Microsoft’s Work Trend Index report shows a productivity crisis.

Employees are interrupted every 2 minutes—275 times per day from meetings, emails, and chats. Meanwhile, 80% of workers report lacking the time or energy to do their jobs. Yet 53% of leaders say productivity must increase.

Most companies are trying to speed up the same broken processes. They’re adding AI tools to write emails faster and run meetings more efficiently. But that doesn’t solve the fundamental problem.

The breakthrough isn’t working faster. It’s working differently, reimagining workflows and guiding AI as a teammate.

The report found companies that work this way see dramatically different results. 71% of their workers say their company is thriving, compared to just 37% globally.

These teams aren’t automating chaos. They’ve started redesigning how work flows around outcomes instead of departments.

This Thu (May 29), I’m highlighting in my newsletter two real-life use cases of companies making this transformation and the results they’re seeing. Subscribe here to the Practical AI in GTM newsletter: https://lnkd.in/eg48-RXp

UPDATE (May 29): Here’s are the real-life case studies in this newsletter, https://lnkd.in/g7uwZKtZ

See the link to the 2025 Microsoft Work Trend Index report in the comments.

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I brought AI to the nursery because plants and I have a complicated relationship. I love them. They don’t usually love me back as much.

Here’s what I did:

• Used ChatGPT’s live video mode to pan over flowers and asked which would thrive in my northwest-facing area with hanging clay pots that gets 6-8 hours of sun but is protected under the pergola.

• Uploaded photos of several varieties I liked and asked for a detailed table breaking down the following for each plant: sun/water needs, height/width, temp hardiness, fertilizer requirements, bloom time, deadheading needs, etc.

I loved this. Everything in one table!

• Asked which ones would work best in my specific setups like my DIY gutter planter that’s in the shade and a small picture frame planter that’s more exposed.

This is next-level research. Very different consumer behavior. I didn’t need to know the right keywords or translate my needs into search terms. I just showed or told AI my actual situation and let it figure out the connections.

Before AI, I had to read every single plant label and do endless (traditional) Google searches and click on various blue links. Now I just video the flowers and upload photos of what catches my eye.

I now get a custom analysis and recommendations. Just me, my iPhone, AI, and what turned out to be some gorgeous flowers.

Will everything survive the summer? We’ll find out. I did overrule some of AI’s recommendations, so we’ll see how that goes. But my old approach wasn’t foolproof either.

Interestingly, I’m already seeing new work applications from this experience. Many of my work AI use cases were inspired by personal AI experiments.

Sometimes the best learning happens when you’re just trying to keep something beautiful alive.

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