Generative AI in the Workplace: Managerial Implications for Creativity, Productivity, and Job Design
DOI: https://doie.org/10.10399/IJBE.2026347434
Dr. Parul Agrawal, Dr Jitendra Patel, Rupam Jyoti Deka
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Keywords:
generative artificial intelligence, productivity, creativity, job design, work design, human–AI collaboration, management
Abstract:
Generative artificial intelligence (AI) has moved from laboratory novelty to a general-purpose technology embedded in everyday knowledge work, raising urgent questions for managers about how to capture its benefits while managing its risks. This paper synthesises the emerging empirical and theoretical literature to examine the managerial implications of generative AI across three interrelated domains: productivity, creativity, and job design. Field and laboratory experiments converge on substantial average productivity gains, with effects concentrated among less-experienced workers, suggesting that generative AI can compress performance inequality and act as a skill-leveller. Evidence on creativity is more ambivalent: the technology elevates the novelty and quality of individual outputs yet narrows collective diversity, creating a social dilemma for organisations that depend on variety for innovation. For job design, generative AI reconfigures the task composition of roles along an augmentation–automation spectrum, with consequences for autonomy, skill variety, and meaning that map directly onto established work-design theory. The paper advances an integrative framework and a five-stage managerial approach: assess, redesign, reskill, govern, and learn, arguing that the value of generative AI depends less on the technology itself than on the deliberate organisational choices that surround its adoption.