Spoke to an AI product leader at a $100bn public company.
Their AI strategy isn’t working as planned…
Has nothing to do with people. They poached tons of talent from FAANG.
Has nothing to do with use cases. They’ve made waves publicly for their early AI wins.
Has everything to do with risk tolerance and politics.
This company formed an internal AI org to be the service provider of AI needs for the rest of the firm.
Because of that, a mandate exists where employees are only able to work with this internal function and no outside AI vendors/software. It’s how this behemoth is controlling risk.
Issue is, there are lots of mouths to feed and not enough internal resource. Folks at the company have gotten impatient and are going rogue, pull on outside vendors to help with AI transformation.
This is why I believe AI transformation will largely be relegated to outside partners, and why getting enterprise adoption is so damn hard.
You can get data right.
You can get talent right.
You can get use cases right.
You can get training right.
But the weight of bureaucracy and cultural debt can be crushing and is likely the biggest risk to companies missing out on the value of this technological supercycle.
"We approach safety and capabilities in tandem, as technical problems to be solved through revolutionary engineering and scientific breakthroughs. We plan to advance capabilities as fast as possible while making sure our safety always remains ahead." - Safe Superintelligence
Interesting (and cool) approach by ChatGPT to reinforce learning by serving up two response variants, and asking for which one is best. #ChatGPT#AI@OpenAI
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