In today's rapidly evolving digital landscape, the integration of artificial intelligence, machine learning, and other cognitive technologies into work environments is enhancing operational efficiency and user experience, leading to the emergence of Cognitive-Enabled Building (CEB). Amidst these advancements, concerns about the impact on workplace equity and individual privacy are increasing, underlining the importance of these factors in Human-Building Interaction. This research aims to develop and validate an instrument for assessing how CEB technologies influence workplace equity and privacy. It seeks to measure the effects of cognitive system on employees’ perceptions of privacy and equitable access to technological resources. To build the scale, qualitative and quantitative analysis are used to create a scale that could capture the breadth of the theoretical concept of occupant interaction with CEB technologies. The process involves semi-structured interviews, and instrument-testing that targets a diverse population to represent the broad spectrum of potential occupants and stakeholders in the design and operation decision-making processes of CEBs. Data analysis methods are outlined, including thematic analysis for the semi-structured interview transcripts to generate items, calculating Cronbach’s Alpha to determine the internal consistency, and Test-retest reliability. By using a robust method, this scale instrument will be a tool to bridge gaps in current knowledge about balancing technological advancement and individual rights in the workplace, potentially influencing guidelines and policies to ensure these technologies are implemented in a manner that respects and promotes workplace equity and privacy.