Key Takeaways:
- Transparency in AI outputs is critical, with 58% of companies stalling AI projects due to trust deficits.
- Trust in AI can enhance revenue, with security and explainability being top assurances for adoption.
Research from Gong reveals an artificial intelligence (AI) trust barrier that stands between companies innovating with AI and those stuck in exploration and confusion.
The study showed that 58% of companies (including 62% in the U.S.) have stalled AI projects that is a result not for a lack of budget, but a deficit in trust
A survey of over 2,000 U.S. and UK leaders reveals that transparency in how AI generates outputs is essential for them to trust, invest in, and deploy AI tools. As it stands, 80% of U.S. leaders feel their organizations are falling behind when it comes to realizing AI’s most powerful benefits, giving solution providers an opportunity to allay concerns and drive their success.
Why AI Trust Can Enhance Revenue
To that end, Gong Labs data that is based on aggregated and de-identified signals derived from over 25 million sales interactions processed within its platform, found that one in four calls referenced security, with uncertainty over AI’s foundational data and learning mechanisms the most discussed topics.
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“Security and AI trust are no longer back-office conversations; they are revenue conversations,” said Chris Peake, Chief Trust Officer, Gong, in a statement. “Gong’s research found that trust can be a performance multiplier when applied as part of an AI strategy. By embedding enterprise-grade governance directly into the Revenue AI OS, we’re helping the world’s most successful teams bypass the doubt and move straight to acceleration.”
Trust Preventing Adoption of Unproven AI Tools
The survey uncovered several barriers preventing companies from adopting AI solutions from providers that had failed to allay their concerns. With more than half of companies having delayed or cancelled their plans to adopt an AI tool, the data suggests that organizations are under-utilizing powerful AI capabilities and leading these companies to miss out on transformational gains.
What’s more, this same lingering uncertainty had meant 44% planned AI investments had been paused. The top assurances U.S. leaders said would help them confidently adopt AI solutions were:
- Security guarantees built into solutions (25%)
- Assurance (24%)
- Explainability, or the ability to articulate AI-derived outputs (24%)
- Ability to articulate AI model guardrails protecting data (24%)
- Third-party audits or certification (23%)
- Transparency into how training data is used (22%)
- Transparent model logic (22%)
Lesson To Take from Gong Report
Gong officials summarized that with the right guardrails, trust can be an enabler of a successful AI strategy. Gong is working with customers to address the trust gap by building enterprise-grade security and data governance within its revenue AI operating system, producing explainable and relevant insights using its context-aware AI, grounded in patterns observed across aggregated customer usage, and providing built-in governance and insight.
“The competitive advantage delivered by AI is no longer up for debate, but the trust barrier remains for those using tools that have yet to establish this trust,” said Peake.
