For decades, the familiar phrase "This call may be monitored or recorded for quality assurance" has served as a catch-all disclosure in contact centers, but in today's artificial intelligence-enabled service environment, that language is no longer just outdated, it's misleading. Customer service leaders who continue to rely on legacy disclosures risk eroding trust, increasing legal exposure, and slowing the adoption of the very AI tools designed to improve the customer experience.
The reality is that artificial intelligence has fundamentally changed how customer interactions are handled. What was once periodic, manual review has now shifted to continuous, automated analysis. AI-driven speech-to-text and analytics tools often evaluate up to 100 percent of interactions in real time, while additional capabilities, from agent assist to chatbots and predictive analytics, extend AI's footprint across the entire customer journey.
Customers are increasingly aware that AI is involved in their service experiences, and they want clarity. According to Gartner research, 56 percent of customers say they want to know when they are interacting with generative AI. At the same time, a striking 92 percent expressed concerns about its use in customer service.
Those concerns are not abstract. Customers cite data security (43 percent), incorrect responses (38 percent) and fraud (32 percent) as their top worries. This signals a widening gap between what organizations are doing with AI and what customers understand about those activities.
When companies fail to transparently communicate AI usage, they risk creating a trust deficit. Customers might hesitate to engage with self-service tools, assume unethical data practices, or question the integrity of the brand. In an environment where loyalty is fragile, this lack of clarity can directly impact both customer satisfaction and operational efficiency.
The Stakes Are Rising
The implications extend beyond customer perception. AI disclosure is quickly becoming a legal and regulatory issue. Gartner predicts customer-initiated AI litigation will increase by more than 300 percent by 2029, driven by concerns such as misinformation, privacy violations, and fraud.
Traditional disclaimers that are rooted in a simpler era of quality monitoring do not adequately reflect the breadth of modern AI activity. Today, customer data might be transcribed, analyzed, reused for model training, or shared with third-party systems. These processes carry different levels of risk and require more precise communication to customers.
In short, transparency is no longer optional. It is a strategic imperative.
So what does effective AI disclosure look like? It starts with abandoning the one-size-fits-all approach and replacing it with a more nuanced, customer-centric model.
1. Move to tiered disclosures.
Not all AI interactions carry the same level of risk. Low-stakes use cases, such as topic detection with a chatbot, can be paired with simple, conversational disclosures. Higher-risk scenarios, particularly those involving sensitive data or transactions, should include explicit opt-in language.
2. Update the language and intent.
Customers don't respond well to vague legal jargon. Instead of focusing on monitoring, organizations should explain how AI is being used and, critically, how it benefits the customer (e.g. faster resolution, improved accuracy, more personalized support).
3. Deliver disclosures in context.
Timing matters. Disclosures should appear at the point when AI is actively being used, not buried at the beginning of an interaction where they might be irrelevant or ignored. This reduces friction while increasing relevance.
4. Ensure consistency across channels.
Customers expect the same level of transparency whether they're engaging via voice, chat, SMS, or social messaging. Inconsistent disclosures can create confusion, or worse, suspicion about hidden practices.
5. Build a transparency hub.
Leading organizations are going beyond in-interaction disclosures by creating dedicated AI transparency pages. These hubs outline which data is collected, how it is used, how it is protected, and which opt-out options exist. This not only builds trust but also strengthens legal defensibility.
Transparency as a Competitive Advantage
Forward-thinking customer service leaders should view AI disclosure not as a compliance burden, but as an opportunity. Transparent practices can differentiate companies in a crowded market, reinforce trust, and encourage greater adoption of AI-driven self-service.
Consider the alternative: Customers who feel uncertain or misled are less likely to engage with automation and more likely to escalate to live agents, which drives up costs and undermines efficiency gains. By contrast, clear and thoughtful disclosures can reassure customers, set expectations, and create a sense of partnership in the service experience.
The phrase "This call may be monitored" belongs to a different era. In today's AI-driven environment, it no longer reflects reality.
Customer service leaders must evolve their approach to match the technologies they deploy. That means embracing transparency, tailoring disclosures to risk, and communicating in a way that puts customers at ease rather than on guard. In the end, the organizations that get this right won't just mitigate risk, they'll build stronger, more trusting relationships with the customers they serve.
Ian Elliott is a director, analyst for the Customer Service and Support team at Gartner.