Industry
AI applications across education, healthcare, finance, government, and other verticals.
AI is transforming every industry—from education and healthcare to finance and government. Explore how organizations across verticals are deploying AI agents, LLM-powered workflows, and intelligent automation to solve sector-specific challenges and deliver measurable outcomes.
718 articles in this category
Google: From Data to Discovery – AI's Role in Higher Education
Google outlines a roadmap for higher education to harness AI through better data management, overcoming challenges like dark and siloed data, enhancing data literacy, and using strategic partnerships and tools for improved decision-making and student outcomes.
Udacity: 2025 State of AI at Work
Udacity's 2025 State of AI at Work report reveals a major skills gap in AI training across industries, with only one-third of workers receiving adequate resources. The report, drawing on responses from 850 professionals in 87 countries, finds that while millennials view AI as a tool for efficiency and revenue growth, this positive sentiment is less shared by Gen Z and Gen X. Popular AI tools include writing assistants and image generators, underscoring the need for enhanced AI training and data literacy.
Google: How AI is Building the Campus of Tomorrow
The content highlights how higher education institutions are integrating generative AI to tackle challenges like declining enrollment and budget constraints while enhancing personalized learning, research, and administrative efficiency.
U.S. Department of Education: Navigating AI in Postsecondary Education – Building Capacity for the Road Ahead
The document outlines guidance from the U.S. Department of Education on integrating AI into postsecondary education by emphasizing ethical practices, transparency, AI literacy, collaborative partnerships, and continuous evaluation to improve both academic and institutional outcomes.
World Economic Forum: 2025 Future of Jobs Report
The report outlines how macrotrends like technological change, the green transition, geoeconomic shifts, economic uncertainty, and demographic changes will reshape global labor markets by 2030, emphasizing significant job growth alongside a critical need for extensive reskilling and upskilling to bridge emerging skills gaps.
George Mason University: Artificial Intelligence Policy Framework for Institutions
The paper proposes an ethical AI policy framework for institutions that focuses on data privacy, bias mitigation, energy efficiency, and the importance of interpretability to build trust, illustrated through case studies in various sectors including education and healthcare.
U.S. Congressional Budget Office: AI and Its Potential Effects on the Economy and the Federal Budget
The report examines how artificial intelligence could boost economic growth and transform federal revenues and spending, while also highlighting uncertainties about its impacts on employment, wages, and the timing and scale of these effects.
Australian Government: Voluntary AI Safety Standard
The Australian Government’s Voluntary AI Safety Standard outlines ten guardrails for implementing safe and responsible AI practices, focusing on aspects like accountability, risk management, and transparency in line with ethical and international standards.
University of Chicago: Agentic Systems – A Guide to Transforming Industries with Vertical AI Agents
The content explains agentic systems—industry-specific AI agents powered by large language models—that offer real-time adaptability, domain expertise, and complete workflow automation through components like memory, reasoning engines, and cognitive modules.
Swiss Business School: AI's Impact on Critical Thinking
The study finds that frequent use of AI tools is negatively associated with critical thinking skills, suggesting that while AI has benefits, there is a need for educational strategies to counteract cognitive offloading and maintain robust critical thinking abilities.
UNESCO: Guidance for Generative AI in Education and Research
UNESCO's guidance outlines ethical and responsible use of generative AI in education and research, addressing potential biases, copyright issues, and digital inequalities, while recommending human-centered strategies and regulatory measures for its integration and competency development.
Cambridge: How Educators Can Help Future Learners Outwit the Robots
Professor Rose Luckin's keynote at the Cambridge Summit emphasizes that while AI can transform education, nurturing uniquely human skills such as social intelligence and meta-cognition is crucial, and ethical, collaborative development between educators and AI developers is essential for future learning.
Deloitte: Powering Artificial Intelligence – A Study of AI's Environmental Footprint, Today and Tomorrow
Deloitte's report assesses AI's growing environmental impact, noting that data center energy use may nearly triple by 2030 due to AI demands. It advocates for strategies like renewable energy adoption, improved efficiency, ecosystem collaboration, and greater transparency to achieve "Green AI" and calls for joint action from industry and policymakers to ensure a sustainable future.
Google: LearnLM – Improving Gemini for Learning
LearnLM is a Google AI model designed for educational settings that follows detailed pedagogical instructions to improve teaching effectiveness. Human evaluations show it outperforms existing models in various learning scenarios, and future work will explore additional educational applications.
University of Michigan: Artificial Intelligence Research Committee Recommendations Report
The report recommends significant investments in computing, personnel, and ethical oversight to boost U-M's AI capabilities, advocating for better internal coordination, a centralized AI resource hub, and enhanced national and industry collaborations.
Hangzhou Normal University: Does ChatGPT Enhance Student Learning? A Systematic Review and Meta-Analysis of Experimental Studies
This review of 69 experimental studies found that ChatGPT interventions improved students' academic performance, affective motivation, and higher-order thinking while reducing mental effort, though it had no significant effect on self-efficacy and many studies had methodological limitations.
George Washington University Law School: Artificial Intelligence and Privacy
Daniel J. Solove’s piece argues that current privacy laws—focused mainly on individual control—are inadequate for addressing the systemic harms posed by AI, and calls for a regulatory framework based on harm analysis and structural reforms.
U.S. House of Representatives: Bipartisan House Task Force Report on Artificial Intelligence
A bipartisan House task force report assesses the impact of AI on privacy, national security, society, and the economy, while offering recommendations for responsible development and regulation.
Anthropic: The Dawn of GUI Agent – A Preliminary Case Study with Claude 3.5 Computer Use
This study evaluates Claude 3.5 Computer Use—a novel AI model that interacts with GUIs via API—to understand its capabilities and limitations in executing tasks across various software, guiding future improvements in GUI automation.
Google DeepMind: A New Golden Age of Discovery
AI is transforming scientific research by accelerating key areas like knowledge synthesis and experimental simulation, while also requiring careful strategies, investments, and policies to manage risks and ensure sustainable, equitable innovation.
Google DeepMind: New Golden Age of Discovery
AI is transforming scientific research by accelerating key areas like knowledge synthesis, data management, simulation, and complex modeling, while urging strategic investments and interdisciplinary collaboration to harness its benefits and address potential risks.
National Academies: Artificial Intelligence and the Future of Work
The report examines how AI, particularly large language models, could boost productivity and reshape job markets by creating new roles and displacing existing ones, while emphasizing the need for investments in skills, infrastructure, ethical oversight, improved data collection, and lifelong learning.