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UTEP · AAIIAI News Digest
Archived digest · Week of Dec 01 - Dec 07, 2025

Applied AI news,
scored for your field

Each week the Institute for Applied AI Innovation reviews AI publications and scores them for Research Relevance, Educational Value, Innovation/Novelty, Practical Impact, Interdisciplinary Potential and Ethical/Policy Implications. Then it writes summaries for each discipline at UTEP.

Read the top 10 →
Your Discipline 6 stories

The Week at a Glance

Business & Entrepreneurship · Dec 01 - Dec 07, 2025

Business & Entrepreneurship. Accounting/IS, economics/finance, marketing/management/supply chain. Prefers market analysis, analytics, fintech, and innovation strategy.
Departments: Accounting & Information Systems, Economics & Finance, Marketing, Management & Supply Chain
Business & Entrepreneurship

Weekly Summary of Top AI Articles

This week’s articles delve into the transformative role of AI in various sectors, particularly in the workplace and entrepreneurship. Benjamin Manning's research at MIT highlights the potential of AI agents in reshaping market dynamics. Meanwhile, the uneven adoption of generative AI across businesses raises questions about productivity disparities. Additionally, insights into launching AI startups and the importance of productizing analytics tools for supply chain management are discussed, showcasing the diverse applications of AI technology.

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Key Findings
  • AI agents can significantly impact markets and institutions, as explored by Benjamin Manning.
  • Generative AI has transformed software development but is adopted unevenly across industries.
  • Launching an AI startup presents challenges, as illustrated by Julie Bornstein's experience with Daydream.
Implications
  • The integration of AI in the workplace may lead to significant shifts in job roles and market structures.
  • Businesses must strategize their AI adoption to avoid productivity gaps and leverage its full potential.
  • Entrepreneurs in the AI space need to navigate challenges in technology translation and market fit.

Key Metrics

Numbers reported in that week's stories
Predicted productivity increase in software development due to AI coding assistants
5-year inflation data trend analysis from October 2020 to October 2025
Monthly active users (MAU) growth linked to LinkedIn Games engagement strategies
Weekly summary for Business & Entrepreneurship

Business & Entrepreneurship

Top articles by AAII Impact Score (out of 30).

Browse the archive ›
No. 1 · Political Science & Public Administration

Exploring how AI will shape the future of work

Research Political Science & Public AdministrationEconomics & FinanceComputer ScienceEngineering Education & Leadership
· 12/01/2025
26/30 AAII Impact Score

AI Summary: Benjamin Manning, a PhD candidate at MIT Sloan School of Management, is researching the design and evaluation of AI agents that act on behalf of individuals, focusing on their impact on markets and institutions. His work aims to address critical questions regarding AI's role in decision-making and user preference understanding. Manning also explores the potential of AI to simulate human responses, which could significantly enhance social scientific research by allowing rapid prototyping of experimental designs. He envisions a future where AI accelerates the pace of understanding in economics, enabling researchers to concentrate on theoretical development and interpretation rather than computational tasks.

Topics: AI EthicsAI Decision-MakingUser Preference UnderstandingHuman Response Simulation
AI Rubric Scores
Research Relevance
5
Educational Value
4
Innovation/Novelty
5
Practical Impact
4
Interdisciplinary Potential
5
Ethical/Policy Implications
3
Read the full article ›
No. 2 · Computer Science 21/30

The State of AI: Welcome to the economic singularity

· 12/01/2025
Business Computer SciencePolitical Science & Public AdministrationEconomics & Finance

AI Summary: The article discusses the uneven adoption of generative AI across businesses, highlighting a stark contrast in its impact on productivity. While AI coding assistants have significantly transformed software development, with predictions that AI will soon generate a substantial portion of code at companies like Meta, many organizations report minimal returns on their generative AI investments. A study from MIT indicates that 95% of generative AI projects currently yield no return, fueling skepticism about the technology's long-term business impact. However, historical patterns suggest that transformative technologies often experience a lag in productivity gains as companies adapt their infrastructure and processes.

