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Generative AI is already boosting efficiency in knowledge work—automating administrative workflows, accelerating analysis, and scaling personalized communication—yet short‑term productivity gains risk being undermined by privacy breaches, algorithmic bias, and loss of tacit expertise unless firms invest in governance and reskilling.
low review_meta openalex
The Use of ChatGPT in Business Productivity and Workflow Optimization · Horn Sarun · Mar 26, 2026
ChatGPT-4 slashes multifamily underwriting time by up to 90% in a standardized Seattle test, but consistently misses local market nuances—human oversight remains essential.
medium quasi_experimental openalex
AI-Augmented Real Estate Underwriting: A Practical Framework for Integrating Generative AI into Multifamily Pro Forma Development · Sushmita Vinod Naik · Mar 26, 2026
China’s national digital‑economy pilot zones materially raise the quality and digital intensity of listed firms’ productive capacity, boosting high‑tech productivity and green innovation; gains are concentrated among non‑state, high‑tech, and eastern companies.
medium quasi_experimental openalex
The Impact of Digital Economy Pilot Zones on Corporate New Quality Productive Forces: Evidence from Double Machine Learning · Mingrui Rao, Yan Chen · Mar 26, 2026
AI-enabled finance platforms broaden credit and savings access for low-income users and help buffer climate shocks—women appear to benefit most; but digital-literacy gaps, infrastructure limits and privacy risks threaten inclusive reach and sustained impact.
medium descriptive openalex
Artificial Intelligence, Climate Resilience, and Financial Inclusion: Case Studies from the Global South · Neha Mehta · Mar 26, 2026
US AI investment rises with economic growth, trade openness, renewable energy use and global integration, but energy-policy volatility shows a Goldilocks effect — some uncertainty spurs innovation, while high unpredictability undermines long-term AI investment.
low correlational openalex
Do energy policy uncertainty, trade openness, and renewable energy drive artificial intelligence investment? Evidence from the United States · Xin Jin, Babatunde Sunday Eweade, Dilber Uzun Ozsahin, Berna Uzun · Mar 26, 2026
An AI system that ingests news and market data improves regulators' early detection of financial stress in retrospective tests, offering a practical tool to speed up responses to emerging instabilities.
medium descriptive openalex
Research on the Construction of an AI-Driven Financial Regulatory Early Warning Mechanism · Xiaowen Zhang · Mar 26, 2026
A co-regulating metacognitive layer helps LLM design agents escape fixation and produce better battery-pack designs. The CRDAL architecture outperforms both a plain loop and a self-assessing loop on design quality and design-space exploration, with no significant increase in computational cost.
medium quasi_experimental arxiv
Supervising Ralph Wiggum: Exploring a Metacognitive Co-Regulation Agentic AI Loop for Engineering Design · Zeda Xu, Nikolas Martelaro, Christopher McComb · Mar 25, 2026
A large procurement workflow that looks safe at the state level can still hide sizable next-step uncertainty: expanding state detail from 42 to 668 raises state-action blind mass from 0.0165 to 0.1253, implying much higher oversight needs than coarse metrics suggest; a simple maximum-probability score m(s) predicted autonomous-step accuracy on held-out data within about 3.4 percentage points.
medium theoretical arxiv
The Stochastic Gap: A Markovian Framework for Pre-Deployment Reliability and Oversight-Cost Auditing in Agentic Artificial Intelligence · Biplab Pal, Santanu Bhattacharya · Mar 25, 2026
Proposed system would let autonomous agents sell verifiable 'memories', turning one-off API calls into tradable assets and potentially cutting redundant work. The idea is purely conceptual and untested: critical issues of valuation, verification at scale, privacy, and incentives remain unaddressed.
n/a theoretical arxiv
Infrastructure for Valuable, Tradable, and Verifiable Agent Memory · Mengyuan Li, Lei Gao, Haoxuan Xu, Jiate Li, Potung Yu, Lingke Cheng, Yue Zhao, M... · Mar 25, 2026
A new public dataset of 55 hours of continuous expert desktop recordings and 3.6M UI annotations aims to jump-start general-purpose computer-use agents; preliminary benchmarks show current action models fail about 60% of professional tasks, indicating substantial room for improvement.
n/a descriptive arxiv
CUA-Suite: Massive Human-annotated Video Demonstrations for Computer-Use Agents · Xiangru Jian, Shravan Nayak, Kevin Qinghong Lin, Aarash Feizi, Kaixin Li, Patric... · Mar 25, 2026
A redesigned generative search engine, OneSearch-V2, boosted on-site engagement and sales in live experiments—raising item clicks by ~4%, buyer conversion by ~3%, and order volume by ~2%—achieving these gains through latent-reasoning query understanding and self-distillation without increasing latency.
medium rct arxiv
OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework · Ben Chen, Siyuan Wang, Yufei Ma, Zihan Liang, Xuxin Zhang, Yue Lv, Ying Yang, Hu... · Mar 25, 2026
A simple dynamical model calibrated to PISA and domain data finds humans risk abrupt loss of core skills once AI performs roughly 85% of tasks, but scheduled practice or occasional AI outages can largely avert the collapse.
medium theoretical arxiv
The enrichment paradox: critical capability thresholds and irreversible dependency in human-AI symbiosis · Jeongju Park, Musu Kim, Sekyung Han · Mar 25, 2026
An AI system matches human experts on preschool-quality ratings (up to 88% agreement) and speeds assessments 18-fold, making monthly AI-assisted monitoring in Chinese kindergartens feasible.
