Category: AI Research
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5 Ways AI Agents Will Change Your Business in 2026
Google’s 2026 AI Agent Trends highlights a shift towards practical AI agent applications in the workplace. Organizations are leveraging these agents for routine tasks, enhancing productivity and customer experience. Key recommendations include defining clear workflows, measuring performance, training staff, and ensuring security. The focus is on creating an AI-ready workforce for sustained success.
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The 10 Day Small Model Sprint, Turn Your Own Data Into Faster Answers
Last week we covered PayPal’s key move, put a smaller, fine tuned model into the Search and Discovery step to cut response time and operating cost, while keeping quality competitive on everyday questions (Sahami et al., 2025). This week we turn that insight into a practical sprint you can actually run, no data science department…
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Agentic Commerce, But Fast: What PayPal’s New Research Means for Your Business
PayPal’s research reveals that employing a smaller, fine-tuned AI model in their search functionality leads to faster responses and reduced computing costs, enhancing customer experience. This strategy allows for quicker and more relevant replies, crucial for retaining users. It also enables businesses to deploy AI across more platforms effectively.
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The Hidden AI Impact on White-Collar Jobs
MIT’s Iceberg Index reveals that AI’s impact on white-collar jobs—particularly in administrative and professional services—exposes 11.7% of the workforce, significantly higher than in tech roles. This underlines the need for businesses to adapt workflows and for workers to prioritize tasks complemented by human creativity and judgment over routine tasks vulnerable to automation.
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The Tip of the Iceberg: Why Visible AI Adoption Is Only 2.2% of the Real Story
The post highlights the misconception that AI’s impact is predominantly visible, focusing on tech job losses and automation. In reality, MIT’s Iceberg Index reveals that 98% of AI’s potential effects remain concealed across diverse occupations. Businesses should prioritize understanding hidden skills and tasks for proactive adaptation, rather than reacting to surface-level changes.
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The Iceberg Index: The New Way MIT Researchers Measure Workforce Exposure in the AI Economy
MIT’s Iceberg Index offers a fresh perspective on AI and job automation by measuring job skill exposure rather than predicting job loss. It reveals significant hidden vulnerabilities in various sectors, emphasizing the need for proactive preparation and reskilling in workplaces. Understanding task-level exposure will help businesses and workers adapt effectively to AI advancements.