Executives often ask: how many survey responses do we need before Customer AI works? The instinct is to think in percentages—“we need a 40% response rate”—as if more responses automatically equal b...

When companies struggle with Customer AI, they often blame messy operational data or siloed systems. In practice, the biggest failure point isn’t missing telemetry—it’s bad survey design. As explai...

Executives often describe data as if it’s clean, structured, and ready for analytics. Reality tells a different story. Studies show that 77% of organizations admit significant data quality problems...

In 2011, MIT researcher Erik Brynjolfsson and colleagues set out to answer a simple but critical question: does being data-driven actually pay off? Their survey of 179 large, publicly traded firms ...

Factories, equipment, and cash reserves have long been considered the core assets of business. But in the last decade, another asset has quietly overtaken them: data.

A 2011 MIT study showed that ...

Artificial intelligence didn’t rise in a straight line. Its history is a cycle of soaring optimism, disappointing results, and renewed breakthroughs. The downturns became known as AI winters—period...

The AI everyone talks about today—ChatGPT, Claude, Gemini—owes its existence to one breakthrough: the transformer architecture. Introduced in 2017, it reshaped natural language processing and launc...

On their own, each type of AI is powerful. But in Customer AI, the real breakthrough comes when generative, predictive, and prescriptive AI work as a system—a loop that turns fragmented data into g...

When people talk about AI in business, the conversation often drifts toward chatbots or large language models. Useful, but a narrow slice of the field. In Customer AI, three types of AI matter most...

If you want to understand customer loyalty, don’t just look at renewals or churn in year three. Look at the first 90 days. Early-life experiences set the tone for the entire relationship, and once ...