The Work We're Losing
The companies effectively using AI aren't automating everything—they're strategically preserving the expertise-building work that creates competitive advantage when technology inevitably fails.
Why AI Projects Fail: The Human Factors Analysis
Most AI implementations fail not because the technology doesn't work, but because organizations treat them as technology projects instead of people projects. This analysis reveals the four human factors that destroy 80% of AI initiatives.
The Design Problem We Call User Resistance
Recent research analyzing 63 studies reveals that what we call "user resistance" to technology isn't about fear of change—it's valuable feedback about design failures that make work harder, strip away meaningful judgment, ignore human workflows, and break essential collaboration.
Beyond ChatGPT: How Specialized AI Models Change the Economics of Business Automation
Successful AI implementation isn't about choosing the most advanced technology—it's about matching tools to actual business needs through systematic experimentation and optimization.
The False Promise of AI Deregulation
The House's proposed decade-long ban on state AI regulation creates a dangerous oversight vacuum just when we need thoughtful rules to ensure AI systems serve human needs rather than exploit our vulnerabilities.
