The rapid adoption of generative AI has left brands facing a difficult choice: either disclose every use of the technology or risk appearing opaque when customers learn of it later.
Customers may value openness, but broad labels can also create doubt when AI has only assisted a human-led process rather than determined the final outcome.
As a result, CX leaders should think about moving away from blanket policies that either disclose everything or disclose nothing.
Speaking with CX Today previously, Sarah Stephenson, Social Director at tmp, argued that as AI-generated content floods social feeds, brands must differentiate themselves through a credible human perspective.
“It’s now about how you demonstrate authenticity and expertise through your own personal experiences. Creating something that AI can’t replicate or copy.”
Should Customers Know When Content Is AI-Generated?
AI has become a routine part of how brands create content and engage customers online, however, this raises the question of whether customers should always be told when AI has been involved as concern for the technology continues to grow.
With AI’s limitations now becoming mainstream public knowledge, from hallucinations appearing in court reports, to dangerous first-hand experiences with the technology, organizations must decide where transparency genuinely benefits customers and where blanket labeling could add confusion.
The scale of the challenge on social platforms is growing at an alarming rate, as Reddit recently revealed that it blocks around 23 million spam views a day before users see them, detecting roughly 25,000 spam posts and comments daily, and removing nearly 2 million inauthentic votes every day.
Having reduced only 20% of user exposure to spam between January and March 2026, this reveals that despite drastic improvements to moderation, AI-generated material is becoming harder to distinguish from human-created work.
For brands, this creates a difficult balancing act as customers generally care less about the technology itself, than whether they can trust the information they receive, however, trust can erode if customers discover AI was used in a misleading manner.
Alys Reynders, CMO at Quickbase, told CX Today that transparency is becoming more critical than ever.
“At a time when more consumers than ever have become wary of brand opacity in marketing and advertising, the trust implications of omitting AI generated content could lead to severe PR implications for the brands adopting artificial intelligence,” she explained.
“The prospect of backlash could be even more pronounced for the use of AI images or video.”
The debate for whether AI should be disclosed at all stretches beyond to how brands can remain accountable for the experiences they create and preserve customer confidence in an increasingly AI-mediated digital world.
Does AI Disclosure Build Customer Confidence or Create Unnecessary Friction?
While transparency often appears as the obvious solution to customer trust, research from Gartner reveals that many consumers want to know when AI has been used, as 68% frequently wonder whether the content they see online is real.
At the same time, simply adding an “AI-generated” label may not automatically increase confidence, as only 14% of consumers are comfortable with fully autonomous AI.
When brands are unable to understand what customers are concerned about, content deemed less authentic can leave them balancing transparent AI and ensuring disclosure does not undermine customer confidence.
In many cases, people are not objecting to AI itself in human oversight, but to how it is used imitate people or create experiences that customers believe are entirely human driven.
As a result, blanket disclosure policies may not always be the most effective approach, requiring brands to explain where AI has supported a process and where human judgment remains responsible.
Alice Warren, Fractional Director of Community Management and Social Listening at Quimby Digital, spoke with CX Today about how brands should be more careful when assuming disclosure alone strengthens trust.
“I think that labeling will directly erode trust,” she argued.
“The trust factor relates more to deceptive use of AI, not responsible AI practices.”
For CX leaders, the next priority is ensuring customers are never misled about who created content or who they are interacting with.
Does AI Labeling Protect Human Connection?
Beyond transparency, deciding whether to disclose AI affects authenticity as organizations must now ensure they do not lose empathy and genuine human understanding.
Whilst AI has enabled brands to respond to customers quickly with personalized experiences, it cannot always recognize the contextual complexity that defines CX.
According to Genesys’ 2026 State of CX report, 95% of consumers expect organizations to remember their information across channels, while 92% expect experiences to be as good as the best interaction they have had with any company.
As customers become more comfortable with AI as part of the service experience, their expectations for seamless access to human support when needed continue to grow.
Holly Enneking, VP of Marketing at Markup AI, explained to CX Today that this distinction is fundamental to maintaining authentic customer relationships.
“AI can help brands respond faster, personalize interactions and remove friction, but it can’t decide when a customer needs a person instead of a process,” she explains.
“Brands can preserve a sense of authenticity by using AI to support their teams, not impersonate them.”
When brands are clear when customers are interacting with automation and ensuring human agents remain available for complex decision-making, they can enable AI to enhance CX without diminishing the authenticity of the relationship.
For CX leaders, AI can also free employees from administrative tasks rather than attempting to replace them from the customer journey altogether.
How Much AI Disclosure Is Enough?
Whilst some level of AI transparency is necessary, where should brands draw the line?
AI’s involvement in the content creation stage is almost at 100%, functioning as a productivity tool instead of replacing the creator.
In fact, inputting disclosures for every low-risk AI-assisted workflow could overwhelm customers with information that provides little value.
When customers are unable to distinguish between low-risk uses of AI and situations where disclosure genuinely matters, transparency can lose its value and make it harder for users to identify interactions with effective impact.
When AI creates or substantially alters something that customers could reasonably believe is genuine, these incidences are highly critical for user awareness.
According to Gartner, 68% of consumers frequently question whether the content they encounter online is real, highlighting that clear disclosure helps customers make informed decisions while protecting brands from accusations of deception.
Richa Taldar, Staff Product Manager at Walmart, told CX Today that this distinction should form the basis of every AI disclosure policy.
“I would draw the line based on whether AI changes what the customer believes is real or what they think they’re buying,” she explained.
“If AI creates a fictional person, testimonial, product result, or event that could reasonably be mistaken for something real, the brand should disclose it.”
For CX leaders, this distinction shifts disclosure from a blanket compliance exercise to a practical framework centered on customer expectations.
“Using AI to improve how marketing is created is very different from using it to change what customers believe they will receive,” she added.
Brands should provide situation-specific disclosures whenever AI influences the customer journey, offering greater transparency without overwhelming customers with unnecessary information.
Finding the Balance Between Innovation and Transparency
The continuous debate surrounding AI disclosure requires CX leaders to develop a framework that balances transparency with practicality.
Instead of panicking over whether AI was involved at any point in a process, organizations should consider whether its use changes how customers might interpret information, make decisions, or take away from that brand.
By placing accountability at the center of responsible AI adoption, customers are more likely to accept AI supporting the behind the scenes, as Gartner’s 2026 Marketing Survey found that 61% of consumers frequently question whether the information they use to make everyday decisions is reliable.
When CX leaders understand that trust depends on whether brands can demonstrate AI transparency, accuracy, and responsible governance rather than the technology’s mere existence, they can develop disclosure policies that prioritize meaningful customer outcomes over blanket compliance.
Speaking with CX Today, Jeanne Duca, CMO at BCN, believes this distinction should shape how organizations approach disclosure.
“The real issue isn’t whether AI was involved, it’s whether the brand remains responsible for the outcome,” she explained.
“Disclosure policies should focus on customer impact rather than simply the presence of AI somewhere in the workflow.”
This allows brands to avoid overwhelming audiences with labels that provide little practical value.
Ultimately, responsible adoption depends on more than just AI disclosure, as human ownership, fact-checking, responsible data governance, and clear pathways to human support remain essential for maintaining customer confidence as capabilities evolve.
“AI should enhance relationships by making interactions more personalized, responsive, and valuable, not more automated for automation’s sake,” she concluded.
