For many organizations, AI governance still sounds like someone else’s job. 

IT evaluates the technology. Legal considers compliance. Privacy looks at data. Information security manages risk. HR addresses employee use. 

Communications may be consulted when something needs to be announced. 

But AI is moving too deeply into how organizations communicate, make decisions and interact with people for that division of responsibility to hold. 

Because there is another question AI governance must answer: What happens to trust? 

And that question belongs squarely in the communications conversation. 

Who owns AI governance today? 

There is no simple answer. 

Research from the International Association of Privacy Professionals (IAPP) and Credo AI found primary responsibility distributed across several functions: 

• Privacy: 22% 

• Legal and compliance: 22% 

• IT: 17% 

• Data governance: 10% 

• Ethics and compliance: 6% 

• Security: 5% 

The research also found there is no clear best practice for where AI governance should sit. Mature programs increasingly draw on specialists from multiple departments. 

That fragmentation is understandable. 

AI governance is inherently cross-functional. No communications leader should be expected to determine cybersecurity controls, interpret every regulatory requirement or architect enterprise technology. 

But there is a problem if communications stays outside the room. 

Reputation does not respect the org chart. 

Consider what can happen when AI becomes part of everyday work. 

• An employee can enter sensitive information into an AI platform, rely on an inaccurate output or publish AI-assisted content without sufficient review. 

• An AI system can give a customer incorrect information, use data in a way they did not expect or communicate without appropriate disclosure. 

• An AI-enabled experience can make an employee feel surveilled or act beyond the authority a customer thought they granted it. 

Whether the problem begins with the technology, the way an employee uses it or the workflow surrounding it, the resulting trust issue will not remain contained inside IT, legal or compliance. 

It becomes an organizational relationship problem. 

And eventually, a communications problem. 

Organizations are lending AI their reputations 

New research provides an especially useful signal. 

An Experian-commissioned study conducted by Forrester Consulting surveyed 6,247 credit-active, digitally literate consumers across 13 markets in Europe, the Middle East, Africa and Asia Pacific. 

Three-quarters said they would feel more comfortable using AI connected to a financial institution they already trust. 

Think about what that means. 

People are not necessarily evaluating AI as an independent entity. They may be transferring some of the trust they already have in an organization to the AI experience that organization provides. 

Company trust can become AI trust. 

That is an enormous opportunity for organizations introducing AI into customer relationships. 

It is also an enormous responsibility. Because trust can travel in the opposite direction too. 

When an organization puts its name behind an AI agent, chatbot, automated recommendation or AI-assisted communication, that technology becomes another expression of the organization. 

Its behavior contributes to the relationship. 

Its mistakes can affect credibility. 

Its choices around data, disclosure and human oversight communicate something about what the organization values. 

The technology may be new. The reputation at stake is not. 

Communications cannot outsource the trust questions 

Many governance questions appropriately belong to other functions. 

• Security should determine whether systems are secure. 

• Legal should assess legal exposure. 

• Privacy should establish appropriate data protections. 

• Technology teams should understand system architecture and access. 

But communications leaders bring another set of questions to the table: 

• When should AI assistance be disclosed? 

• How will customers understand when they are interacting with AI? 

• What expectations are we creating with employees, clients and partners? 

• Where could an AI-enabled experience feel inconsistent with our values? 

• When does technically permissible use cross a line our stakeholders may consider unacceptable? 

• How should we communicate when AI makes a mistake? 

• What human decisions should remain visible in high-trust interactions? 

These are not simply technical questions. They are questions about relationships, expectations and credibility. 

Communications leaders have expertise that AI governance needs. 

Yet communicators are not consistently leading the conversation 

There is another reason this matters. 

Research supported by the Arthur W. Page Center for Integrity in Public Communication found that AI is already embedded in PR work, but PR leaders are not always leading the discussion around it. Agency leaders were only marginally more active than clients in AI conversations, raising questions about who is setting the strategic agenda as AI becomes part of communications work. 

Meanwhile, the LexisNexis 2026 AI in PR & Communications report found that: 

• 55% of PR professionals surveyed were already using AI for content 

• PR and media professionals reported especially high concern about misinformation 

• Nearly 60% reported using generative AI tools without approval 

That combination should get our attention. 

The profession responsible for protecting credibility cannot afford to view AI governance only as something created elsewhere in the organization and handed down as policy. Communications leaders need to help shape it. 

Not because communicators should own every control. But because we understand something essential to governance that technology alone cannot answer: 

Trust is built in the experience people have with an organization. 

AI governance is expanding beyond data risk 

Organizations appear to understand at least part of the governance challenge. 

Recent analysis from S&P Global found that among companies with AI policies: 

• 91% address data privacy 

• 74% address potential bias 

• 69% address cybersecurity 

• Only 40% enforce identification of AI-generated content 

S&P Global identified the last area as a clear governance gap and specifically warned that insufficient guardrails around AI-generated content could create reputational risk or lower trust in a company’s products and services. 

That gap is revealing. 

Organizations have become increasingly aware that AI creates data risk. 

Yet, we have more work to do in recognizing that AI also creates communications, relationship and reputation risks. 

Those risks will become more important as AI moves beyond assisting employees behind the scenes and begins interacting directly with customers, employees, donors, clients and other stakeholders. 

Communications needs a seat at the governance table 

The answer is not to move AI governance into the communications department.  

It is to design governance collaboratively. Legal, privacy, security, technology, HR, operations and business leaders all bring essential perspectives. 

Communications should too. 

For communications leaders, that may mean helping establish: 

• Standards for AI-assisted content and disclosure 

• Expectations for customer-facing AI 

• Employee communication and transparency 

• Human review and decision-making expectations 

• Crisis and incident-response protocols 

• Guidelines for AI use in high-trust stakeholder interactions 

It also means asking questions before something goes wrong rather than preparing messages afterward. 

At Human Driven AI, we believe effective governance should follow the work. It should help people understand not simply what AI tools are permitted, but how AI fits into real workflows, decisions, information sharing and relationships. 

Because policies alone do not create trust. People experience governance through the choices an organization makes. 

And as AI increasingly becomes part of that experience, communications leaders have both an opportunity and a responsibility to help shape those choices. 

We do not need to own every part of AI governance. 

But if we are responsible for organizational trust and reputation, we can no longer treat AI governance as somebody else’s job. 

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Human Driven AI helps organizations move from scattered AI experimentation to shared, scalable practice. We build the governance foundations, redesign workflows around human and AI strengths, and deliver custom training programs that teach your teams how to put those systems into practice.

Whether you need an executive Lunch-and-Learn, a hands-on offsite workshop, an enterprise AI transformation program or a strategy to strengthen your brand’s visibility through GEO, we help you turn AI capability into better ways of working.

Ready to move from using AI to working differently with it? Let’s talk.

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