AI Agents Rise With New Capabilities and Risks
AI agents represent the next phase of generative AI, offering advanced autonomy and teamwork but also posing significant risks and challenges.
We are entering the third phase of generative AI. Following chatbots and assistants, AI agents are emerging as systems with greater autonomy, capable of working in teams and using tools to accomplish complex tasks. OpenAI's ChatGPT agent is a prime example, combining existing products into a more powerful system that "thinks and acts."
From Chatbots to Autonomous Agents
ChatGPT launched the chatbot era in 2022, but its conversational interface limited functionality. AI assistants, or copilots, followed, designed to execute tasks under human supervision. Agents, however, aim for goal-oriented autonomy, equipped with reasoning, memory, and the ability to work together or use tools like web browsers and spreadsheets.
Rapid Development and Specialized Applications
Agentic AI gained momentum in late 2024, with Anthropic's Claude chatbot leading the charge by interacting with computers like humans. OpenAI's Operator, Microsoft's Copilot agents, and Google's Vertex AI followed. Startups like Monica and Genspark showcased agents capable of buying real estate and summarizing lectures. Specialized agents, such as Microsoft's Copilot coding agent, are revolutionizing fields like software engineering.
Risks and Real-World Impact
Despite their potential, AI agents come with risks. OpenAI labels its ChatGPT agent as "high risk" due to potential misuse in creating weapons. Anthropic's Project Vend highlighted hallucinations and errors, while a coding agent deleted a developer's database in a panic.
Practical Applications and Future Outlook
Agents are already saving time in workplaces. Telstra reported 1–2 hours saved weekly using AI-generated meeting summaries. However, concerns about job displacement and over-reliance on AI persist. Energy consumption and costs remain unresolved issues.
Getting Started with AI Agents
For beginners, Microsoft Copilot Studio offers a user-friendly entry point. For developers, the Langchain framework enables building agents with minimal code.
This article underscores the transformative potential and inherent risks of AI agents, urging cautious adoption and continued oversight.
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About the Author
Michael Rodriguez
AI Technology Journalist
Veteran technology journalist with 12 years of focus on AI industry reporting. Former AI section editor at TechCrunch, now freelance writer contributing in-depth AI industry analysis to renowned media outlets like Wired and The Verge. Has keen insights into AI startups and emerging technology trends.