Topics: Generative AIAI Coding AssistantsProductivity Gains LagBusiness Impact Skepticism
AI Rubric Scores +
Research Relevance
3
Educational Value
4
Innovation/Novelty
3
Practical Impact
4
Interdisciplinary Potential
3
Ethical/Policy Implications
4
Read Full Article ›
No. 3 · Economics & Finance 20/30

Time Series and Trend Analysis Challenge Inspired by Real World Datasets

· 12/03/2025
Research Economics & FinanceMathematical SciencesComputer Science

AI Summary: The article presents an analysis of inflation expectations using three time series methods: moving averages, year-over-year changes, and Bollinger Bands, applied to the 5-year inflation data trend from October 2020 to October 2025. The analysis focuses on the 10-Year Breakeven Inflation Rate (T10YIE), which reflects market expectations for inflation over the next decade. Each method provides distinct insights: moving averages reveal trend direction, year-over-year changes indicate momentum shifts, and Bollinger Bands highlight periods of extreme movement. The dataset consists of 1,305 daily observations sourced from the Federal Reserve Economic Data (FRED).

Topics: Time Series AnalysisInflation Expectation ModelingBollinger Bands ApplicationMarket Trend Prediction
AI Rubric Scores +
Research Relevance
3
Educational Value
4
Innovation/Novelty
3
Practical Impact
4
Interdisciplinary Potential
4
Ethical/Policy Implications
2
Read Full Article ›
No. 4 · Computer Science 19/30

Here’s What You Should Know About Launching an AI Startup

· 12/05/2025
Business Computer ScienceMarketing, Management & Supply Chain

AI Summary: Julie Bornstein's AI startup, Daydream, aims to enhance personalized fashion shopping by matching customers with suitable garments using AI technology. Despite her extensive experience in digital commerce, Bornstein encountered significant challenges in translating AI capabilities into practical applications, particularly in understanding complex customer requests and ensuring model reliability. The startup has postponed its full launch to 2026 to refine its technology and team, focusing on the dual task of interpreting customer needs and aligning them with available products. Daydream's approach highlights the complexities of integrating AI into fashion retail, emphasizing the need for a nuanced understanding of both customer and merchant vocabularies.

Topics: Consumer AIPersonalized Fashion ShoppingCustomer Request InterpretationModel Reliability in Retail
AI Rubric Scores +
Research Relevance
2
Educational Value
3
Innovation/Novelty
3
Practical Impact
4
Interdisciplinary Potential
4
Ethical/Policy Implications
3
Read Full Article ›
No. 5 · Industrial, Manufacturing & Systems Engineering 17/30

Build and Deploy Your First Supply Chain App in 20 Minutes

· 12/04/2025
Applications Industrial, Manufacturing & Systems EngineeringComputer ScienceMarketing, Management & Supply Chain

AI Summary: The article discusses the transformation of a simulation model for inventory management from a Jupyter Notebook into a deployable web application using Streamlit. It emphasizes the importance of productizing analytics tools for supply chain professionals, enabling them to simulate various inventory management scenarios and assess the efficiency of existing ordering rules. The tutorial aims to guide users through the process of building and deploying their first application, providing insights into key parameters affecting inventory costs and stock availability. The author highlights the practical application of data science in addressing operational challenges within retail logistics.

Topics: Enterprise AIInventory Management SimulationWeb Application DeploymentData Science in Logistics
AI Rubric Scores +
Research Relevance
2
Educational Value
4
Innovation/Novelty
3
Practical Impact
4
Interdisciplinary Potential
3
Ethical/Policy Implications
1
Read Full Article ›
No. 6 · Marketing, Management & Supply Chain 15/30

A Product Data Scientist’s Take on LinkedIn Games After 500 Days of Play

· 12/05/2025
Business Marketing, Management & Supply ChainComputer Science

AI Summary: The article analyzes LinkedIn Games, highlighting their role in enhancing user engagement and retention on the platform. It posits that the primary goal of these games is to increase monthly active users (MAU) by fostering social interactions and reducing user churn. The author identifies two mechanisms through which LinkedIn Games achieve this: direct interactions through game-related posts that encourage user engagement and indirect engagement by creating a habit loop that prompts users to return to the platform. Overall, the analysis emphasizes the strategic importance of LinkedIn Games in supporting the platform's revenue-generating activities.

Topics: Consumer AIUser Engagement StrategiesHabit Formation MechanismsSocial Interaction Enhancement
AI Rubric Scores +
Research Relevance
2
Educational Value
3
Innovation/Novelty
2
Practical Impact
4
Interdisciplinary Potential
3
Ethical/Policy Implications
1
Read Full Article ›
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