Transparency With AI and Humans: The Trust Gap Brands Cannot Ignore

AI has officially moved from the background to the front lines of customer service. In the 2025 holiday season, nearly 8 in 10 shoppers (78%) interacted with AI or automation at some point in their journey, and 73% said they used it more than the year before. That alone is a watershed moment. But the bigger shift is not adoption. It’s expectation. 

Consumers are no longer asking, “Are you using AI?” They are asking, “Can I trust how you are using it?” 

The latest findings from the Liveops 2025 Holiday AI & Customer Service Report, which included a survey of 1,000 U.S. adults, point to a hard truth: speed is rising, but confidence is not. AI did what it promised in one dimension, with 85% of respondents saying it sped up service and made it more accessible. Yet only 29% said AI improved their holiday experience, and 14% said it made things worse. The gap between efficiency and trust is where loyalty is won or lost. 

Transparency is the bridge. And right now, most brands are not building it. 

Read the full 2025 holiday AI & customer service report

Transparency is not a feature, it’s the experience 

Consumers are surprisingly consistent about what they want: clarity. Only 22% of respondents said companies always disclosed when AI was being used. At the same time, 69% said brands should always reveal it. 

That spread matters because it signals something deeper than a preference. It signals a trust contract that has not been written clearly enough. 

When customers cannot tell whether they are interacting with a person or automation, they fill in the blanks themselves. Some assume they are being routed away from real help. Others feel tricked, even when the system is well-intentioned. And once doubt enters the interaction, everything that follows is judged more harshly, including response time, policy explanations, and resolution outcomes. 

Transparency is not just saying “This is a bot.” It’s designing an interaction that feels honest from the first second to the last, including what happens when automation cannot solve the issue. 

The escalation problem is a transparency problem 

One of the most telling data points in the report is not about sentiment. It’s about behavior. 

More than half of shoppers (55%) said they had to escalate an AI-handled issue to a human. Nearly half (45%) said the technology did not understand their problem. And 54% said humans delivered better service than AI. 

This is where transparency stops being philosophical and becomes operational. 

If a customer starts with automation and ends with a person, the handoff cannot feel like a trap door. Customers should never have to fight their way out of a loop, repeat themselves, or guess what to type to reach a human. When that happens, customers do not blame the workflow. They blame the brand. 

A transparent experience makes escalation feel normal and intentional. It says, “We are moving you to the right support, not moving you around.” 

Different generations define transparency differently 

The report also highlights a reality brands have to plan for, not debate: comfort with AI is not evenly distributed. 

Gen Z adoption was extremely high, with 89% using AI during holiday shopping, compared to 60% of Boomers. But even for digital native shoppers, transparency still matters. Faster does not mean better if it’s unclear, repetitive, or dismissive. 

For older shoppers, the trust bar is often higher. They may be more sensitive to disclosure cues, more likely to want a human option upfront, and less willing to tolerate conversational friction. 

The takeaway is not “build one path for Gen Z and one path for Boomers.” It’s “build one truth for everyone.” Make disclosure clear, make the opt out obvious, and make the handoff smooth. 

A practical transparency framework brands can implement now 

Transparency can feel abstract until you break it into design decisions. Here is a simple framework that turns “we should be transparent” into specific actions. 

1. Discloseearly and clearly
   Don’t bury it. Make it explicit at the start of the interaction, in plain language, with a tone that fits your brand. Skip the legalese phrasing and keep it human. Customers do not need a policy statement. They need clarity. 
2. Explain what automation can do
   Set expectations in one sentence. For example: “I can help with order status, returns, and simple changes.” This reduces frustration and improves resolution rates because customers stop asking the system to do what it cannot.
3. Provide an easy route to a person
   Not as a last resort, as a designedoption. Some issues require judgment and empathy, especially during high-emotion moments like missing packages, damaged gifts, billing errors, or delivery failures. 
4. Make handoffs seamless
   If the interaction moves from automation to a person, carry context forward. Repetition is one of the fastest ways to destroy trust.
5. Measure trust, not just containment
   If you only track deflection, you willoptimize for the wrong thing. Track escalation satisfaction, repeat contact rate, complaint language around “stuck,” and the percentage of customers who choose human support when offered. 

Transparency is how you avoid the “more AI” backlash 

One of the most cautionary findings in the report is the direction consumers want next. Only 17% want companies to increase AI usage next year, while 32% want less. 

That does not mean consumers are anti-AI. It means they are tired of bad experiences that feel like automation for automation’s sake. 

Transparency is the difference between “AI is helping me” and “AI is blocking me.” It’s also the difference between a customer who accepts automation in routine moments and a customer who decides your brand is not worth the effort. 

Where Liveops fits in 

The most effective service models are not “AI only” or “humans only.” They are designed systems where automation clears the path, and people carry the relationship, especially when nuance and empathy matter. 

That is where Liveops helps brands turn transparency into real operations. From designing clear disclosure and smoother handoffs to aligning automation with the moments it can truly handle, Liveops supports a service approach that protects trust while still delivering speed and scale. 

Because the next era of customer service will not be defined by how much AI you deploy. It will be defined by how honestly you deploy it and how confidently customers feel along the way.