Generative AI and IT Workforce: Emerging Findings from a Multi-Site Focus Group Study

Abstract

To address the need for research on AI's impact on the information technology workforce, the Society of Information Management (SIM) Academic Council is conducting a series of focus groups with SIM leaders throughout the United States. Currently, eight SIM chapters have conducted focus groups. Thematic analysis reveals several consistent and unexpected findings, three of which we highlight here. Participants consistently described GAI as a ''productivity multiplier'' that is shifting the way in which workers add value. With the increasing capabilities of GAI, daily work is migrating from writing code to two main areas: directing and architecting AI agents, and evaluating and debugging AI-generated code. Participants noted the commoditization of baseline-level technical execution. When AI can produce competent first ''drafts'' of code and documentation, the ability to discern the quality and appropriateness of AI generated output becomes the scarce resource. This represents a structural shift from building to orchestration and evaluation. This shift not only affects desirable skills, it also validates the importance of domain knowledge and critical thinkingParticipants also noted significant changes in requirements for entry-level positions, which may create a talent pipeline collapse. Participants also described the collapse of algorithmic hiring and a reversion to relationship-based channels. Applicant tracking systems (ATS) are becoming overwhelmed by AI-optimized resumes, resulting in a move away from algorithmic screening towards professional network-based hiring. Taken together, these implications suggest that GAI is not only changing the nature of IT work, but is also restructuring how the profession identifies, develops, and grants access to talent.

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