Trust: The Key to Scaling Agentic AI Across the C-Suite
As Salesforce's latest research reveals, **trust in AI** is the critical factor unlocking revenue growth, competitiveness, and customer success for global businesses. Nearly two-thirds of C-suite executives (65%) say trust drives revenue, 67% link it to competitiveness, and 64% to customer satisfaction[1].
Why Trust Matters: Data as the Foundation
Accurate and secure data tops the list for building AI trust, with 80% of C-suite respondents emphasizing it. Training AI on comprehensive customer and company data boosts worker trust by 53%, and those trusting the data are 10% more likely to see revenue impact[1]. Grounding AI in reliable data fosters adoption and ROI, as noted by Salesforce SVP John Kucera[1].
Path to Profit: Key Stats on AI Trust
- 80% of C-suite cite accurate, secure data as critical for AI trust[1].
- 53% of workers trust AI trained on full data[1].
- Trusted data users 10% more likely to report revenue gains[1].
CIO Trends: Scaling Agentic AI in 2026
AI adoption has surged 282% as CIOs shift to scaling agentic workflows, but trust remains the bottleneck. Top fears include data security, privacy, and lack of trusted data. Only 35% of CIOs collaborate closely with chief data officers, and just 23% are fully confident in AI with built-in governance[2]. CIOs report rising confidence: 75% feel more secure in their roles, 97% know more about AI[2].
Salesforce CIO Daniel Shmitt emphasizes embedding AI into workflows with trust at every step for confident scaling[2]. CIOs focus on customer service, with 65% working more closely with those teams on agentic AI[3].
C-Suite Perspectives on Agentic AI
2025 research across CEOs, CFOs, CIOs, and CHROs shows alignment on AI agents transforming operations, but bottlenecks persist in trustworthy data and governance. CFOs worry most about security/privacy (66%), while CIOs prioritize customer service for AI impact[3]. Sales teams echo this: 62% see trust driving revenue, a third linking it to customer satisfaction[1].
Overcoming Challenges for 2026
Salesforce's Agentforce highlights real-world lessons: inconsistent AI outputs erode trust, demanding a mindset shift to view agents as complex systems requiring strategy, not just pilots[4]. Platforms like Salesforce Data Cloud enable a 360-degree customer view, powering trusted, actionable AI[1].
By prioritizing data quality, governance, and trusted platforms, C-suites can scale agentic AI responsibly, turning ambition into measurable business value.