The Landscape of Generative AI in Information Systems: A Synthesis of Secondary Reviews and Research Agendas

TEXT START: The post-ChatGPT surge has rapidly reframed IS research and practice.

The Dissection

This paper converts a structural rupture into an institutional research agenda. It catalogs benefits, unreliability, ethical risks, and governance gaps, then routes them toward “joint optimization”: hybrid human-AI ensembles, validation, design principles, and adaptive regulation. The result is a management framework for absorbing disruption, not an analysis of who loses productive necessity or who controls the systems.

The Core Fallacy

It mistakes institutional lag for a solvable coordination problem. Under the Discontinuity Thesis, superior AI does not wait for organizations, regulators, or social values to co-evolve. Competitive pressure forces substitution wherever cognitive labor can be automated. Human-AI collaboration is therefore a temporary transition form, not evidence that mass human participation remains economically necessary. Governance can shape deployment, but it cannot repeal the productivity and ownership mechanics driving displacement.

Hidden Assumptions

• Productivity gains will become broadly shared benefits rather than accrue to AI-capital owners.
• Human oversight and validation will remain scarce, valuable, and resistant to automation.
• Organizations can choose augmentation over substitution despite competitive pressure.
• Regulators can coordinate effectively across jurisdictions and firms.
• “Democratizing expertise” expands durable economic agency rather than making expertise cheaper and labor more disposable.
• Technical and social subsystems can reach stable alignment before productive participation collapses.

Social Function

Transition management and ideological anesthetic, containing a partial truth. The paper accurately identifies technical unreliability and governance weakness, but packages the distributional crisis as a design-and-regulation problem. Its language allows institutions to appear responsible while avoiding ownership, bargaining power, wage dependency, and the death of the mass employment-consumption circuit.

The Verdict

A competent inventory of symptoms with the central mechanism omitted. Its proposed agenda may make AI deployment safer, more governable, and more productive—thereby accelerating the automation it treats as a socio-technical mismatch. Under DT, this is not a roadmap for broadly shared prosperity. It is a polished hospice manual for information-systems scholarship as productive participation moves toward collapse.