Every story tagged Trust AND Security, curated for CIOs and IT leaders — ranked by source credibility, engagement, and freshness.
3 stories · open in the command center
Developer trust in tools is built through familiarity, predictability, and alignment with established workflows—a critical concern as AI coding agents become prevalent despite 84% adoption but only 29% trust levels. Organizations must recognize that new tools like agentic AI don't simply improve productivity; they fundamentally change development processes and require corresponding shifts in culture, governance, and validation practices that existing toolchains (CI/CD, testing, linting) may not adequately support. IT leaders should prioritize building organizational processes and cultural acceptance around AI tools rather than assuming tool adoption alone will drive business value, as misaligned processes can actually increase validation time and production risk.
As trust collapses across society—from government institutions to healthcare systems—CIOs have a strategic opportunity to position IT as the most trusted function in the C-suite by providing clarity and decisive action in an uncertain environment. CIOs' unique combination of technical expertise and experience making decisions under uncertainty positions them to serve as trusted advisors who can help organizations navigate AI-related risks, data security challenges, and systemic volatility. To capitalize on this competitive advantage, IT leaders must actively rebrand IT from a cost center to a trust-building partner that delivers both strategic context and measurable business outcomes.
American Express is pioneering an agentic commerce platform (ACE) that enables AI agents to autonomously execute transactions on behalf of users through intent contracts and single-use tokens, establishing accountability and trust controls at the payment layer—a critical gap in emerging AI commerce standards. While Amex's closed-loop issuer-network model provides enhanced security and transaction validation, significant black boxes remain in upstream human verification and authorization mechanisms that could expose organizations to fraud, chargebacks, and regulatory risk at scale. Technology leaders must evaluate how agentic AI systems will integrate with payment infrastructure and establish clear cryptographic proofs of user intent before widespread deployment, as current protocols lack transparent human-to-agent authorization linkages.