Botsitting, AI Outputs, Prioritization, Harvesting Thoughts, and Wi-Fi
Your Weekly Review of News in Technology, UX and AI
This week's issue is about the gap between AI activity and AI value. OpenAI's own research finds no statistical link between how much a company uses ChatGPT and its revenue per employee. Fortune's Stephen Messer argues most companies are doing an “AI Shuffle” while HBR quantifies the hidden cost of that gap with “botsitting.” And on the UX side, NN/g's new piece makes the same point at the individual level: one AI output is an example, not an evaluation. The theme: usage isn't the same as value, and most organizations (and most of us individually) don't yet have a rigorous way to tell the difference.
Let’s dive into the latest news, resources, and use cases from the world of product, UX, AI and technology:
📊 Product-Market Fit
💵 AI Revenue per Employee
🕺 AI Shuffle
👶 Botsitting
🤖 AI Output
☑️ Prioritization
💭 Harvesting Thoughts
🛜 Wi-Fi
Podcast
Finding Product-Market Fit with Ken Gavranovic
Discover how seasoned technology executive Ken Gavranovic shares insights on building innovative products, leading digital transformation, and harnessing AI to drive business growth. Whether you’re an aspiring entrepreneur or a product leader, learn practical strategies to navigate and excel in the tech landscape.
News and Useful Reads
Buried in OpenAI’s latest research: No correlation between AI use and revenue per employee
AI usage continues to expand rapidly, as well as the money flowing into AI and AI companies. But as companies are spending more in AI, that isn’t translating to more revenue generated per employee.
In one small table on page 35, the researchers report no statistically significant correlation between the revenue per employee, and how much those employees use AI, measured in messages sent and tokens used.
“Revenue per employee is not meaningfully associated with output tokens per employee or messages per active user once other controls are included,” the report explains.
AI isn’t changing how companies work. It’s changing what a company is
Adding AI without changing the underlying structure of how we work isn’t transformation, it’s just adding tools.
I have called this the “AI Shuffle”: the corporate habit of exchanging one technology logo for another while preserving every underlying assumption about how work gets done. It feels like progress because it generates activity. It does not produce an advantage.
How Much Time Do Your Employees Spend Botsitting?
Do you find yourself spending more and more time managing the technology that is meant to save you time on other tasks? If so, you’re not alone.
AI promises to reduce workloads and improve organizational performance, but its benefits often come with a hidden cost: “botsitting,” the work employees do to make AI useful, from supplying context and checking outputs to correcting errors. Research shows that workers spend nearly a day a week on these tasks.
One AI Output Is an Example, Not an Evaluation
Too often, we’re treating AI outputs as the final word (or document or presentation). The reality is that we should be treating them as an example or an input into our work.
One output cannot establish how well an AI system performs. Evaluate with multiple representative inputs, repeated runs, and confidence intervals.
Why product prioritization frameworks can miss user harm
Are you considering the potential harm your product or feature might do (or be used for)? Most of us probably aren’t, but it’s something we shouldn’t overlook.
These frameworks can accommodate risk, but they don’t require you to account for serious harm that affects only a small group of users. You still have to identify that harm and express it as value, urgency, or necessity before the framework can account for it.
Big Tech Wants to Harvest Your Thoughts
Being able to read thoughts was once the realm of science fiction. But it’s quickly becoming reality. And the ability to control them may not be far off either…
The mining of brain data has already begun, and prospectors are ranging hungrily across the landscapes of the mind.
Other Interesting Finds
Ordinary WiFi can now identify you with near-perfect accuracy
Well, this doesn’t sound dystopian at all…
Ordinary WiFi networks could quietly become powerful surveillance tools, allowing people to be identified without cameras, special sensors, or even carrying a connected device. Researchers showed that unencrypted signals routinely exchanged between WiFi devices and routers can be used to create radio-based images of people and recognize them within seconds. In tests involving 197 participants, the system identified individuals with nearly 100% accuracy, even from different angles and regardless of how they walked.