I’m always on the lookout for great stories about how real people are using generative AI in their workplace. In two recent articles in the Wall Street Journal, professionals in six different fields, ranging from medicine to law, described their generative AI success stories, how it accelerated their work, and how it improved their quality of life.
Generative AI For Information Management
At Mass General Brigham, 450 doctors are using AI assistants to reduce paperwork by automatically taking notes during patient consultations. Amy Wheeler, a doctor using the technology, said that the notes were “incredibly accurate” and usually required only minimal editing. The net result? Doctors can focus on patients during the visit rather than taking notes, improving the patient experience and reducing physician burnout.
Writer Alexandra Samuel also uses AI assistants to transcribe, summarize, and organize next steps for her meetings. As with the example above, this lets her focus on the meeting rather than on taking notes. She also uses AI powered services to help manage her email so that she can better track discussions, write responses, and keep from dropping the ball on important items.
Generative AI For Research
At Ropes & Gray’s law practice, junior lawyers – who used to be saddled with endless research work – now use generative AI for searching relevant case law instead. Along with accelerating research, the systems help surface related search terms that they may not have considered, and all results are verified before being used in court. Result? Increased capacity and accelerated professional development through both greater case exposure and closer work with other members of the firm.
Writer Samuel also uses generative AI for a number of research tasks. She specifically calls out tech support, subject research – both high level (“explain it like I’m 5”) and deep dives on relevant articles – and for generating additional examples for her work.
Generative AI For Marketing
Dan Bettinger, a principal product-marketing manager at a technology company, shared that he uses generative AI for a range of tasks, including summarization and competitor analysis. It has become a major tool for his blogging activities, helping improve his copywriting, filling out blog posts, and helping him explore alternative blog post ideas. Alex Brown, a director of professional services at a title software company, uses generative AI in a similar fashion – summarizing and condensing complex or long-winded topics into concise, informative nuggets for presentations and reports. For both professionals, generative AI both improves the quality of the results and saves hours of work.
Most intriguingly, Bettinger also uses AI to “pressure test” his posts. He asks the AI to act as a skeptic, providing feedback about its dislikes and how to improve. He notes that this previously would have required focus groups, which can be expensive and time-consuming. The use of AI for crowdsourcing or artificial focus groups has been growing, and can serve as a useful first-pass for a lot of writing. However, it doesn’t replace the human experience yet for a number of reasons, not least of which being that LLM’s have struggled to accurately portray identity groups.
Generative AI For Accessibility
Raul Trevino is a staff cloud engineer whose rare genetic eye disease means he needs accessibility tools to do his work. This has been a challenge historically, as support for accessibility in software and on the web has been spotty at best.
However, he can now use generative AI as a flexible accessibility tool, “helping him read, process information and make decisions much faster.” He simply tells the AI what he is looking for, and it delivers results in a standard, accessible format. The results have been phenomenal, reducing eye strain and stress, as well as saving him several hours per project.
Common Themes When Using Generative AI
There were a few common themes among all of the examples:
- All of them used a “human in the loop” process, where they personally verified the results of the AI before it ever reached their customer. This did cost some time, but far less time than if they had done all of the work themselves.
- Across the board, AI helped increased their overall capacity. It also let them focus on the things they did well, while pushing the tedious work to the AI.
- Developing the right prompts had a major impact on speed and results. Sometimes it took a bit of “prompt engineering” to get the AI to behave in exactly the way they wanted it to.
Keith Ferrazzi, CEO of Ferrazzi Greenlight, says in the article, “It’s not so much ‘AI is coming for our jobs’ but rather, roles are being reconfigured with an AI partner to help businesses and employees work better and more efficiently, while also improving employee job satisfaction.”
Better, more efficient work, and higher employee job satisfaction – coming soon to a job near you.
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