In the Age of AI, Companies Need a Chief Trust Officer – Unite.AI

By
Every company knows who manages technology and risk. The Chief Information Officer runs the tech stack. The Chief Compliance Officer makes sure regulations are followed. But as artificial intelligence takes on a larger role in decisions, another question is harder to answer: who is responsible for trust?
That question isn’t abstract. Generative AI is already writing emails, drafting policies, answering customer questions, and shaping hiring or financial choices. Employees and customers often can’t tell what’s real, who wrote a message, or whether a decision came from a person or an algorithm. That uncertainty doesn’t just frustrate—it erodes confidence in the organization itself.
To close that gap, some companies are experimenting with a new role: Chief Trust Officer. The mandate is broad—guarding ethics, overseeing data use, and protecting stakeholder confidence. But a title alone won’t solve the problem. Trust isn’t built by adding another name to the org chart; it comes from how clearly companies explain their choices.
Whenever I speak with CEOs about AI, the mood is the same: excitement mixed with exhaustion. Everyone sees the potential, but real business value is harder to measure. Yet the bigger risk isn’t wasted investment – it’s the erosion of trust.
As companies lean on bots, templates, and auto-filled replies, communication begins to lose the cues that signal credibility: tone, intent, and presence. Messages may still deliver information, but without those cues, they feel hollow. Over time, that hollowness weakens confidence in leaders, decisions, and the organization itself.
That’s why intention matters. Trust survives when companies draw a clear line between transactional AI – billing updates, password resets, scheduling notices – and relational AI – strategy announcements, recurring team updates, inter-departmental communication, or client relationship-building exchanges. The first can be automated without risk; the second requires a human voice. Without this boundary, organizations risk automating the very moments when trust is built, and with it, the foundation that makes AI adoption sustainable.
So what does this responsibility actually look like in practice? Whether or not a company adopts the title “Chief Trust Officer,” the function itself is unavoidable. Someone has to own the task of making AI understandable, explainable, and credible across the organization.
That responsibility goes beyond ethics checklists or compliance reports. It means translating AI decisions into plain language for every audience it touches – boards that need to assess risk, employees asked to adopt new tools, customers interacting with automated systems, and regulators demanding clarity. Without this translation, AI becomes a black box. With it, people understand not just what decisions were made, but why.
Without that bridge, communication degrades. AI outputs become efficient but impersonal, and people begin to doubt the authenticity of those outputs. The trust function ensures that relational moments – like a strategy announcement or customer support exchange – retain the presence, empathy, and credibility that only humans can provide. When tools are built to preserve human presence, they deepen connection.
For many companies, trust is treated as an abstract value – something mentioned in mission statements but rarely measured. That’s no longer enough. In the age of AI, trust has to move from symbolism to practice.
The first step is defining the boundary between transactional and relational AI. Clear policies about where automation is appropriate signal to employees and customers that the company is intentional about its choices. Without that clarity, efficiency risks spilling into moments that depend on human presence and empathy.
The second step is measuring trust directly. This means asking the people who matter most: Do employees trust leadership to use AI responsibly? Do clients trust the company to deliver on its promises? Do customers trust the interactions they’re having? These answers, tracked over time, give leaders the clearest picture of whether their AI strategy is building confidence or eroding it.
In other words, trust can no longer remain vague or assumed. It has to be defined, tested, and measured with the same rigor as any other strategic priority. Companies that commit to this discipline through clear boundaries and direct feedback will be far better positioned as AI reshapes the marketplace.
If defining the relational cut line and measuring trust are the first steps, the next is assigning responsibility. Someone inside the organization must bring clarity to these principles and ensure they don’t remain abstract. Whether that person carries the title of Chief Trust Officer, Chief AI Officer, or sits within HR or Communications is less important than the fact that the role is explicitly recognized. Without ownership, trust risks slipping through the cracks as everyone’s responsibility and no one’s job.
But ownership can’t stop at one office. Trust has to permeate the day-to-day choices across the business: how teams adopt new tools, how leaders communicate strategy, how clients are supported, how employees feel their voices are heard. A designated leader can set the frame, but the organization as a whole must embody it. Put simply, trust may start with a single accountable role – but it only succeeds when it becomes a shared operating principle.
AI will keep advancing faster than most companies can regulate or even fully understand. That pace makes trust less of a “soft value” and more of a strategic capability – something leaders have to design for, measure, and protect. The question isn’t only who carries the title, but how deeply the trust function is embedded into daily operations.
The companies that succeed won’t be those that chase every new tool, but those that set clear boundaries, explain choices in plain language, and preserve human presence where it matters most. That’s what turns AI adoption from a source of doubt into a source of confidence. In that sense, trust is the foundation that makes it usable. Companies that treat it this way will find themselves not simply keeping pace with technology, but leading with it.
Robotics and Automation: A Real-World Look at What’s Next in Manufacturing
Victor Cho is the CEO of Emovid, where he explores how AI can support more authentic, emotionally intelligent communication. With a background in product innovation and digital leadership, he’s focused on building tools that help people connect more effectively—without losing the human touch.
In the AI Race, Strategy Outpaces Speed
Who Is Paying for AI? The Monetization Problem No One Talks About
Why Companies Remain Cautious of AI — And How to Deploy It Securely
Executive Perspective: Building Cyber-Resilient Operations in Emerging and New Markets
From Scattered ChatGPT Chats to a Living AI Operating System: How To Build an AI-First Company
How AI Is Transforming Enterprise Communications
Advertiser Disclosure: Unite.AI is committed to rigorous editorial standards to provide our readers with accurate information and news. We may receive compensation when you click on links to products we reviewed.
Copyright © 2025 Unite.AI

source
This is a newsfeed from leading technology publications. No additional editorial review has been performed before posting.