AI Agents
Building, deploying, and managing autonomous AI agents for workflow automation, customer support, internal operations, and more.
AI agents represent the next evolution in enterprise automation—intelligent systems that can reason, plan, and take action autonomously. Unlike simple chatbots, AI agents handle complex multi-step tasks across customer support, internal operations, data analysis, and specialized workflows. Discover how agentic AI is transforming how organizations operate.
524 articles in this category
How ibl.ai Integrates with Google Gemini: Technical Capabilities and Value for Higher Education
ibl.ai’s Gemini guide shows campuses how to deploy Gemini 1.5 Pro/Flash and upcoming 2.x models through Vertex AI, keeping their own API keys and quotas. Its middleware injects course prompts, supports multimodal and function calls, and dashboards track token spend, latency, and compliance—letting admins toggle Flash for routine chat and Pro for deep research.
How ibl.ai Integrates with OpenAI: A Guide to Model Options and Deployment Flexibility
ibl.ai’s guide walks campuses through plugging any GPT model—using a self-managed key or private Azure cluster—while keeping data FERPA-safe. Its middleware routes prompts, logs and meters token spend, and unlocks embeddings, Whisper, and DALL·E upgrades without changing course code.
ChatGPT and ibl.ai: Partners in AI-Enhanced Higher Education
Pair ChatGPT’s conversational AI with ibl.ai backend to combine language brilliance with campus-grade governance, integrations, and analytics—real-world deployments prove the duo cuts costs, boosts faculty control, and delights students without vendor lock-in.
Google: Agents Companion
The document "Agents Companion" outlines advancements in generative AI agents, detailing an architecture that goes beyond traditional language models by integrating models, tools, and orchestration. It emphasizes the importance of Agent Ops—combining DevOps and MLOps principles—with rigorous automated and human-in-the-loop evaluation metrics and showcases the benefits of multi-agent systems for handling complex tasks.
Bain & Company: Nvidia GTC 2025 – AI Matures into Enterprise Infrastructure
Nvidia's GTC 2025 shows that AI has moved from experimental projects to a core element of enterprise infrastructure. Companies are shifting focus to clean, connected data while using AI not only to analyze but also to generate insights. Smaller, specialized AI models, along with semi-autonomous systems with human oversight, are becoming standard. Additionally, tools like digital twins and simulation platforms are being widely adopted to enhance decision-making and cross-functional collaboration.
National Security: Superintelligence Strategy
The document proposes a national security strategy for advanced AI that leverages deterrence through Mutual Assured AI Malfunction (MAIM), nonproliferation via tight controls on AI technology and information, and competitiveness by boosting domestic capabilities and legal frameworks—all aimed at mitigating the risks of superintelligence while maintaining global strategic balance.
PWC: Agentic AI – An Executive Playbook
Agentic AI leverages autonomous, human-like reasoning to optimize workflows and drive business growth by reducing costs, improving customer experience, and enhancing decision-making. It requires strategic planning, robust infrastructure, and ethical guidelines, and has evolved through advances in machine learning, NLP, and multimodal data integration.
MIT: The AI Agent Index
The MIT AI Agent Index is a public database that catalogs agentic AI systems—tools capable of planning and executing tasks with minimal human oversight—by detailing their technical components, applications, and risk management practices. It reveals that most systems are developed in the USA, mainly by companies in software engineering, and while many projects offer open code and documentation, information on safety policies and external evaluations remains limited.
Hugging Face: Fully Autonomous AI Agents Should Not Be Developed
The paper argues that fully autonomous AI agents, which operate without human oversight, pose serious risks to safety, security, and privacy. It recommends favoring semi-autonomous systems with maintained human control to balance potential benefits like efficiency and assistance against vulnerabilities in accuracy, consistency, and overall risk.
University of Memphis: Generative AI in Education – From AutoTutor to the Socratic Playground
The research paper explores how generative AI and large language models can transform education through advanced tutoring systems like the Socratic Playground, emphasizing a pedagogy-first approach, human oversight, and adaptable, interactive learning methods that enhance critical thinking and understanding.
Google: AI Business Trends 2025
Google's AI Business Trends 2025 report identifies five transformative trends: multimodal AI, AI agents, assistive search, AI-powered customer experience, and security with AI. These trends are driving market growth and innovation, enhancing integration of diverse data, automating business workflows, improving information discovery, personalizing customer interactions, and strengthening security practices.
Deloitte: The Cognitive Leap – How to Reimagine Work with AI Agents
The white paper advocates for using multiagent AI systems to transform business processes through scalable, human-in-the-loop designs, supported by industry examples and a detailed implementation framework.
IBM: Enterprise AI Development – Obstacles and Opportunities
A survey of 1,063 US enterprise AI developers revealed significant skills gaps—especially in generative AI—and challenges from a lack of standardized processes and trusted, easy-to-integrate tools, with ongoing concerns about AI agents’ trustworthiness and compliance.
O'Reilly: Technology Trends for 2025
The report analyzes O'Reilly's usage data to predict that in 2025, AI and its associated skills will drive major trends, with a shift in software development focus toward AI integration, increased attention to security, and new platform features like badging and a generative AI Q&A tool.
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.
Google: Agents – Architecture, Tools, and Applications
Generative AI agents extend language models by using external tools and orchestrated reasoning frameworks like ReAct and Chain-of-Thought, with practical implementations shown through examples such as LangChain and Vertex AI.
World Economic Forum: Navigating the AI Frontier – A Primer on the Evolution and Impact of AI Agents
This white paper examines the evolution of AI agents—from simple rule-based systems to advanced models capable of complex decision-making—and discusses their benefits, risks, and the critical need for robust ethical and governance frameworks to manage their growing role in society.
Capgemini: Harnessing the Value of Generative AI - 2nd Edition: Top Use Cases Across Sectors
Capgemini’s report examines the widespread adoption of generative AI across industries, highlighting increased investments, improved productivity, and enhanced customer satisfaction. It emphasizes the growing role of AI agents, the need for strong governance, and addresses ethical and environmental concerns based on insights from a global survey of 1,100 executives.
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.