The purpose of this paper is to explore the preparedness of Public Relations (PR) in dealing with the impact of big data and Artificial Intelligence (AI) on the communications profession in Indonesia. The research objective is to determine an understanding of AI that will have an impact on automating and simplifying PR work, to identify the competency of future PR, and to find out big data and AI can replace what kind of PR jobs. This study employed an online survey methodology with a total of 320 PR practitioners and was completed through semi-structured interviews of 10 respondents, both from State-owned enterprises and private companies. The research concludes that there are PR jobs that have been replaced by the tool development of big data and AI, among others were 45% news clippings, 45% news analyses in the media, 37% media relations, 34% content of social media management, 33% release distribution, and 24% photos and videos. This research proposes new competencies that need to be strengthened, specifically in the areas of the content creator, influencer management, social media management, and data analytics. The topic of big data and AI in the communications profession and public relations practitioners in Indonesia has never been discussed before. This has a substantial impact on the management and technology of communications and gives a broader impact on the preparedness of the industry, academia, and society.

This paper aims to investigate the mechanism linking an individual’s internal processes, work engagement, active learning, and adaptive performance in three of Indonesia’s digital technology-based companies. The research uses a mixed-method approach. The first study used a quantitative research method in which the data is based on a survey of 185 employees and the collected survey data is then analyzed using the Structural Equation Modeling technique. The second study used a qualitative research method where the data is gathered from 17 managers through semi-structured interviews. We found from the quantitative research that work engagement fully mediates the relationship between self-efficacy and a growth mindset toward active learning. Meanwhile, a partial mediating effect of active learning between work engagement and adaptive performance was also discovered. Based on our literature study, previous research has shown inconsistent findings on the relationship between growth mindset and work engagement. Our findings contribute to the existing literature by clarifying the direct relationship between growth mindset and work engagement. Meanwhile, the qualitative findings emphasized that there are two mechanisms underlies individual adaptive performance (i.e., work engagement and active learning). Additionally, the active learning process promotes continuous new knowledge accumulation to produce new innovation inside an organization.

This paper aims to explore core competencies and analyze the digital leveling implementation of Pharma 4.0 in Indonesian Pharmaceutical companies. This study uses a mixed-method Delphi study conducted in the first two rounds. The first and second rounds aimed to determine the core competencies of the Pharmaceutical Industry to face the Pharma 4.0 era. In the first round, FGD was conducted involving 12 participants, and semi-structured interviews were carried out with 10 participants in the second round. Alongside Delphi, this research also employs NVIVO as a tool for content analysis. Furthermore, in the third round, a survey was conducted to determine the leveling of the digital implementation of Pharma 4.0, involving 215 senior management participants representing 34 national pharmaceutical industries. The study revealed eight core competencies needed by human capital in the pharmaceutical industry to face the Pharma 4.0 era: critical thinking, bioinformatics, entrepreneurial thinking, digital skills, intrapreneurial skills, research skills, regulatory compliance, and data ethics. Regarding digital leveling implementation, this study found five main levels: level 1 (simplification), level 2 (automatization), level 3 (integrated system), level 4 (digital transformation), and level 5 (disease prediction). This study also affirms that most of the pharmaceutical industries in Indonesia are at level 2 (mean = 4.2) and level 1 (mean = 4.0). Several pharmaceutical industries are at level 3 (mean = 3.5), and a few others are at level 4 (mean 3.2) and level 5 (mean = 1.4). This study is the first to analyze the leveling of digital implementation in Pharma 4.0. The results showed that core competencies could be used as a benchmark to develop employee skills. This current study provides the essential data for core competency development and digital leveling implementation for the pharmaceutical industry and government in preparing Pharma 4.0.