Survey Results Highlight Mixed Sentiment Toward AI in Sales Teams

According to a recent LinkedIn post from 1up, the company highlights survey findings from hundreds of sales professionals on their attitudes toward artificial intelligence in sales workflows. The post suggests that while AI adoption is widespread, trust and usability remain key friction points for frontline teams.

The company’s LinkedIn post indicates that 76% of sales teams reportedly use five or more AI tools regularly, pointing to what the post characterizes as “tool bloat.” It also notes that 58% of respondents are occasionally or often disappointed by AI tools, citing hallucinations and confusing user experiences as primary issues.

As shared in the post, only 2% of surveyed professionals say they fully trust AI outputs, with most teams described as being in “trust but verify” mode. In addition, just 7% reportedly view AI sales reps as the future, while 48% see AI as mainly suitable for repetitive tasks rather than core sales activities.

The post further reports that 32% of respondents have grown more skeptical of AI over the past five years, despite increased usage. For investors, these findings may signal persistent barriers to deeper AI penetration in sales, including trust, reliability, and integration complexity, which could slow the monetization pace for AI-driven sales tools.

From an industry perspective, the survey data suggests demand may shift toward platforms that consolidate functionality and reduce tool fragmentation. Vendors that can demonstrably reduce hallucinations, simplify interfaces, and embed human oversight may gain competitive advantage, while those offering narrow point solutions could face heightened churn or pricing pressure.

For 1up, positioning around presales and AI-enabled workflows could benefit from this environment if its offerings address the pain points surfaced in the survey. However, the mixed sentiment toward AI and low trust levels underscore execution risk across the broader AI sales enablement space, potentially influencing adoption curves, customer lifetime value, and the timing of revenue realization.