leading to costly missteps and eroded confidence.
The cautionary tale of Zillow’s iBuying collapse ghana cell phone database in 2021 is a case in point. Zillow leaned heavily on an AI-powered home-buying algorithm to identify properties to purchase, renovate and resell at a profit. But the model was a black box to many people relying on it — and it overestimated home values in a rapidly changing market.
Dig deeper: Your AI strategy is stuck in the past — here’s how to fix it
Lacking guardrails, the system led Zillow to overpay for thousands of homes. Within months, the company reported hundreds of millions in losses, laid off a quarter of its workforce and shut down the program entirely. The underlying issue wasn’t just poor predictions — it was the lack of transparency, oversight and human-in-the-loop checks that could have flagged problems before they spiraled.
The most successful marketing organizations won’t be the ones with the flashiest AI tools, but the ones that design systems their teams can understand, monitor and explain.