Discovering the Hidden Potential of Generative AI

The recent emergence of generative AI makes this an exciting time for businesses. Generative AI is capable of revolutionizing how businesses operate, and generative AI models can create new products and services, automate tasks, and improve decision-making.

In order to better understand what Generative AI can truly do for organizations, the SSONext podcast is sharing one of our top sessions from last month's Intelligent Automation World Series online event. In the session we spoke to Shail Khiyara, CEO of VOCAL, Amol Rajamane, Global Digital Automation Technology Leader at DuPont, and Melanie Dunbeck, Automation Strategy & Enablement Lead at Kelly Services, about their vision and experience with Generative AI. The following are some key takeaways from that session, but if you are interested in hearing the full conversation check out the podcast below. 

Immediate use cases 

While the full arsenal of use cases for generative AI has yet to be fully understood, the panel discussed some immediate opportunities generative AI offers.

For Amol, one of the most evident use cases of generative AI comes in knowledge management. Generative AI can be leveraged to organize a document repository that saves time for employees seeking data. For example, instead of using a search engine that points employees in a dozen different directions during their dig for information, a large language model will compile the necessary information in an accessible and understandable format. This removes much of the leg work for employees and gives them more time to complete analysis.

At Kelly Group, a staffing and recruiting firm, generative AI is also being used to lighten the load for employees.

“Our recruiters need to process job descriptions. They need to process resumes. There's a lot of communication required when engaging with the client and with our candidates. And so, our use case is around creating and using generative AI help with prompt engineering and transforming large quantities of information,” Melanie said.

Recruiting agencies must manage hundreds of clients who have different needs, which is why using the prompt-generating abilities of generative AI allows recruiters to put together job descriptions quicker and focus more of their time on locating talent. 

Addressing data security concerns 

As with any new AI technology, stakeholders are likely to have concerns about how the solution will impact their work and privacy.

“When we bring this technology, there are challenges about security, privacy, ethics. Which makes choosing the right tool or the right large language model very, very critical,” said Amol. 

Organizations don’t want their employees plugging company data into these large language models. In fact, this spring, Samsung announced it would be banning employees from using programs like ChatGPT in their work after an engineer reportedly uploaded sensitive information to the A.I. chatbot. 

In order to find a generative AI solution that both protects data and improves organizational efficiency, businesses must have a strong AI framework that defines what different functions should get out of their work with generative AI and how it should be used to protect critical data. This framework should also provide a guide to finding a generative AI solution that checks all the key boxes.

For those interested in gaining more insights on use cases for generative AI, be sure to register for SSOW this March 25-28 in Orlando, Florida. During the conference, attendees can participate in bootcamps focused on how HR and finance/accounting teams can use the technology.