Anthropic recently published research showing that Claude behaves differently depending on the language you use. Not just translating differently. Actually expressing different values. In Arabic, Claude is warmer and more deferential. In English, it's more rigorous and cautious. In Russian, it challenges your assumptions more. When we read that, we had one question: does Kai do this too? So Jordan, our AI lead, analysed around 3,000 internal Kai sessions. The answer: yes.

Data is the key to actionable decision-making. In a fast-paced environment like sales, you’re surrounded by it. From gathering customer data to monitoring sales status to tracking goals, salespeople are constantly collecting and using data. However, the challenge with having all of this data at your fingertips is organizing it in a way that lends itself to analysis and action.

Living in South Florida, I've spent a lot of my career talking to customers about disaster recovery through the lens of hurricanes. Those conversations are easy because everyone understands the threat. We can watch a storm develop for days. Weather stations track every shift in direction. Data centers activate contingency plans. Business continuity teams prepare for impact.

The AI-analytics category has one operating assumption: AI’s job is to do more of what humans currently do. Adoption is measured by delegation surface. Success is when AI takes the whole task. Ask the executives running AI daily what they refuse to delegate, and you get a different story. Actually, you get the same story, from operators who do not know each other, running different companies, across different functions.

Most data stacks weren’t built for AI agents. Take the ODI Assessment to find out if yours is ready.

For years, the mandate for System Integrators (SIs) was clear: lead the "cloud-first" migration. The promise was lower costs, greater agility, and seamless innovation. But for many enterprise customers, that promise remains unfulfilled. Instead of agility, organizations have inherited a complex, fragmented data estate. Data is siloed across on-premises legacy systems and multiple public clouds, creating governance headaches and inflating infrastructure costs.