trust varies depending on whether their interactions with AI afford a safe, secure, and reliable environment, on prevailing laws and regulations, and on other environmental factors.

We recognize enabling best practices in AI Trust is a journey anchored on effective AI Governance.  

Adaptive.AI offers a customer-centric service offering to unlock performance and trust for superior customer and stakeholder experience while protecting your AI investments.

Learn more about the central theme, a tier-model approach – Pivot, Transform and Adapt – to maximize AI performance by building trust and a detailed AI Trust Taxonomy by downloading a copy of the eBook.