Promoters of Artificial Intelligence (AI) innovations, such as OpenAI, DeepMind, and AlphaGo, often present ambitious promises of singular solutions capable of overcoming human knowledge limitations (Gehani, 2002). However, critics caution against over-reliance on unproven technologies, citing failures and shortcomings of Conventional AI systems, such as hallucinations and inaccuracies (Gehani, 2001). These limitations have motivated efforts to innovate advanced AI systems with human-like consciousness. This exploratory research investigates the early introductory stages of both Conventional AI and the nascent attempts to develop Conscious AI within their technology life cycles (Gehani, 1995, 1998). The study critically examines AI innovations through the lens of four models: (1) the limitations of the Turing Thinking Machine model, (2) Gehani’s systems thinking and V8 piston engine value-adding model (1993, 1998), (3) the Open Innovation model (1992), and (4) Searle’s Chinese Room thought experiment. Drawing lessons from these frameworks, the research highlights key characteristics of human consciousness and proposes foundational building block capabilities for advancing Conscious AI technology (Gehani, 2013, 2016). The study concludes with future implications and critical lessons, emphasizing the importance of ethical, human-centric innovation during this pivotal period in AI development.