Review of 43 studies finds AI aids government decisions but raises bias and transparency concerns

Study title: The Impact of Artificial Intelligence on Public Sector Decision- Making: Benefits, Challenges, and Policy Implications

A systematic review of 43 studies from 2020-2025 examined how artificial intelligence is transforming government decision-making, finding benefits in efficiency and data-driven service delivery alongside drawbacks including bias and transparency deficits.

Read the study abstract

Artificial intelligence (AI) is increasingly transforming government decision-making processes. This article presents a systematic literature review of 43 studies (2020-2025) examining AI’s impact on public-sector decision-making, delineating its advantages, disadvantages, policy implications, technical aspects, and ethical concerns. The findings indicate that AI technologies offer significant benefits for government decision-making, including improved efficiency, data-driven insights, and enhanced service deliv…

By the Truvace deskJuly 22, 20261 min read1 sourceEvidence: Moderate · 70/100 — Systematic review or meta-analysis · n = 43 · 1 independent sourcePeer-reviewedTRV-2026-0493· cite & verify

The Impact of Artificial Intelligence on Public Sector Decision- Making: Benefits, Challenges, and Policy Implications — "WSIS Forum 2013 - The Elephant in the Room: Why the Economic Dimension Needs Higher Priority in Internet Governance Policy Debates (International Digital Economy Alliance (IDEA)" by ITU Pictures is licensed under CC BY 2.0. To view a copy of this license, visit https://creativecommons.org/licenses/by/2.0/.

Trace impact readingContested

P 61

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

G 63

In brief

The findings matter because governments are deploying AI for high-stakes decisions, and the review indicates that without governance frameworks, regulatory oversight, and attention to data quality and explainability, efficiency gains may be undermined by erosion of accountability and public trust.

Main points

Systematic literature review of 43 studies from 2020-2025 on AI in public-sector decision-making.
Technical success factors identified include data quality, system integration, and explainable AI.
Policy response calls for robust governance frameworks, regulatory oversight, and ethical guidelines to ensure accountability and public trust.

The gain

AI adoption in government was found to improve efficiency and service delivery through automation of routine tasks and predictive analytics.

The problem

Integration of AI into government decision-making introduces algorithmic bias, transparency deficits, and accountability challenges that raise fairness and privacy concerns.

The rundown

The review synthesized 43 peer-reviewed studies published between 2020 and 2025 to map advantages, disadvantages, policy implications, technical aspects, and ethical concerns of AI in government.

Authors highlight that data quality and explainable AI are critical for implementation, while ethical debates center on fairness, privacy, transparency, and alignment with public values.