Why Customer Trust in AI Agents is Still Conditional

Customer sentiment toward AI agents is warming, with 49% of users reporting positive experiences—a nine-point increase from 2025, according to Intercom’s 2026 AI Sentiment Report. However, the report highlights that this trust is passive and conditional, often relying on exposure rather than a genuine belief in the technology’s ability to handle complex, nuanced, or emotionally charged situations.

What happened

Intercom’s research, which surveyed over 1,000 end users, found that trust spikes significantly when users see an agent in action; positive sentiment jumped from 49% to 74% after respondents watched a video of an AI agent successfully resolving a query. Despite this, 54% of users remain skeptical of AI’s ability to handle complex issues. The primary barriers to trust are not accuracy concerns, but rather fears regarding accountability, the lack of human judgment, and the perception that AI operates in a silo. Users specifically worry that agents will adhere rigidly to policy rather than exercising the flexibility required for exceptions. Furthermore, when AI is used for tasks like shopping, users express concern that the agent’s allegiance lies with the company’s bottom line rather than their own needs.

Why it matters for customer support teams

For small business owners and support leads, this data serves as a critical reminder: automation should not be a "set it and forget it" strategy. Your customers are not just looking for a fast answer; they are looking for a safety net. The report makes it clear that users feel more comfortable when they know they are talking to an AI and when they have a clear, easy path to escalate to a human. If you deploy AI agents without a visible human-in-the-loop component, you risk creating a "silo" perception that alienates your customers. To build lasting trust, you must move beyond passive acceptance and actively design your support flows to demonstrate that your AI is an extension of your human team, not a replacement for it.

What to do this week

1. Audit your AI chat interface to ensure it explicitly discloses that the user is interacting with an AI agent, as transparency is a top driver of user comfort.
2. Review your escalation protocols to ensure that a "human handoff" button is prominent and functional in every automated conversation flow.
3. Identify three common "complex" customer scenarios where your AI currently struggles and draft a clear policy for when these should be automatically routed to a human agent instead of being handled by the bot.

Sources

• Announcing the 2026 AI Sentiment Report: How end users feel about AI Agents — Intercom Blog