Feature
Generative AI is on everyone’s agenda right now. As you contemplate what this promising, evolving and perhaps even concerning technology can do to lighten your workload and improve efficiency, seeing how others have successfully tapped its power can provide inspiration. Professionals are using some of the biggest large language models (LLMs) and tools in the game to tackle problems humans were unable to solve. Here, we look at several examples that demonstrate the range of business uses for generative AI.
1. Lifespan
The consent forms patients sign before agreeing to surgery are complex and difficult to understand for many people asked to agree to them. Not understanding what you are letting a surgeon do to you can be terrifying. Yet, a study done by the New England Journal of Medicine found that most of these forms are written at a college level, while over half of Americans read at or below the sixth-grade level.
Dr. Rohaid Ali and Dr. Fatima Mirza at Lifespan, one of Rhode Island’s largest health care systems, were painfully aware of this, according to a case study.
“Surgical consent conversations can be very overwhelming and emotionally charged for patients,” Dr. Mirza says.
The doctors also knew that understanding these forms is crucial for patients. Comprehension is linked not only to the complexity that surrounds consent for invasive procedures, but also to patient outcomes.
The doctors thought the GPT-4 version of ChatGPT might be able to simplify the forms. Lifespan began using ChatGPT to revise these forms, so they could be understood by a middle school reader. It went well. With a carefully worded prompt, the AI was able to reduce a ponderous three-page form to a single easy-to-read page.
Patients loved it.
“Since we’ve implemented the simplified consent forms,” says Mirza, “countless patients have expressed how meaningful it is for them to have a one-page form they can understand. It’s a welcome source of comfort in a period of heavy uncertainty.”
Results
- Reduced the word count of long, difficult consent forms by 25%
- Health system applying process to other medical documentation, including patient intake forms
- First chatbot output required one expert modification
2. Lucy
Lucy is a modern search tool that allows companies to access their own data, on their own servers, with a straightforward natural language question. It works inside whatever chat system a client uses, such as Microsoft Teams or Slack. The founders of Lucy call it an “answer engine” rather than a search engine.
“We make a promise that you can find information you didn’t even know existed in your company,” says Steve Frederickson, chief product officer, Lucy.ai. “Lucy is the fulfillment of that promise.”
The company’s first product used an AI platform to find answers. But as demand for Lucy grew along with customer’s data stores, the amount of data “she” had to search increased beyond her ability, according to a case study.
It was time to build a new AI infrastructure to handle the proliferation of data she was swimming in. The company worked with Microsoft Azure services, tapping a suite of products to build a secure system that could search any kind of data, including video, to find, in seconds, the answer to a question a user has about their own data.
The newly rebuilt Lucy can find that answer — in videos, PDFs, PowerPoint presentations and more — in seconds in response to natural language questions.
“When we launch with a new enterprise customer, we need to index terabytes of data from thousands of SharePoint sites immediately,” Frederickson says.
Lucy, in her updated configuration, can do the necessary indexing.
Results
- Newly built AI infrastructure
- Tool adopted by 100% of customers who try the new video indexer
- Tool pinpointed precise moment in a video that answers a user’s query
See more: 10 Top Generative AI Companies
3. DeepMind
Scouring scientific literature for data can be a time-consuming, tedious chore for scientists. Scientists at Google DeepMind thought that Gemini could help speed up the work. When faced with a 2021 study that needed to be updated, they asked Gemini for help, according to a case study.
The original scientists extracted data from hundreds of papers for the report. Data extraction for scientific research is a time-consuming job that entails reading thousands of papers, filtering out those that aren’t relevant and pulling relevant data from the hundreds that are left.
Taylor Applebaum, a software engineer at DeepMind, was charged with attempting to use AI to update the study for 2023.
“Over 200,000 new open-access papers were added to this domain since 2021,” she says. “We couldn't do this manually. So, we asked Gemini to help us out.”
The team wrote a prompt asking Gemini to find relevant papers, read them and extract the key data.
“Over a lunch break, Gemini read 200,000 papers for us, filtered it down to 250 and extracted their data,” she says. “Now we have a refreshed version of the data set.”
Gemini was also able to examine a screenshot of a graph in the original study and reverse engineer the code that created it. The team used that code to update the chart with new data.
Results
- Annotated relevant data from initial set of 200,000 papers
- Quickly put scientists in position to update years-old research paper
- Saved significant labor for a team of scientists
4. Booking.com
Booking.com wanted to tap AI to make it easier for customers to find a travel itinerary. The company has a history of data-driven innovation. It also has huge stores of data — content, reviews and booking details — that could help. But that data was hard for customers to filter, according to a case study.
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The company worked with Amazon Bedrock to build a tool that could quickly sort through the data to respond to customer’s natural language questions about travel. The company already used AWS for data storage and machine learning (ML).
“Generative AI is on everyone’s agenda right now,” says Thomas Davey, VP of big data and machine learning, Booking.com. “We can pick the right language models and fine-tune them with Booking.com data to deliver destination and accommodation recommendations that are tailored and relevant.”
The company built an AI Trip Planner that allows customers to have an in-app conversation with an AI about where they want to go and what they want to do when they arrive. It strips out the customer’s personal data and then taps Booking.com’s vast data set of reviews and travel information to make recommendations. It creates a carousel of options customers can flip through and book within the app.
Results
- Turned decades of user reviews into instant recommendations
- Helped customers find itinerary ideas they never would have thought of
- Quickly stripped personal data from in-app conversations to protect user privacy
5. Minijob Zentrale
Minijob-Zentrale (MJZ) is a German agency that gathers and reports on data and news about part-time jobs. A team of editors publishes articles intended to engage and inform an audience of interested parties. The team often reports on complex regulatory issues and news. They were finding it challenging to come up with story ideas and write articles on this topic that were both interesting and accurate, according to a case study.
The team worked with IBM and its watsonx.ai. The generative AI was able to analyze MJZ’s workflows and content to create an AI editorial assistant, Mini, to help them with the work. Mini simplified texts, came up with ideas and helped adapt stories and data for the target reader.
With Mini on the team, lifting some of the workload from the editors, the team was able to write and publish more articles faster, while maintaining accuracy and creative control.
“With this tool,” says Madeline Scholz of Minijob-Zentrale, “we will need only a quarter of the time compared to before to plan, write and publish an article.”
The AI also helped editors better understand and empathize with their readers, so the content they write and publish is on target.
Results
- 75% less time to publish articles
- Simplified complex editorial texts
- Learned about the audience
See more: 10 Top Generative AI Certifications
