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AI investment has a U-shaped link to internal-control problems: modest AI spending appears to strengthen controls, but beyond a turning point higher AI investment is associated with more control deficiencies — a pattern strongest for software AI and softened by CIOs, IT-industry firms and greater audit scrutiny.
medium quasi_experimental Summary openalex
Too Much of a Good Thing? AI Investment and Internal Control Deficiency · Wentao Ma, Bingjie Deng, Xiaofan Chen, Wanyun Li · Jul 05, 2026
Specifying which parts of online content were generated by AI can blunt the trust-damaging effects of blanket AI disclosures; scope-based labels make AI involvement more informative and convey seller effort, improving consumer responses.
medium rct Summary openalex
From Compliance to Communication: How Explainable AIGC Disclosure Shapes Consumer Responses in E-Commerce · Kaixin Sha, Qi Wang, D Xu · Jul 05, 2026
AI investments fail to scale because firms treat AI as a broad technology program rather than as discrete, governable decision opportunities; a decision-centric AIPN framework ties AI spending to identifiable, measurable sources of value and prescribes staging and portfolio assembly to improve returns.
n/a theoretical Summary openalex
Governing Enterprise AI Investments: A Decision-Centric Portfolio Framework · Abhinav Mathur, Abhishek Kathuria, Devina Chaturvedi · Jul 05, 2026
Generative AI is moving from a peripheral tool to a core strategic partner in corporate governance, boosting decision quality when organizations cultivate shared human-AI intentionality and the right interface and trust structures; however, these gains are contingent on firm capabilities and contextual factors.
n/a theoretical Summary openalex
GenAI Agency: Mediating Skill Development and Algorithmic Trust · C. C. Liu, Chukui CHEN · Jul 05, 2026
Projects that disclose AI use raise less money on Kickstarter, but the penalty depends on what AI made: admitting AI-created images carries a smaller funding hit than admitting AI-created text, a gap that widens when AI produces the final product and narrows when AI is used for marketing.
medium correlational Summary openalex
The Transparency Penalty Unraveled: How AIGC Modality Moderates Consumer Responses to AI Disclosure in Crowdfunding · Wenhao Bai, Zhong Yao, Wuhuan Xu · Jul 05, 2026
German public research transfer offices are piloting AI largely for language and content tasks, but envision broader process and decision-support uses; adoption is fragmented and often misaligned with established transfer workflows.
low descriptive Summary openalex
AI Use Cases in Knowledge and Technology Transfer: Evidence from Expert Interviews · Josip Lovrekovic, Masoumeh Tavakoligargari, Manuel Etzkorn, Anna Gieß, Jan Jürje... · Jul 05, 2026
Digital twins and AI-powered predictive analytics enhance supply-chain resilience by boosting firms' anticipation and recovery capabilities, with the resilience payoff larger under greater supply-chain complexity; three distinct capability configurations — including an anticipation-led pathway — suffice for high resilience in Taiwan's electronics sector.
low correlational Summary openalex
Digital Twin-Enabled Supply Chain Resilience: Anticipation and Recovery Capabilities in Taiwan's Electronics Manufacturing Sector · Chih‐Lun Wu · Jul 05, 2026
AI capability at startups is multidimensional: firms that combine data/tech stacks, AI talent and agile risk-taking report stronger performance in Qatar's nascent ecosystem. The evidence is correlational — based on a cross-sectional founder survey and PLS-SEM — so linkages should be interpreted as associations, not proven causal effects.
low correlational Summary openalex
AI Capability of Startups in Qatar · Savanid Vatanasakdakul, Deema Al-Mohanadi, Chadi Aoun · Jul 05, 2026
AI decision support for index-fund investors is under-studied: few papers design AI tools to counter cognitive biases, and attention bias among retail investors is especially neglected; a proposed AI artifact and simulation suggest potential gains but lack empirical validation.
low review_meta Summary openalex
Mitigating Attention Bias in Index-Fund Investment: AI-Enabled Decision Support for Retail Investors · Ruiyi Ma, Ying Zhang, David Sundaram · Jul 05, 2026
Workplace AI companions matter for relationships, not just tasks: a new framework argues that cognitive, emotional and developmental competencies arise through sustained worker–AI interaction and should shape design and organizational policy.
n/a review_meta Summary openalex
Thinking, Feeling, Becoming: A Relational Competency Framework for Human–AI Companionship at Work · Min Ou, Hope Koch, Qin Weng · Jul 05, 2026
Listed Nigerian banks that invest in and disclose AI assets—and that deploy chatbots—show higher returns on assets; larger banks also outperform peers. The association is robust in the sample but rests on a small, non-random set of banks and does not establish causality.
low correlational Full text openalex
Artificial Intelligence Structured Investment and Financial Performance of Deposit Money Banks in Nigeria · Joseph Ese Eginiwin, STEVE CHIJIOKE NWAIMO, IRIKEFE PETER OLOWU · Jul 04, 2026
Field experiments show AI tools deliver sizable task-level productivity gains, but national productivity improvements in the United States will depend on wider adoption, complementary software and data investments, and workforce reskilling.
medium review_meta Full text openalex
Effect of Artificial Intelligence Adoption on Labour Productivity in The United States · Sarah Martinez · Jul 03, 2026
AI acts as a general‑purpose productivity engine but with uneven effects: it can spur growth and innovation while amplifying job disruption and inequality, yet the evidence base is fragmented and context‑dependent, calling for more integrated and causal research.
