Adoption of GenAI is Outpacing the Internet and the Personal Computer

The survey first defined genAI as follows: “Generative AI is a type of artificial intelligence that creates text, images, audio, or video in response to prompts. Some examples of Generative AI include ChatGPT, Gemini, and Midjourney.”

I love how simple this is. This helped to eliminate the “unknown” use of embedded AI solutions. It also helped control for people who don’t understand terms like “large language model” and “machine learning”. I suspect they were also trying to get at people that have knowingly made a decision to use a conversational genAI chat solution. Then they asked if respondents had used genAI for their work, followed by asking if they used it for personal use.

The authors found that: “… 39.4 percent of all August 2024 respondents say that they used generative AI, either at work or at home. About 32 percent of respondents reported using generative AI at least once in the week prior to the survey, while 10.6 percent reported using it every day last week.”

Almost one third of Americans are using genAI at least once a week, and ten percent every single day. According to the study, these are some of the most common tasks performed at work, in order of the frequency of use. This helps us get a sense of the most common everyday use cases: writing communications; performing administrative tasks; interpreting, translating, summarizing; searching for facts or information; coding software; documentation or detailed instructions; generating or developing new ideas; support with customers or coworkers; data analysis or visualization; and tutoring or educational assistance.

People are using genAI at work in their day-to-day lives. They are finding ways to be productive. The productivity gains are there. The next logical question is how organizations can take advantage of these productivity gains. This is an interesting question, and the survey found that: “Employer encouragement is highly correlated with AI use: 82.9 percent of workers who report encouragement also report using generative AI, compared with only 7.1 percent of workers who report no encouragement.”

This means that those of us who are banning the use of genAI at work are missing out on the potential for productivity gains. The incredibly well researched and articulate professor Ethan Mollick out of Wharton noted that: “… when I talk to leaders and managers about AI use in their company, they often say they see little AI use and few productivity gains outside of narrow permitted use cases.”

Organizations are not seeing the gains that workers are. He noted that this seems to be due to two major factors – scary policies and lack of internally driven research and development in an AI lab environment. He points out that organizations can crowd source innovation from workers by encouraging them to safely innovate, and then use the lab to operationalize that innovation and drive enterprise value.

This tells me that we really must figure out how to balance the real risks inherent to generative technologies in a way that does not stymie innovation. I continue to believe that the organizations that find a way to take advantage of genAI with truly innovative use cases will get the edge, broadly and specifically in mortgage.

Last thought for today – equally staggering about the study, fully 60 percent of Americans have never knowingly used a genAI solution. That is also bonkers! So when you are in a room of 20 people talking about genAI, up to 12 of them might have absolutely no idea what you are talking about. With such limited understanding, how can organizations get started? We must educate and create awareness. If AI is going to be for everyone, we really must lean into educating our organizations.

GenAI is still very early in implementation in mortgage, which means the edge is still up for grabs. But it will start with understanding what we are talking about. We are offering some education if you are interested.