Confident Nonsense: Garbage In, Polished Garbage Out

AI doesn’t correct bad data. It does produce confident output built on
whatever you feed it. Because of this, most “AI failures” are actually
upstream data governance failures hiding behind polished outputs. Leaders
should treat data readiness as a product, with clear owners, thresholds,
and controls that prevent confident nonsense from scaling.

Technology Companies Are Slow to Understand Physical Industries

There’s a narrative in tech that construction, manufacturing, and energy companies are resistant to change. I’ve spent 26 years in this space, and I think that narrative is backwards. 

The real problem? Technology companies are slow to understand physical industries. That realization shaped everything about how we built Briq. Here’s what we learned.

A Look Forward to 2026, Part 3:  Why Humanity Wins in the Age of AI

As we enter 2026, the omnipresence of artificial intelligence will continue to transform it from a cutting-edge advantage into a mere operational baseline. As every competitor integrates the same autonomous agents, generative tools, and optimization engines, the race for the “fastest algorithm” will become irrelevant. Industry leaders agree: the brands poised to win in this saturated environment will bypass the technology arms race entirely. 

Expert Mode:  Democratizing AI: How UserTesting Empowers Every Employee to Drive Innovation

The integration of artificial intelligence into business operations is no longer a futuristic vision but a present reality.  However, the true potential of AI lies not just in its adoption, but in its democratization within an organization. Empowering every employee, regardless of their technical expertise, to leverage AI can unlock unprecedented levels of innovation and efficiency. 

Expert Mode: Why Your Marketing Cloud Might Be Confusing Your AI

For years, enterprise marketing leaders have been engaged in a monumental construction project. With blueprints drawn up by the major marketing clouds and materials sourced from an ever-expanding MarTech landscape, you’ve meticulously built intricate technology stacks. The goal has always been the same: a unified, intelligent system capable of delivering personalized customer experiences at scale. Millions of dollars and countless hours have been invested in this pursuit. We’ve all seen the diagrams, marvelled at their complexity, and worked tirelessly to integrate the disparate pieces.

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