medium review_meta Full text openalex
Artificial Intelligence and Economic Development: A Systematic Review of Patterns and Pathways · Sin‐Yu Ho, Fiyinfoluwa Giwa · Jul 03, 2026
AI can turn grassroots volunteering into scalable social enterprises by using skill-matching, predictive planning and digital impact metrics to boost organizational capacity and spur job creation; realising these gains depends on equitable access, governance and deliberate human-centered design.
n/a theoretical Full text openalex
Artificial Intelligence as a Catalyst for Social Entrepreneurship and Volunteering Engagement · Violeta Zlatkova · Jul 03, 2026
A bibliometric study finds rapid growth in AI-driven green fintech research but little TOE-based theorizing, and proposes a bank-focused framework arguing that infrastructure, culture and regulation jointly unlock green investment benefits.
n/a theoretical Summary openalex
Mediating Pathways to Sustainable Investment: A TOE Framework for AI-Driven Green Fintech Adoption in Banking · Reem A. Abdalla, Lamya Abbas Hidaytalla, Gulnar Sadat Mulla · Jul 03, 2026
A pilot using real-money markets finds that pairing people with AI rarely yields uniform gains: most users either copy the model or worsen performance, but a small subset with collaborative traits reasoning with the AI outperforms both the model and typical human forecasts.
medium correlational Full text arxiv
Human Capital, Not Model Benchmarks, Predicts Hybrid Intelligence in Forecasting · Vivienne Ming · Jul 02, 2026
Frontier coding models and greater reasoning effort sharply raise first-run success and cut correction needs; a browser-based testing tool increased costs without improving functional outcomes, while a design prompt improved interface aesthetics but not functionality.
medium quasi_experimental Full text arxiv
Reasoning effort, not tool access, buys first-try reliability in agentic code generation: an observational study · Achint Mehta · Jul 02, 2026
Applying conventional engineering controls to coding agents dramatically improves security oversight: in a controlled test on a Python repository with 11 injected backdoors, an AI reviewer’s detection recall rose from 54.5% without constraints to 90.9% with a constrained substrate and a small CLI, with both interventions contributing independently.
medium quasi_experimental Full text arxiv
Steerability via constraints: a substrate for scalable oversight of coding agents · Thomas Winninger · Jul 02, 2026
Automated detectors suggest LLM-generated code is common but falling and concentrated in tests and duplicated snippets, while LLM-like comments stay steady; company repositories show higher detected usage, and only a small fraction of human-labeled bugs are associated with flagged LLM code.
low correlational Full text arxiv
An Exploratory Study on LLM-Generated Code and Comments in Code Repositories · Yongyi Ji, Jiaji Wang, Yi Zhou, Fuxiang Chen, Hongji Yang · Jul 02, 2026
LLMs remain short of expert reliability in airport operations: the best models score 82.7% on a 300-question aviation benchmark versus roughly 95% for practitioners, highlighting a persistent, safety-relevant performance gap and the need for domain-specific evaluation before deployment.
n/a descriptive Full text arxiv
Pre-Flight: A Benchmark for Evaluating Large Language Models on Aviation Operational Knowledge · Alex Brooker, Tim Hughes · Jul 02, 2026
AI coding agents make code slightly more complex but do not displace new contributors: across matched GitHub projects, adoption raised Python cognitive complexity by ~11% and cyclomatic complexity by 3–4%, while newcomer inflow, onboarding and retention remained unchanged.
medium quasi_experimental Full text arxiv
Decoupling Code Complexity from Newcomer Participation: A Causal Study of AI Coding Agent Adoption in OSS · Weiwei Xu, Xuanning Cui, Hengzhi Ye, Minghui Zhou · Jul 02, 2026
A single firm's AI coding push coincided with a doubling of developers' merged pull requests to 2.09x pre-mandate levels by April 2026; evidence links most of the gain to voluntary adoption and accumulated use, and code-review work shifted heavily toward automation without higher revert rates.
medium quasi_experimental Full text openalex
AI Writes Faster Than Humans Can Review: A Longitudinal Study of an Enterprise 2x Mandate · H. He, Shyam Agarwal, Yegor Denisov-Blanch, Pavel Azaletskiy, Sanmi Koyejo, Bogd... · Jul 02, 2026
Taxing AI can rebalance costs and fund regulation, but one-size-fits-all levies would misfire; policymakers should match specific tax instruments to distinct AI externalities and grapple with measurement, leakage and innovation trade-offs.
n/a review_meta Full text openalex
Taxing Artificial Intelligence · Juliette Faivre, Sarah H. Cen · Jul 02, 2026
Embodied AI forces firms to redesign how value is created: business models shift from one-off hardware sales toward continuous, data-driven orchestration across ecosystems. That shift creates tensions—openness versus control, scaling versus local fit, automation versus reliability, and monetization versus trust—that firms must manage.
n/a theoretical Full text openalex
Embodied Artificial Intelligence (AI) business model dynamics: concept, framework, and the agriculture template · Ricarda B. Bouncken, Beate Cesinger · Jul 02, 2026
China’s low-carbon city pilots are linked to a substantial expansion of local AI industries — about 17% more AI firms in treated cities — with gains channelled through cleaner energy mixes and increased green technology innovation, especially in established innovation hubs and transitioning regions.
medium quasi_experimental Full text openalex
Do low-carbon cities hinder AI industry growth? Evidence from China · Luyuan Tang, Shiyao Xie, Yuan Xu, Ziwen Sun · Jul 02, 2026