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A closed-loop platform trains 8B enterprise agents that the authors say match GPT-4o on workflow benchmarks while cutting inference costs eight- to tenfold; the approach aims to let firms deploy capable, privacy-preserving assistants without sending data to frontier models.
medium descriptive arxiv
EnterpriseLab: A Full-Stack Platform for developing and deploying agents in Enterprises · Ankush Agarwal, Harsh Vishwakarma, Suraj Nagaje, Chaitanya Devaguptapu · Mar 23, 2026
Economies should stop overrelying on forecasts and build adaptive preparedness: a five‑pillar model places AI‑enabled decision systems alongside energy, supply‑chain, human‑capital and financial resilience to manage systemic shocks.
low theoretical openalex
Beyond Forecasting: Adaptive Economic Preparedness in a Geopolitically Uncertain and AI-Driven World · Ravi Kumar Neelayapalem · Mar 23, 2026
AI has been remaking science for six decades: successive generations of tools have outsourced bottlenecks to machines, and an emergent ecosystem of agents, preprint platforms, codebases and citation infrastructure is speeding discovery, changing who can do science and altering incentives for credit.
n/a review_meta openalex
A Brief History of AI for Scientific Discovery: Open Research, Metrics, and Autonomous Agents · Surasak Phetmanee · Mar 23, 2026
An LLM-driven graph workflow slashed API implementation time at Volvo from roughly five hours to under seven minutes per endpoint, achieving 93.7% automation accuracy; the pilot reported an estimated 979 engineering hours saved and unanimous stakeholder satisfaction.
medium quasi_experimental arxiv
LLM-Powered Workflow Optimization for Multidisciplinary Software Development: An Automotive Industry Case Study · Shuai Wang, Yinan Yu, Earl Barr, Dhasarathy Parthasarathy · Mar 22, 2026
Generative AI forces a rethink of professional expertise and firm design: existing theories of work and organizations need extension to capture new, evolving interdependencies between professionals and generative machine learning, the paper argues.
n/a theoretical openalex
Generative machine learning in professional work and professional service firms : a research agenda · James Faulconbridge, Kasper Trolle Elmholdt, Frida Pemer, Aline Seepma, Tale Skj... · Fetched Mar 22, 2026
Firms that adopt generative AI report better decision quality and greater strategic agility, and these gains are linked to stronger organizational performance; however, benefits depend on company culture and technological readiness and the evidence is associative rather than causal.
low correlational openalex
The Strategic Impact of Generative Artificial Intelligence on Organizational Decision Making · Muhammad Nawaz Khan · Mar 22, 2026
A cheap Shadow-RAG tutor unlocks latent capability in modern 32B models: on a graduate Applied Mathematics final, structured reasoning guidance lifts accuracy from 74% with naive retrieval to 90%, achieved with just 3 person‑days and a single consumer GPU, while older model generations improve far less.
medium descriptive arxiv
From 50% to Mastery in 3 Days: A Low-Resource SOP for Localizing Graduate-Level AI Tutors via Shadow-RAG · Zonglin Yang, J. -H. Xie, Lining Zhang, Jiyou Jia, Zhi-X. Chen · Mar 21, 2026
AI deployment and its market value are highly concentrated: just 1.6% of work activities account for over 60% of AI market value, with 72% directed at information-based tasks and only 12% at physical activities.
medium descriptive arxiv
Where can AI be used? Insights from a deep ontology of work activities · Alice Cai, Iman YeckehZaare, Shuo Sun, Vasiliki Charisi, Xinru Wang, Aiman Imran... · Mar 21, 2026
Firms engaged in an automation arms race rationally displace more workers than is socially optimal, eroding demand and harming both workers and owners; conventional fixes—from wages and entry to UBI or upskilling—fail, leaving a Pigouvian automation tax as the only effective remedy.
n/a theoretical arxiv
The AI Layoff Trap · Brett Hemenway Falk, Gerry Tsoukalas · Mar 21, 2026
US mid-to-large firms that adopt AI in recruitment report faster, cheaper, and higher-quality hiring, with top-management support and perceived usefulness driving adoption; making algorithms transparent is crucial for perceived fairness and improved employee experience.
low correlational openalex
Artificial Intelligence Adoption in Talent Acquisition: Effects on Recruitment Efficiency, Algorithmic Fairness Perceptions, and Employee Experience · Aichurek Nuralieva · Mar 21, 2026
Industrial robots strengthen Chinese cities' ability to withstand energy shocks, chiefly by modernising industry and boosting green innovation; the resilience gains are larger in cities with stricter environmental rules and higher science budgets.
medium quasi_experimental openalex
Does the Application of Industrial Robots Enhance Urban Energy Resilience? Evidence from China · Bingnan Guo, Mengyu Li · Mar 21, 2026
Let platforms finance app development: revenue-sharing-as-infrastructure would let developers build on AI platforms without upfront fees, widening participation and aligning incentives between platforms and app-makers. The idea could unlock innovation and latent jobs in low-income countries, but its impact depends on platform strategy, monetization feasibility, and regulatory and payment-system realities.
n/a theoretical arxiv
Revenue-Sharing as Infrastructure: A Distributed Business Model for Generative AI Platforms · Ghislain Dorian Tchuente Mondjo · Mar 20, 2026
Google Gemini favors non-OTA sources for experiential hotel queries far more than for transactional ones, widening the discovery path beyond commission-driven intermediaries; the effect is stronger in Japanese than in English.
