automation

Building Pro-worker AI

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Brookings identifies AI's potential to enhance worker capabilities through pro-worker technologies, categorizing them into five types: labor-augmenting, capital-augmenting, automating, expertise-leveling, and new task-creating technologies. While new task-creating tech is clearly beneficial for workers, automating tech is not. Pro-worker AI is underdeveloped due to firms prioritizing automation for economic returns. To promote pro-worker AI, policies should focus on health care and education, foster competition, encourage worker input, and create a supportive legal environment for worker ownership of skills.

https://www.brookings.edu/articles/building-pro-worker-ai/

Half the AI Agent Market Is One Category the Rest Is Wide Open

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Software engineering comprises nearly 50% of AI agent tool usage, while healthcare, legal, and other sectors each hold less than 5%, indicating vast untapped opportunities. Despite AI's capability to perform efficiently, user trust limits its deployment. Founders should focus on vertical-specific AI solutions, capitalizing on unique workflows and driving change management to unlock growth potential. There are approximately 300 vertical AI unicorns waiting to be created across various industries.

https://garryslist.org/posts/half-the-ai-agent-market-is-one-category-the-rest-is-wide-open

Taming Agent Sprawl: 3 Pillars of AI Orchestration

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Focusing on managing AI agent sprawl, the article outlines the need for orchestration to prevent conflicting actions among AI agents. Key pillars for effective orchestration include conflict resolution, universal context, and cross-agent security. The proposed MAESTRO framework provides steps to establish centralized governance for AI operations, ensuring efficiency and reducing costs related to redundant tasks. Organizations without orchestration will face budget overruns due to uncoordinated AI agents.

https://www.cio.com/article/4132287/taming-agent-sprawl-3-pillars-of-ai-orchestration.html

AI Coding Tools for Knowledge Work: What Executives Need to Know

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AI coding tools like Claude Code enhance knowledge work beyond simple chatbots. They automate repetitive tasks, improve documentation workflows, and support team collaboration efficiently. Unlike traditional chatbots, these tools can read and edit files directly, enable repeatable processes, and execute multiple tasks simultaneously. They provide a form of “memory,” allowing users to refine instructions for future use. While there are risks involved, such as potential inaccuracies and security concerns, executives should swiftly adopt these tools to boost productivity.

https://sloanreview.mit.edu/article/ai-coding-tools-for-knowledge-work-what-executives-need-to-know/

The Agentic Commerce Revolution

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O'Reilly discusses the shift in digital commerce towards agentic AI, which is unbundling traditional processes like discovery, comparison, and checkout, leading to challenges in accountability and trust in payment systems. Two philosophies emerge: 1) Conversational Checkout prioritizes immediate convenience, allowing seamless purchases through AI without user intervention, but is limited to simple tasks. 2) Autonomous Trust Layer focuses on verification and security, using protocols and mandates for complex, high-stakes transactions, reliant on user trust and authorization. This shift has significant implications for data ownership and customer relationships in e-commerce.

https://www.oreilly.com/radar/the-agentic-commerce-revolution/

How One CIO Focuses on Small Wins to Shape AI Adoption

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CIO Matt Price of Gold Bond Inc. emphasizes focusing on small, targeted AI use cases for effective adoption. After enhancing employee training on AI tools like Gemini, their use soared, helping automate tasks like categorizing customer art orders and managing invoices. Upcoming plans include integrating an AI voice agent for customer support. Price advises other businesses to pursue specific use cases to achieve small wins and improve efficiency. Proper governance and training are crucial as various departments adopt AI, considering data access and security.

https://www.ciodive.com/news/gold-bond-focuses-small-wins-ai-adoption/811159/

Two Kinds of AI Users Are Emerging. The Gap Between Them Is Astonishing.

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AI users split into two types: “power users” leveraging advanced AI tools for productivity, often non-technical, and casual users sticking to basic interactions with AI. Microsoft Copilot is criticized for underperformance in enterprise settings, limiting true AI potential. Enterprises face risks due to rigid IT policies that hinder innovation and AI adoption. Smaller companies, unhindered by legacy systems, often experience greater productivity gains with AI. The future suggests successful workflows will emerge from bottom-up initiatives, emphasizing the necessity of user-friendly APIs and secure access to AI tools.

https://martinalderson.com/posts/two-kinds-of-ai-users-are-emerging/

Stop Managing Your AI ‘workforce’, Start Allocating AI Capabilities

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The rise of AI agents capable of complex workflows presents a pivotal moment for organizations. While many view these agents as digital co-workers, this framing limits their potential. Instead, organizations should focus on how these capabilities can reshape workflows and decision-making structures, leading to greater productivity and competitive advantage.

https://www.kyndryl.com/us/en/institute/2026/01/ai-workforce

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