TLDR: A recent study by SAS and IDC, ‘The Trust Imperative,’ indicates a significant global surge in trust for generative AI, with nearly half of respondents expressing complete confidence. This rise occurs despite a critical lag in implementing robust AI safeguards, governance, and ethical practices, which paradoxically leads to higher trust in less established AI forms over traditional, more explainable ones. Organizations prioritizing trustworthy AI are significantly more likely to see higher returns on their AI investments.
CARY, N.C. – September 30, 2025 – A groundbreaking global study, ‘IDC Data and AI Impact Report: The Trust Imperative,’ commissioned by SAS, a global leader in data and AI, and conducted by IDC, has unveiled a striking paradox: trust in generative AI (GenAI) is rapidly escalating worldwide, even as the implementation of essential AI safeguards and governance lags significantly. The research, which surveyed 2,375 IT and business leaders across North America, Latin America, Europe, the Middle East, Africa, and Asia-Pacific, highlights a growing confidence in emerging AI technologies, particularly GenAI, over more established forms.
The study reveals that IT and business leaders now report greater trust in generative AI than any other form of artificial intelligence. Nearly half of all respondents (48%) expressed ‘complete trust’ in GenAI, with agentic AI also garnering substantial confidence at 33%. In stark contrast, traditional AI, such as machine learning, was the least trusted, with less than one in five (18%) indicating complete trust. This phenomenon is particularly pronounced among organizations with minimal investment in trustworthy AI systems, where GenAI (e.g., ChatGPT) was perceived as 200% more trustworthy than traditional AI, despite the latter’s established reliability and explainability.
Kathy Lange, Research Director of the AI and Automation Practice at IDC, commented on this contradiction: “Our research shows a contradiction: that forms of AI with humanlike interactivity and social familiarity seem to encourage the greatest trust, regardless of actual reliability or accuracy.” Lange further questioned, “As AI providers, professionals and personal users, we must ask: GenAI is trusted, but is it always trustworthy? And are leaders applying the necessary guardrails and AI governance practices to this emerging technology?”
Despite the surging trust, significant concerns persist among respondents, including data privacy (62%), transparency and explainability (57%), and ethical use (56%). The report underscores a critical gap: while a substantial 78% of organizations claim ‘complete trust’ in AI, only 40% are actively investing in governance, explainability, and ethical safeguards to ensure their AI systems are truly trustworthy. Furthermore, the prioritization of trustworthy AI measures remains low, with only 2% of respondents listing ‘formulating an AI governance framework’ among their top three organizational priorities, and fewer than 10% developing ‘responsible AI policies.’
The study also highlights the tangible benefits of prioritizing responsible AI. Organizations that are ‘Trustworthy AI Leaders’—those investing most in practices, technology, and governance frameworks—are 1.6 times more likely to achieve double or more the return on investment (ROI) from their AI projects compared to ‘followers.’ This suggests that neglecting trustworthy AI measures could significantly hinder an organization’s ability to fully realize the potential of its AI investments.
Also Read:
- Generative AI Sees Widespread Adoption, Yet Ethical Gaps and Nuanced Public Trust Remain Key Challenges
- Enterprise Leaders Prioritize Trust and Governance for Scalable Agentic AI Deployment
Key obstacles to AI adoption and trustworthiness identified in the report include weak data infrastructure (49%), inadequate governance processes (44%), and a shortage of AI skills (41%). The findings emphasize the urgent need for organizations to align their trust in AI with concrete investments in robust safeguards and governance frameworks to unlock AI’s full potential responsibly.
