In the Age of AI, Who Owns Trust?

As generative AI spreads across business functions, companies experiment with Chief Trust Officers to close a widening credibility gap.

When it comes to handling AI in the corporate world, there’s a clear designation of responsibility. The CIO owns the tech stack. The CCO owns compliance and risk. But who owns trust in the age of generative AI? More companies are experimenting with Chief Trust Officers (CTrOs) tasked with governing algorithm ethics, data use, and stakeholder confidence. But a title alone won’t fix the widening trust gap.

In a Deloitte survey, 74 percent of respondents reported that GenAI makes it harder for them to trust online content. But the problem is not limited to misinformation and AI-generated videos; Generative AI is also eroding consumer trust. 

As more companies embed GenAI across customer support, marketing, hiring, insurance underwriting, and healthcare intake, customers often cannot tell when they are interacting with an algorithm, how their data is being used, or how decisions are being made. The result is a credibility deficit: companies may be innovating faster than they can explain it all to stakeholders.

It’s no longer enough for corporations to make AI decisions responsibly; companies must also explain them clearly and proactively. Hence, the need for a CTrO shaping how organizations talk about automation, transparency, and decision-making. Ultimately, a CTrO must prioritize disclosure. 

Where Trust Breaks Down

Trust most often erodes at the point where organizations blur the line between human and AI interaction. One of the Chief Trust Officer’s core responsibilities is to define – and publicly clarify – where automation ends and verified human judgment begins. As generative AI becomes embedded in customer support, marketing, HR, and sales, companies must decide not only where automation is appropriate, but also where human accountability is essential. And it is not enough to make those decisions internally; customers and employees must be clearly informed when AI is involved.

These choices are not abstract ethical debates. They are operational decisions that affect daily interactions. Where is it acceptable for customers to receive AI-generated responses? When must they know they are speaking to a human representative? Are blended experiences permissible – and if so, how will that be disclosed? The absence of consistent standards in these moments is where confusion and eventually distrust begin.

Marketing is one of the clearest pressure points. Brands now routinely use AI to generate ad copy, product descriptions, and influencer-style content. Without disclosure standards, consumers may not realize that the imagery, testimonials, or endorsements shaping their purchasing decisions are synthetic. When AI-generated claims prove inaccurate or exaggerated, credibility suffers. The CTrO’s office would establish guardrails, requiring teams to disclose when content is AI-generated and to verify that automated claims meet the same standards as human-created materials.

Data use presents an equally significant trust challenge. Customers increasingly understand that their chats, uploads, and service interactions may be used to train AI systems. If that process is unclear or buried in dense legal language, suspicion grows. A trust-first organization explains plainly what data is collected, how it is anonymized, whether it contributes to model training, and how individuals can opt out. The CTrO’s role is to ensure that privacy commitments align with actual practice, and that disclosures are written for human comprehension, not legal defensibility.

Trust Is a Business Outcome

For many executives, trust still feels intangible – important, but difficult to quantify. That mindset is changing. More people are recognizing that trust directly affects revenue, retention, and risk exposure. If customers suspect that AI is manipulating pricing, misusing data, or replacing human accountability, they will disengage. Regulators will intervene. Employees will hesitate to adopt tools they don’t understand.

A CTrO turns ethical AI from a general principle into specific practices the organization can enforce and measure. That means establishing governance frameworks, audit trails, and reporting structures that demonstrate accountability. It means aligning AI use with brand promises. And it means preparing for a regulatory landscape that is rapidly evolving, from data-protection laws to emerging AI-specific disclosure requirements.

Importantly, the CTrO cannot operate in a silo. Trust must be embedded across the organization from product design and engineering to marketing and customer experience. The CTrO’s role is to coordinate these efforts, ensuring that AI deployment aligns with corporate values and stakeholder expectations.

Importantly, the Chief Trust Officer does not need to be a standalone, full-time role. In many organizations, trust functions as a responsibility assigned to existing executives-most often the Chief Privacy Officer or Chief Experience Officer. What matters is not the title, but clear ownership of transparency, disclosure, and AI-driven decision accountability.

Final Thoughts

In the corporate world, AI governance is about both risk mitigation and retaining credibility. In an environment where customers are skeptical and misinformation is rampant, companies that can demonstrate transparency will stand out. Consequently, those who fall behind will struggle to make amends. Once consumer trust is lost, it’s difficult to get back. 

While skeptics view the CTrO as little more than a symbolic hire, establishing the role is a strategic decision – one that gives companies the chance to distinguish themselves on the basis of trust. As GenAI continues to change the face of industry, the CTrO presents an opportunity executives can’t afford to lose.