Enhancing AI Adoption in the R&D Workforce toward Productivity Gains of an Industrial Technology Organization

Abstract

AI’s potential is recognized as an enabler in delivering time to market products faster, supporting market growth and expansion, and protecting the bottom line through improvements in productivity and efficiency; as well as harnessing innovation in order to maintain market leadership. With many industrial technology companies seeing the AI revolution, understanding the many facets of Research and Development (R&D) workforce to achieve accelerated AI adoption is critical, amidst this rapidly evolving technology.

This study employed qualitative research methods, drawing on structured questionnaires, follow up interviews and review of internal documentation identifying issues encountered related to AI adoption and defining R&D organizational factors that affect its results. With a case study approach, data analysis involved four (4) key themes: (1) organizational structure, (2) employee behavior and employee engagement, (3) AI literacy and (4) organizational policies and ethical considerations. It defined a framework for enhanced AI adoption of an R&D system in a technology development organization, by identifying and addressing the gaps in its organizational structure and workforce composition. Focusing on the industrial technology organization reviewed, this study provided a timely and relevant approach to adopt AI in the workplace to positively impact the R&D goals of faster time to market development through productivity improvements. The findings derived in this study led to the four recommendations to enhance AI adoption, including: (1) defining a formal AI organizational structure to drive and coordinate AI projects; (2) creating AI-focused employee engagement programs; (3) investing in AI proficiency role-based trainings and (4) establishing an adaptive AI governance.