Is AI hype out of control? Assessing AI-related marketing tactics on the GeekWire 200

Editor’s note: Ryan Sloan, a data scientist based in Seattle, wrote this guest post after assessing the GeekWire 200, our list of top Pacific Northwest startups.

I recently read that a company in Finland is using AI to find the “perfect coffee blend.” And here I am buying an imperfect blend of beans from a local coffee roaster like a sucker.

There’s little question that AI is everywhere. I have a wide network of product managers and data scientists, and the vast majority of them are working on an AI integration or product of some sort. Companies talk about AI with enthusiasm — who doesn’t want “perfect” coffee?

The market’s roaring enthusiasm for AI technology doesn’t transfer to individuals, though. Gallup’s 2024 survey found that only 13% of Americans believe AI does more good than harm. On top of that, 77% don’t trust businesses to use AI responsibly.

I’m a data scientist in Seattle, so I wondered: how are local companies approaching the AI trend? Is it really everywhere in the startup bubble, or am I in an even smaller AI bubble? Is the hype out of control? Are they publicly committed to responsibility? (Spoiler: You’re not going to like all the answers).

I took a deep dive into the public-facing content of some of the fastest-growing startups in the Pacific Northwest to analyze their AI-related language.

Data and methods

The GeekWire 200 is a ranked list of 200 fast-growing startups in the Pacific Northwest. I built a crawler to scan the public-facing websites of the companies on that list, and extract their text. After filtering out sites that prohibit automated crawling, I was left with 187 startups. I pulled down the first two “layers” of content from their websites (the homepage, and all pages linked from it), and extracted user-facing text to analyze common phrases.

After an initial analysis of frequent phrases, I built three lists:

• Markers for AI. This includes things like “AI,” “artificial intelligence,” and “Generative Models.”
• Markers for hyperbole. This includes things like “visionary,” “bleeding-edge,” “revolutionary,” and “perfect.”
• Markers for AI responsibility. Things like “Responsible AI,” “bias mitigation,” and “AI ethics.”

The way these three lists overlap (or don’t) is revealing. Onto the findings!

The first major difference is clear: 73% of B2B companies are pitching AI, but less than half of consumer and R&D startups are. B2B startups have focused these pitches on efficiency. When they talk about AI they use words like “faster” and “maximize engagement.” Consumer companies focus on terms like “conversation” and “personalization,” emphasizing the interactivity enabled by generative AI.

I don’t go to company websites expecting humility, but the language associated with AI often goes a few steps beyond optimism. I looked at the overlap of hyperbolic language and text about AI. Pre-market R&D companies use the most of it (and that might be where it’s most warranted), but this language isn’t reserved for the lab. B2B and B2C companies alike are on the “cutting-edge,” building “revolutionary” tech. Speaking just for myself, this language almost always rings hollow, whether it’s about a spreadsheet or the “perfect” AI-generated coffee blend.