Due to its potential to elevate buildings as a system to a level where they turn into cognitive (self-reliant autonomous decision-making and acting) entities, the adoption of Digital Twins (DT) has been significantly increased. Therefore, maturity models have become essential for evaluating and enhancing the advancement in DT to assess the adoption of technology across various industries. The paper proposes a maturity model approach from an Artificial Intelligence (AI) perspective to gain insights into the adoption and implementation of DT in the AEC-FM industry, which distinguishes it from the existing maturity models. Additionally, making a comparison between the interpretation of the term 'cognition' in computer science and its understanding within the AEC-FM industry, presenting pre-classified levels of cognition in literature. In this regard, a literature review is conducted to figure-out the gaps in previous DT maturity model studies. The proposed perspective could cover the missing AI perspective in designing maturity models and provide insights into leveraging the semantics of the term ‘cognitive’ in the AEC-FM industry. Future research directions could further explore various dimensions of DT maturity models and cognition levels within the AEC-FM industry, considering practical challenges and potential applications of DT implementations in-depth.