Antecedents for the adoption of Big data and AI in Chemical Industry

Dr. Ashiff Khan, a Senior Process Engineer at Aramco, with over 20 years of experience in the chemical industry. With multiple U.S. patents in chemical engineering and big data/AI, six post-graduate degrees, and a PhD in big data/AI, he’s a true luminary in his field. Recently, he shared invaluable insights at the Oil & Gas Digital Transformation Conference 2023. In this blog, we’ll dive into his strategies for driving the adoption of big data and AI in the chemical industry.

Dr. Ashiff Khan, a seasoned expert in the field, has highlighted the significant changes occurring in the chemical industry due to technology. In his presentation, he discussed the findings of a study that used surveys and mathematical methods to understand how technology, such as Big Data and Artificial Intelligence (AI), can benefit the chemical industry. The study revealed that having access to a lot of data, closely monitoring processes, and making smart investments in the right tools are crucial. This indicates that technology has the potential to greatly assist the chemical industry, even though it’s just the beginning of its journey. Dr. Khan’s insights also indicate that the industry is at the early stages of embracing these advanced technologies. The ultimate aim is to guide the industry away from traditional practices towards data-driven decision-making, which can foster more innovation and success.

This presentation follows results of a survey-based quantitative method using structural equation modelling. The data collected was studied to draw scientific conclusions about the myriad of hypothesised relationships. This was accomplished by employing a positivist paradigm in the process
This study recognises the strong relationship between data scalability, process monitoring, and the investment in tools for big data/AI adoption as a contribution towards industry application and practice. Mediation effects between the constructs and final measures, and the significance of their relationships was established
This finding of this presentation contributes to the application of the Unified Theory of Acceptance and Use of Technology in chemical industry to be limited in early stages of technology adoption. Based on the literature survey and outcomes, it positions the chemical industry in early stages of big data maturity
This presentation conclusions and contributions towards practical application are expected to enable a shift from conventional methods towards a data-driven approach to decision-making in the chemical industry

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