
Salesforce's AI Problem Is Everyone's AI Problem
The CRM giant's lukewarm outlook tells us something uncomfortable about where enterprise software meets automation.
Bildnachweis: Image via source article. Used under fair use for news commentary. · source
Salesforce just posted earnings that missed analyst expectations by a hair, and the stock's getting punished for it. But here's the thing: the real story isn't about one quarter's numbers. It's about what happens when the software industry realizes AI might eat its lunch.
I'll be honest, I don't usually write about enterprise software. My world's been factory floors and robot arms for decades. But when I saw the Salesforce news, I called my old colleague at Siemens (he moved to their digital industries division a few years back) and asked what he was hearing. His take? "Everyone's nervous, Bob. Not just Salesforce."
The Disruption Nobody Wants to Talk About
Look, I've watched automation transform manufacturing for 30 years. When I started at Kuka back in the day, we were selling the idea that robots would handle the dangerous, repetitive stuff and humans would move up the value chain. That story worked because there was somewhere to move to.
The software industry told itself a similar story about AI. Copilots would handle the grunt work. Agents would automate the boring bits. Humans would focus on strategy and relationships. Bloomberg reports that investors are now "concerned about the possibility that artificial intelligence will disrupt the software business." That's putting it mildly.
Salesforce's guidance for the current period came in just below what analysts expected. Not a disaster, but not the growth story investors wanted. The company didn't disclose exact figures on how AI is affecting their pipeline, which, frankly, tells you something.
What Manufacturing Learned the Hard Way
Verwandte Beiträge
More in AI Models
New research suggests 120 million workers in advanced economies face AI disruption, but the more pressing question is whether our institutions can adapt fast enough to matter.
Aisha Patel · 2 hours ago · 6 min
SK Hynix and Micron both crossed the $1 trillion threshold this week, and honestly, the implications for embodied AI might be bigger than anyone's talking about.
Sarah Williams · 10 hours ago · 4 min
Four new papers tackle the same headache I've watched engineers struggle with for years: getting language models to actually move a robot arm.
Robert "Bob" Macintosh · 10 hours ago · 4 min
Three new papers push the boundaries of how robots understand 3D scenes without task-specific training, but the benchmarks tell a more nuanced story than the abstracts suggest.

