The rise of agentic artificial intelligence (AI) is reshaping consumer–firm interactions, yet adoption critically depends on consumer trust. This paper develops a conceptual framework linking transparency and perceived autonomy/control to trust formation and subsequent behavioral outcomes in agentic AI. Drawing on a systematic literature review guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, thirty studies were synthesized from databases including Scopus, Web of Science, IEEE Xplore, ACM Digital Library, and ScienceDirect. The review identifies transparency process, outcome, data, and value dimensions, and perceived autonomy/control through authorization, scope-definition, and intervening to be prominent antecedents of cognitive and affective trust. These channels of trust, in turn, drive consumer willingness to delegate, purchase intent, and positive word-of-mouth. Moderators such as domain risk, anthropomorphism, and cultural contextualization further specify these relations. The study contributes theoretically in distinguishing channels of cognitive and affective trust, bridging transparency and autonomy as dual antecedents, and introducing cultural moderators widely ignored in Western-centric research. Practically, it offers an organizational trust-by-design primer for businesses implementing agentic AI, highlighting calibrated control, user-centric transparency, and compatibility with cultural and regulative expectations such as Oman 2040 Vision. The results reemphasize that trust must be actively maintained and recalibrated rather than taken for granted as invariable. By keeping trust at design and strategy’s centre, businesses can increase customer trust, accelerate adoption, and derive sustainable value from agentic AI technologies.