Intercom 2026 Report: Why AI Trust Is Conditional and How to Earn It

Intercom has released its 2026 AI Sentiment Report, revealing that while end-user acceptance of AI agents is rising, trust remains strictly conditional. The study of over 1,000 users highlights a critical gap: customers are becoming more comfortable with AI, but they are not automatically trusting it to handle nuanced or high-stakes issues without specific design interventions.

What happened

According to Intercom, 49% of respondents described having positive overall experiences with AI, a nine-point increase from 2025. However, the report notes that this acceptance is often passive, built on mere exposure rather than intentional trust-building. When respondents watched a short video of an AI agent resolving a real query, positive sentiment jumped to 74%, suggesting that seeing the technology work effectively is a powerful trust driver.

Despite this warming sentiment, 54% of users said they would only trust AI to handle simple or routine issues, not complex ones. The report identifies two primary behavioral concerns: accountability and judgment. Users worry that AI agents operate in silos, with no human oversight, and that they lack the flexibility to deviate from rigid policies when a situation requires discretion. Consequently, the top two factors users cited for feeling more comfortable were "easy escalation to a human when needed" and being told upfront that they were interacting with AI.

Trust also varies significantly by channel. Users are most willing to trust AI in chat, the most familiar channel for automated support. Social channels are the least trusted, as users expect direct human interaction there. Phone support is the most polarizing; while frequent AI users may prefer an agent answering the phone, those who rarely use AI find it frustrating. Additionally, as AI expands into shopping, users express concern that agents may prioritize company bottom lines over customer best interests, leading to a perception of bias in product recommendations.

Why it matters for support leaders

For support leaders at small and mid-sized companies, this data is a wake-up call: you cannot rely on users to "warm up" to your AI through repetition alone. The report explicitly states that businesses are currently earning trust "by accident" rather than by design. If your CSAT scores are plateauing or if ticket deflection is high but customer satisfaction is low, the issue is likely not the AI’s accuracy, but its perceived lack of accountability. Users are not afraid the AI will give a wrong answer; they are afraid it will give a rigid, unaccountable answer with no path to a human. Your competitive advantage in 2026 will not come from a smarter model, but from a more transparent workflow. You must stop treating the AI as a black box and start treating it as a junior team member who needs clear guardrails and a visible supervisor.

What to do this week

1. Audit your AI chatbot’s exit path to ensure there is a visible, single-click option to escalate to a human agent, and test it yourself to confirm it works without requiring the user to repeat their issue.
2. Update your AI’s opening message to explicitly state that the user is interacting with an AI assistant and that a human team is available for complex issues, directly addressing the transparency concern highlighted in the report.
3. Review your AI’s response templates for rigid policy language and add a disclaimer or prompt that acknowledges the agent’s limitations, offering to connect the user to a human for exceptions or nuanced cases.

Sources

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