Truace
Subscribe

AI-human collaborative decision-making and how its dynamics and typologies shape decision outcomes

Source article: Advancing Decision-Making through AI-Human Collaboration: A Systematic Review and Conceptual Framework

Abstract The interplay between humans and artificial intelligence (AI) in decision-making has become increasingly intricate and significant. Despite rapid advancements, the literature remains fragmented, with limited integrative frameworks to explain how AI-human dynamics and decision-making typologies shape outcomes. This study addresses this critical gap by conducting a systematic review and bibliometric analysis of 627 articles, culminating in a novel conceptual framework. The framework identifies two critica…

By the Truvace desk2 min read1 sourcePeer-reviewedTRV-2026-0226· cite & verify
Advancing Decision-Making through AI-Human Collaboration: A Systematic Review and Conceptual Framework
Open architecture as an enabler for FORCEnet Cruise Missile Defense by Camacho, Juan G. Guest, Lawrence F. Hernandez, Belen M. Johnson, Thomas M. Kang, Alan H. Le, Giang T. MacGillivray, Brian J. Ngo, Tu K. Norman, Kyle B. Tomei, Franklin. Public domain
Trace impact readingContested
P 72The P score combines the specificity and measured human impact of the grounded problem claim with the strength of this Trace’s cited sources.

Both sides are scored from claims and sources, not community votes.

G 69The G score combines the specificity and measured human impact of the grounded gain claim with the strength of this Trace’s cited sources.

In brief

On 2026-04-03, a peer-reviewed article reported a systematic review and bibliometric analysis of 627 articles on human-AI decision-making. The authors identified two critical dimensions, AI-human dynamics and decision typologies, and proposed a novel conceptual framework comprising four paradigms: adaptive intuitive, programmed algorithmic, interpretive analytical, and integrative hybrid decision-making.

The framework matters because it moves beyond fragmented prior literature to clarify mechanisms and trade-offs in hybrid decision systems, offering actionable insights for organizations navigating AI-driven environments. As a conceptual synthesis rather than an empirical trial of a specific deployment, its impact remains theoretical, laying a foundation for future research on adaptive decision systems amid accelerating technological change.

Main points

  1. Systematic review and bibliometric analysis covered 627 articles on AI-human decision-making.
  2. Framework identifies two critical dimensions: AI-human dynamics and decision typologies that shape decision outcomes.
  3. Proposes four distinct paradigms: adaptive intuitive decision, programmed algorithmic decision, interpretive analytical decision and integrative hybrid decision.

The gain

A systematic review and bibliometric analysis of 627 articles produced a conceptual framework with two dimensions and four paradigms that advances theoretical understanding of hybrid decision-making and provides actionable insights for organizations in AI-driven environments.

The problem

Existing literature on AI-human decision-making was fragmented and lacked integrative frameworks to explain how AI-human dynamics and decision typologies shape outcomes despite increasingly intricate human-AI interplay.

The rundown

The authors conducted a systematic review and bibliometric analysis of 627 articles to address fragmentation in the field. From this corpus they distilled two critical dimensions that shape decision outcomes: AI-human dynamics and decision typologies.

They synthesized these dimensions into four distinct paradigms of AI-human collaborative decision-making: adaptive intuitive decision, programmed algorithmic decision, interpretive analytical decision and integrative hybrid decision. The work is positioned as advancing theoretical understanding of hybrid systems and elucidating mechanisms and trade-offs inherent in collaboration.

Sources

  1. Peer-reviewedGroup Decision and Negotiation2026-04-03

The debate