Analysts agree that incorporating human input to sign off on decisions and outcomes of generative AI processes is proving to be an essential driver of early genAI success.

 “Generative AI is becoming the virtual knowledge worker with the ability to connect different data points, summarize and synthesize insights in seconds, allowing us to focus on more high-value-add tasks,” says Ritu Jyoti, group vice president of worldwide AI and automation market research and advisory services at IDC.

“It is transforming processes like loan underwriting, but human-in-the-loop is critical as it requires 100% accuracy without fail to be truly effective and viable, as the technology is still nascent,” Jyoti says.

Ramping up for model-agnostic AI

Rocket is as much an engineering company as it is a mortgage lender, with more than 1,000 engineers and 600 data scientists working together to build most of Rocket’s code in-house — a major advantage to its innovation efforts. 

When Woodring joined the company in 2017 as CTO to lead the product engineering team, one of his top priorities was accelerating Rocket’s embrace of the cloud. 

“One of the first things that I did after I joined, six months in, we declared that going forward, all of our new technology would be built in the cloud,” he says.