medium descriptive arxiv
When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools · Xingming Li, Runke Huang, Yanan Bao, Yuye Jin, Yuru Jiao, Qingyong Hu · Mar 25, 2026
Pharma’s AI promise won’t be proven by accuracy metrics alone: EFMC2 calls for new impact-oriented KPIs to measure whether AI actually raises R&D productivity and drives top-line value, arguing that strategic indicators are needed to guide adoption and innovation.
n/a commentary semantic_scholar
Strategic Key Performance Indicators for AI in Lead Optimization · Theodor Theis, S. Flohr, Hayley Binch, Werngard Czechtizky, Ewa I. Chudyk, Marku... · Fetched Mar 25, 2026
Among 326 Chinese B2B SMEs, managers who view AI as useful and have AI-capable suppliers are more likely to adopt AI for procurement, and adoption is associated with a roughly 21% faster decision cycle and 16% lower procurement costs; lack of organizational resources hampers uptake.
low correlational semantic_scholar
Research on the Adoption of Artificial Intelligence and Procurement Decision-Making Behavior in B2B Scenarios Based on Quantitative Analysis · Bojun Liu · Fetched Mar 25, 2026
A self-hosted, 8B-parameter model for Dream11's CriQ reduces text-to-SQL input size by over 99%, eliminates costly external API calls, and improves execution success to 98.4% and semantic accuracy to 92.5%, outperforming a Gemini Flash 2.0 baseline; the approach offers a practical route to lower-latency, lower-cost production deployment for domain-specific conversational SQL applications.
medium descriptive arxiv
Schema on the Inside: A Two-Phase Fine-Tuning Method for High-Efficiency Text-to-SQL at Scale · Chinmay Soni, Shivam Chourasia, Gaurav Kumar, Hitesh Kapoor · Mar 25, 2026
Teaching a time-series foundation model basic economic rationality improves demand forecasts: Chronos-2 fine-tuned on synthetic, GARP-consistent consumer histories predicts real consumer choices markedly better than the zero-shot model across all tested horizons. The result indicates economic theory can supply structured synthetic data that acts as a powerful forecasting prior.
medium quasi_experimental arxiv
GARP-EFM: Improving Foundation Models with Revealed Preference Structure · Victor H. Aguiar, Nail Kashaev · Mar 25, 2026
Generative AI used for legal drafting can flip into producing convincing but fictitious case law when internal model states cross a calculable threshold; this deterministic failure mode — not mere randomness — means lawyers, courts and regulators must adopt verification protocols rather than treating these systems as black boxes.
low theoretical arxiv
When AI output tips to bad but nobody notices: Legal implications of AI's mistakes · Dylan J. Restrepo, Nicholas J. Restrepo, Frank Y. Huo, Neil F. Johnson · Mar 25, 2026
Firms with stronger AI development shift income toward capital and away from labor, but the effect varies across industries and ownership types and is dampened by financing constraints.
medium correlational openalex
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON ENTERPRISE INCOME DISTRIBUTION  · Jiang Zhan, JianHeng Ye, Guofeng Liang, Fanrong Feng · Mar 25, 2026
Digital technologies — from automation and IIoT to ERP and AI — are strongly associated with rising labor productivity across Kazakhstan's industry. Case studies of major firms and aggregate regressions suggest digitalization, rather than workforce size or hours, drives most efficiency gains, but causality is not robustly isolated.
low correlational openalex
Digitalization and labor costs: efficiency of industrial enterprises in Kazakhstan · E. S. Akanova, А. Z. Kapenova, Y. U. Uzun, А. А. Mutaliyeva · Mar 25, 2026
AI innovation and 'recasting' are prerequisite for platform firms to gain competitive edge; three distinct AI-driven configurations—dominant, subsidiary, and collaborative—produce advantage, with innovation platforms outperforming transaction platforms.
medium correlational openalex
How AI Enables Platform Enterprises to Build Competitive Advantages: A Configurational Analysis from the Perspective of Situated AI Theory · Xuguang Guo, Ying Teng, Huayong Du · Mar 25, 2026
Combining humans and agentic AI can triple media-production throughput in pilots and raise creative-quality metrics by roughly a quarter to over half, according to illustrative case studies — though the results come from limited, non-randomized deployments. Cyborg workflows offer a practical roadmap for media teams, but claims need independent, rigorous validation before being taken as generalizable productivity gains.
low descriptive openalex
Cyborg Workflows Merging Human Judgment and Agentic AI for Digital Media Transformation · P. Selvaprasanth · Mar 25, 2026
Algorithmic oversight in public transport—from constant GPS tracking to automated deactivations—correlates with higher anxiety, burnout and chronic precarity among drivers; authors call for transparency, mandatory mental-health risk audits, human review of sanctions and wage protections to curb psychological harm.
medium review_meta openalex
Algorithmic Control and Psychological Risk in Digitally Managed Public Transport Systems: Implications for Occupational Mental Health · Johnson O. Oloyele, ADEDOYIN IBOSIOLA, Goodness Olaleye, Damilola Elizabeth Baka... · Mar 25, 2026
Public MCP repositories show a rapid shift toward agent tools that take direct action: software-development agents dominate the ecosystem, and usage of action-enabled tools climbed from 27% to 65% in 16 months, including agents capable of financial transactions. The dataset suggests regulators should monitor the tool layer as well as model outputs to detect deployment risks beyond model-level behaviour.
medium descriptive openalex
How are AI agents used? Evidence from 177,000 MCP tools · Merlin Stein · Mar 25, 2026
AI forecasting and inventory tools meaningfully improve inventory outcomes and operational resilience in smart manufacturing, but benefits materialize only where firms have clean data, trained personnel and the right organizational capabilities.
low descriptive openalex
Assessing the Effectiveness of AI-Driven Techniques for Demand Forecasting and Inventory Optimization in Smart Manufacturing · Matthew Anderson · Mar 25, 2026