medium descriptive arxiv
The End of Rented Discovery: How AI Search Redistributes Power Between Hotels and Intermediaries · Peiying Zhu, Sidi Chang · Mar 20, 2026
Orchestrated human–AI workflows sharply cut effort and defects: across three real modernization projects, the Chiron platform reduced modeled person-days from 1080 to 232.5 and senior-equivalent effort from 1080 to 139.5 days, halved validation issues and raised first-release coverage from 77% to 90.5%, with largest gains when AI was embedded in the end-to-end delivery flow rather than used as an isolated coding assistant.
medium quasi_experimental arxiv
Orchestrating Human-AI Software Delivery: A Retrospective Longitudinal Field Study of Three Software Modernization Programs · Maximiliano Armesto, Christophe Kolb · Mar 20, 2026
Generative AI lifts task productivity by 15–50%—especially for junior workers—yet so far has not caused mass unemployment; instead it reshapes entry-level roles and demands organizational change before broad macro gains emerge.
medium review_meta semantic_scholar
AI, Productivity, and Labor Markets: A Review of the Empirical Evidence · Eric Fruits, Kristian Stout · Fetched Mar 20, 2026
China's growth model is shifting from investment to innovation: total factor productivity's share rose from 18% to 26% in 2016–22, with the digital economy explaining about 40% of that increase; coastal provinces are innovation-driven while inland regions remain capital-intensive.
medium correlational semantic_scholar
Analysis of China's Economic Growth Drivers: An Empirical Study Based on an Extended Cobb-Douglas Production Function (2010-2022) · Zihan Zhao · Fetched Mar 20, 2026
AIGQ’s generative query suggestions boost Taobao engagement: an interest-aware training and policy-optimization pipeline raises click-through and other business metrics in large-scale randomized homepage tests.
high rct arxiv
AIGQ: An End-to-End Hybrid Generative Architecture for E-commerce Query Recommendation · Jingcao Xu, Jianyun Zou, Renkai Yang, Zili Geng, Qiang Liu, Haihong Tang · Mar 20, 2026
Inventory-theory regularization steadies deep-RL: grounding DRL policies in base-stock concepts speeds hyperparameter tuning and raises inventory performance, enabling a 100% deployment on Alibaba's Tmall; synthetic tests show regularization alters which DRL methods perform best.
medium descriptive arxiv
DeepStock: Reinforcement Learning with Policy Regularizations for Inventory Management · Yaqi Xie, Xinru Hao, Jiaxi Liu, Will Ma, Linwei Xin, Lei Cao, Yidong Zhang · Mar 20, 2026
Human-crafted 'skills' let AI agents reliably program real IoT devices, whereas out-of-the-box LLM skills often fail due to timing and hardware-specific constraints; hardware-in-the-loop validation across platforms shows human expertise remains crucial for embedded software success.
medium quasi_experimental arxiv
Skilled AI Agents for Embedded and IoT Systems Development · Yiming Li, Yuhan Cheng, Mingchen Ma, Yihang Zou, Ningyuan Yang, Wei Cheng, Hai "... · Mar 20, 2026
China’s digital economy boosts provincial carbon productivity both locally and across borders, while industrial intelligence depresses local carbon productivity but produces strong positive spillovers that make its net effect beneficial; impacts vary sharply by region.
low correlational openalex
Study on the impact of industrial intelligence and the digital economy on China’s regional total factor carbon productivity under carbon neutrality · Dandan Xiao, Jinwang Liu · Mar 20, 2026
A 1,400-question benchmark finds modern LLMs can leverage retrieval to interpret company filings but largely fail at market trading-signal and time-series reasoning; this gap limits their reliability for real-world financial decision-making.
low descriptive arxiv
FinTradeBench: A Financial Reasoning Benchmark for LLMs · Yogesh Agrawal, Aniruddha Dutta, Md Mahadi Hasan, Santu Karmaker, Aritra Dutta · Mar 19, 2026
A new benchmark reframes GPU kernel evaluation around hardware 'Speed-of-Light' limits: SOL-ExecBench measures 235 CUDA kernels from 124 AI models on NVIDIA Blackwell GPUs and scores optimizers by how much of the gap to analytically derived hardware bounds they close, with measurement safeguards to deter reward-hacking.
n/a descriptive arxiv
SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits · Edward Lin, Sahil Modi, Siva Kumar Sastry Hari, Qijing Huang, Zhifan Ye, Nestor ... · Mar 19, 2026
Learner prerequisites — not information abundance — can bottleneck AI-driven knowledge adoption: unless teaching reaches the prerequisite depth of a target concept, extra instruction is futile, and one-size-fits-all broadcasts can be up to proportionally slower than tailored teaching across diverse learner types.
n/a theoretical arxiv
A Mathematical Theory of Understanding · Bahar Taşkesen · Mar 19, 2026
AI agents fall short on domain-specific data science: in a 17-task benchmark across six industries, AI-only systems performed near or below the median human competitors, while human–AI teams produced the strongest solutions, underscoring the continued importance of human expertise.
medium descriptive arxiv
AgentDS Technical Report: Benchmarking the Future of Human-AI Collaboration in Domain-Specific Data Science · An Luo, Jin Du, Xun Xian, Robert Specht, Fangqiao Tian, Ganghua Wang, Xuan Bi, C... · Mar 19, 2026
Simulated deployments of predictive-policing systems reveal extreme, city-specific racial disparities in police detection—Baltimore shows runaway amplification while Chicago exhibits systematic under‑detection of Black residents; algorithmic debiasing via CTGAN shifts but does not erase these structural imbalances.
medium descriptive arxiv
Unmasking Algorithmic Bias in Predictive Policing: A GAN-Based Simulation Framework with Multi-City Temporal Analysis · Pronob Kumar Barman, Pronoy Kumar Barman · Mar 19, 2026