Emergence of Agentic AI: A Review on Evolution, Background, Working Principles, Applications, Adoption Factors, and Future Research Directions

TEXT START:Agentic AI is gaining new insights and advancements in the field of Artificial Intelligence, fostering significant potential to enable rapid transformation across various this http URL rapid advancement and the potential to revolutionize various domains advocate the need for a deeper understanding and firm grasp of the technology.

The Dissection

This is a field-mapping document disguised as strategic understanding. It catalogs architectures, applications, adoption factors, challenges, and research gaps, but the supplied abstract contains no demonstrated productivity results, labor-displacement analysis, ownership analysis, or account of who captures the gains. Its “comprehensive framework” appears to organize stakeholder willingness to adopt—not to explain the structural consequences of adoption.

The paper treats agentic AI as an emerging research domain whose central problem is insufficient understanding. Under the Discontinuity Thesis, the more dangerous problem is sufficient understanding followed by deployment: autonomous systems become scalable substitutes for cognitive labor, while institutions remain unable to preserve human economic necessity.

The Core Fallacy

The core error is technological neutrality. The review frames agentic AI as a set of capabilities to be studied, improved, and adopted, as if adoption were the endpoint. It is not. Adoption is the transmission mechanism through which cognitive work is detached from human labor and concentrated in the hands of whoever owns the models, infrastructure, data, energy, and distribution channels.

Its adoption logic implicitly assumes that improved system quality produces broadly shared benefit. Under P1–P3, improved system quality produces competitive pressure to automate, P2 blocks durable human-only economic enclaves, and P3 destroys the majority’s access to economically necessary work. The paper studies the machine’s competence while leaving the wage-consumption circuit outside the autopsy.

Hidden Assumptions

• Technical progress will translate into socially productive transformation rather than labor substitution and ownership concentration.
• Stakeholders can choose whether to adopt without competitive coercion.
• Human institutions can absorb agentic systems without losing control of the allocation process.
• Adoption factors such as system quality, usefulness, trust, and ease of use are sufficient predictors of social outcomes.
• “Applications across various domains” implies expansion of opportunity rather than expansion of replaceable tasks.
• New research directions are inherently beneficial, rather than potentially accelerating the destruction of human bargaining power.
• Preserving consumption through transfers, if required, would amount to preserving the existing economic order. It would not. Consumption can be subsidized after productive participation has collapsed.
• The future remains a labor-centered economy in which humans retain an indispensable role. That is precisely the assumption agentic AI puts on trial.

Social Function

Primary classification: prestige signaling and transition management, with a secondary function as ideological anesthetic.

The review is not worthless. A serious inventory of agentic architectures, failure modes, applications, and research gaps can expose real mechanisms. But its framing domesticates the threat. It converts a potential regime transition into a normal academic lifecycle: define the field, improve system quality, increase adoption, identify gaps, and continue.

That narrative is useful to institutions because it makes disruption look governable and incremental. It also serves elites by treating deployment as an engineering and adoption problem rather than a question of ownership, bargaining power, and mass economic redundancy. The malformed abstract—repeated “this http URL” artifacts, inflated claims, and no visible empirical anchor—further weakens its authority as evidence, even while its vocabulary performs comprehensiveness.

The Verdict

This is a reconnaissance map of the weapon, not an analysis of the battlefield. It may clarify how agentic AI works and where it can be deployed, but the supplied text does not confront the Discontinuity Thesis’s decisive issue: once agentic systems become cheaper, faster, and more reliable than humans across cognitive work, adoption becomes a competitive compulsion rather than a voluntary social preference.

Its likely systemic effect is therefore accelerative. By improving understanding, deployment, and adoption without modeling ownership and productive-participation collapse, the review helps prepare the machinery that severs labor from income. It describes the approaching guillotine as an innovation pipeline.