Artificial intelligence (AI) has made great strides and is expected to fundamentally reshape the labor market. But in the absence of longitudinal microdata on firms and workers, research on the effects of AI is still limited, partly contradictory, and demonstrates associations rather than causality. In our ongoing data-driven project, we find that AI is associated with job growth, especially for white-collar workers, and that new occupations are emerging that demand cognitive, social and creative skills. In this continuation project, we focus on key factors behind AI's effects on productivity, wages, job content and work environment. We study firms' and employees' exposure and adaptation to different types of AI in four selected countries over two decades using methods from economics and computer science and unique microdata. We then identify general and specific causal effects on the outcome variables. The goal is to contribute with solid knowledge about how different groups of knowledge-intensive companies and officials are affected by AI. This is to enable politicians, authorities, companies and employees to make informed and future-oriented decisions. Knowledge-intensive services are central to our society's infrastructure and are undergoing a digital transformation. We shed light on how AI affects different groups' tasks, skill requirements, work environment, wages and productivity - in short, what key factors can help workers and employers thrive in tomorrow's world of work.