Models represent reality, and the models we as humans create have traditionally been designed to produce some output. Artificial intelligence (AI) can be viewed as a model of human intelligence’s capabilities, at least in part. In this sense, AI ‘machines’ have been generative since its inception in the 1950s and we should not have been surprised by what we are now seeing in the form of “generative AI” (gen AI) applications, but we are! The reason behind the recent widespread appreciation of the generative aspects of AI applications is due to the ease of availability (all that is needed is a connected browser on any device!) of such AIs to the masses, the increased speeds at which gen AI outputs are being churned out and the impressive usefulness of such rapidly created output. Gen AI has achieved fast-food status on a consumer level and it can be industrialized, commoditized and woven into the socioeconomic fabric of human society. Combined with the power of strategic human enhancive AI architectures such as adaptive cognitive fit (ACF), we can anticipate gen AI to help unleash iterations of rapid and complex advancements with purported benefits which will be treated as hyper-value creation opportunities and hitherto obscure risks (Samuel, et al., 2022). The focus should eventually shift to ACF and similar architectures which will help nurture a society that supports mass-human ascendancy over AIs, as opposed to the converse.