The pharmaceutical industry faces significant challenges, including prolonged drug development cycles (10-15 years), escalating costs (exceeding $1 billion per drug), and mounting pressures to align innovation with sustainability and transparency. This study investigates the transformative role of artificial intelligence (AI) in addressing these challenges, with a focus on value co-creation and environmental, social, and governance (ESG) integration (Prahalad and Ramaswamy, 2000, 2004; Vargo and Lusch, 2004). By analyzing sustainability reports and strategic documents from Johnson & Johnson (J&J) and NVIDIA through qualitative content analysis, this research identifies four thematic topics: AI in Sustainability Report, Value Co-Creation, AI and ESG and Transparency and Reporting. The study aims to find answers starting from how AI is represented in J&J and NVIDIA’s reports, which initiatives are linked to the co-creation of value in drug discovery, development and distribution, to what extent are references to AI in line with ESG criteria, and finally what elements emerge regarding transparency and communication of AI practices.
Findings reveal that AI accelerates drug discovery through machine learning (ML) and deep learning (DL), enabling rapid analysis of genomic, proteomic, and clinical trial data. Applications such as virtual screening and predictive modelling reduce trial failures and optimize resource allocation, aligning with ESG goals like waste reduction and energy efficiency. The strategic collaboration between J&J and NVIDIA exemplifies value co-creation, merging pharmaceutical expertise with advanced computing to enhance R&D efficiency and patient-centric outcomes. For instance, NVIDIA’s high-performance computing (HPC) infrastructure supports J&J’s drug pipeline, reducing time-to-market while fostering sustainable practices.
The analysis highlights AI’s dual role as a driver of operational innovation and a catalyst for stakeholder-driven sustainability. Transparency in AI reporting emerges as a critical factor, with both companies emphasizing ethical AI deployment and open communication. However, disparities exist in how AI’s societal and environmental impacts are framed, underscoring the need for standardized ESG-aligned reporting frameworks. By bridging value co-creation theory (Prahalad & Ramaswamy, 2004) with empirical insights, this study demonstrates how cross-sector partnerships and AI integration can reconcile economic objectives with global sustainability imperatives. The research contributes practical insights for policymakers and industry leaders, advocating for collaborative, transparent AI adoption to advance both innovation and accountability in the pharmaceutical sector.