Inc.
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Spirit Airlines may be gone, but its vast internal archive could give Google an unprecedented look inside a failed company.
A Company Dies. Its Data Lives On. AI Could Tell the Story
Author: Sophie Meharenna
“Everything is copy.”
The famous line is one of my favorites, popularized by writer, journalist, and filmmaker Nora Ephron. It speaks to the philosophy that anything and everything in your life is material to write about. That said, “Everything is data” feels more apropos for the times.
Case in point: Google’s race to purchase Spirit Airlines’ data for $10 million.
When a corporation dies, what happens to your data?
Have you ever thought about what happens to your data when a company ceases to exist?
Analyzing its data can shed light on what made it successful when it lived and what ultimately led to its demise. This is greatly beneficial for business leaders who don’t want to repeat failures.
So, while Spirit Airlines may not be operating after 34 years, if this sale is successful, Google’s AI-training models will give its internal data a corporate afterlife.
And it’s inheriting an exhaustive dataset: the internal enterprise data includes 100 million emails, 500 million Microsoft Teams chats, and collaboration records, among other operational files and audits.
Armed with this information, Google can move from a position of power with implications beyond the airline industry. Sure, they’ll have insight into the highs and lows of Spirit Airlines’ inner workings, but it also might indicate a trending modality of AI-powered lane of corporate autopsies.
In this situation, though the archives will be scrubbed of identifying information, Google’s AI models will be able to reconstruct the voice and spirit (all puns intended) of Spirit Airlines: what worked, what didn’t, and how the company’s internal and external exchanges influenced the organization.
A company’s remains in an AI-powered era
In the past, most failed businesses were observed and diagnosed in retrospect, with incomplete information aggregated from analysts, journalists, or former employees.
As the race to train AI models continues, the next high-profile bankruptcy might not end in liquidation, but again with primary source material sold to the highest bidder and a diagnosis that can be run at scale by a machine.
It begs the question: since everything is copy, and everything is data, where is yours going next? What story will your data tell, and better yet, to whom?
Credits: TCA, LLC.