AI resources update: 1. The AI Agent Index | 2. Advances and challenges in foundation agents

This article is part of an ongoing series looking at AI in KM, and KM in AI.

This AI resources update presents two key resources offering significant insights into the rapidly emerging field of artificial intelligence (AI) agents:

1. The AI Agent Index.
2. Advances and Challenges in Foundation Agents book.

1. The AI Agent Index

Published in February 2026, The 2025 AI Agent Index documents the origins, design, capabilities, ecosystem, and safety features of 30 prominent AI agents based on publicly available information and correspondence with developers. As shown in the following figure from the Index, 2025 has seen a sharp increase in interest in AI agents.

Key findings from the The 2025 AI Agent Index include:

• Rapid Deployment – 24 / 30 agents launched or received major agentic updates in 2024-2025, with releases accelerating sharply. Autonomy levels are rising in parallel.
• Autonomy Split – Chat agents maintain lower autonomy (Level 1-3), browser agents operate at Level 4-5 with limited intervention, and enterprise agents move from Level 1-2 in design to Level 3-5 when deployed.
• Transparency Gap – Of the 13 agents exhibiting frontier levels of autonomy, only 4 disclose any agentic safety evaluations. Developers share far more information about capabilities than safety practices.
• Foundation Model Concentration – Almost all agents depend on GPT, Claude, or Gemini model families, creating structural dependencies across the ecosystem.
• No Standards – There are no established standards for how agents should behave on the web. Some agents are explicitly designed to bypass anti-bot protections and mimic human browsing.
• Geographic Divergence – Agent development concentrates in the US (21/30) and China (5/30), with markedly different approaches to safety frameworks and compliance documentation.

With thanks to Peter Slattery, PhD on LinkedIn.

2. Advances and Challenges in Foundation Agents book

With more than 1,600 references, the academic book Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems provides a comprehensive overview of AI agents. It frames intelligent agents within modular, brain-inspired architectures that integrate principles from cognitive science, neuroscience, and computational research. The exploration is structured into four interconnected parts:

1. First, a systematic investigation of the modular foundation of intelligent agents, systematically mapping their cognitive, perceptual, and operational modules onto analogous human brain functionalities and elucidating core components such as memory, world modeling, reward processing, goal, and emotion.
2. Second, a discussion of self-enhancement and adaptive evolution mechanisms, exploring how agents autonomously refine their capabilities, adapt to dynamic environments, and achieve continual learning through automated optimization paradigms.
3. Third, an examination of collaborative and evolutionary multi-agent systems, investigating the collective intelligence emerging from agent interactions, cooperation, and societal structures, highlighting parallels to human social dynamics.
4. Finally, addressing the critical imperative of building safe and beneficial AI systems, emphasizing intrinsic and extrinsic security threats, ethical alignment, robustness, and practical mitigation strategies necessary for trustworthy real-world deployment.

By synthesizing modular AI architectures with insights from different disciplines, this book identifies key research gaps, challenges, and opportunities, encouraging innovations that harmonize technological advancement with meaningful societal benefit.

Editor’s note: We had been serialising this significant book in RealKM Magazine, but have unfortunately been unable to continue this due to reduced resourcing.

Header image source: Created by Bruce Boyes with Microsoft Designer Image Creator.