Generative AI use cases are moving quickly from pilot to production, now delivering measurable, reliable results at scale across organizations.
From detecting anomalies in security protocols to improving developer productivity by automating code migrations, CIOs and IT leaders shared how they’re harnessing the facility of Gen AI across a wide selection of use cases to attain productivity gains.
CIOs of Nvidia, SentinelOne And service now took part in yesterday's panel, Driving business transformation: CIO insights on harnessing the facility of generative AI at Nvidia's GTC event 2024. The panel was moderated by Rama Akkiraju, vice chairman of enterprise AI and automation at Nvidia. The panel included Sabry Tozin, Vice President of Engineering at LinkedIn, Sonu Nayyar, Senior Vice President and CIO at Nvidia, Sandy Venugopal, CIO at SentinelOne and Chris Bedi, Chief Digital Information Officer at ServiceNow.
Measurable results are the fuel that future use cases need
The panel's insistence that genetic AI delivers measurable results was reflected within the responses to several questions in the course of the session.
Genetic AI use cases must deliver measurable value and help streamline processes at scale in the event that they are to survive the pilot phase and move into production.
Tozin explained how Gen AI increases engineer productivity by automating certain tasks: “We are significantly impacting developer productivity by automating much of this work. This allows engineers to really get back to constructing recent things and adding things that really add value to the business, slightly than simply working on things which might be repetitive or seen as some type of maintenance.”
Another example shared by Bedi is embedding ServiceNow's domain-specific language models into workflows to cut back back office workload by 14%. “We use Gen AI in order that when an worker asks for something in natural language, the Gen AI understands the intent. Ninety-nine percent of the time they receive a response from the genetic AI. But what now we have seen on the back end is a 14 percent reduction within the work coming to those back office departments, in about five months,” Bedi said.
Bedi said, “I measure every part to the max… And in keeping with Sabry, these items sells itself.” When we actually calculate all of those individual metrics and add them up, it comes out to about $10 million in annual profit, and that in 120 days. And the AI ​​of the generation is doing the work of the equivalent of fifty people for us, and we’re just getting began with this technology.”
ServiceNow's significant cost savings and productivity gains also exhibit how CIOs view Gen AI when it comes to human resource contribution and capability. Tozin's insights into how and where genetic AI contributes to LinkedIn show that his engineering teams view it as a technology that may offload routine tasks and liberate the technology for more sophisticated, complex work.
Each of the panelists noted the importance of also specializing in the ROI of any Gen AI initiative, comparing the fee of adopting Gen AI with the productivity gains and potential operational efficiencies it will possibly achieve.
Dealing with change management, including addressing organizational and technical challenges, is a universal challenge that makes measuring results all of the more essential.
The rapidly growing use case of Gen AI is recent product development
The CIOs of Nvidia and SentinelOne told the audience in regards to the role of genetic AI of their company's recent product development efforts and environments. They also talked about how its role in delivering products is growing.
Nayyar says Nvidia has decided to take the initiative to pursue Gen AI use cases across the corporate. “As Jensen mentioned yesterday, we have already got a variety of stuff in production. We have ChipNeMo To increase developer productivity, we’re developing additional developer tools similar to Code Critical to enhance code development support, etc. across the organization. We have entire groups working on it. It is an element of our strategic initiatives. I can go on for a very long time, but now we have already implemented a variety of use cases.”
SentinelOne's Venugopal says genetic AI plays a critical role of their cybersecurity vendor's product strategy and recent product development processes. “We invested so much in our product to essentially leverage the capabilities to research anomalies in all the info you will have, around security logs, access logs, where do you discover these strange things or potential threats and how are you going to generate them?” What correct prompts or next actions should your security operations center (SOC) analysts take? So we were actually the zero customer of this product, and that was an enormous investment within the validation work that we did on the corporate side.”
CIO advice for firms just starting out
All CIOs on the panel recognized that the organizational and technical challenges must be addressed directly and early in the method. Nayyar highlights the importance of making a culture that values ​​experimentation and risk-taking, with the aim of making a secure environment for innovation. All CIOs either specifically mentioned data security and governance or mentioned it as a core strength that each company must work on in the event that they want to achieve success with Gen AI.
Here's the very best advice CIOs gave in the course of the panel today:
See and use generative AI as a learning tool. Tozin emphasized that genetic AI have to be viewed as as essential a learning tool and platform for improving skills because it is a task engine. He says a useful exercise is to ask the AI ​​to show you and your team concepts it’s possible you’ll already know to sharpen your understanding.
Show curiosity and fascination for genetic AI to allay the corporate's fear of it. Venugopal recommends CIOs and executives to stay interested in the rapid advances in genetic AI and study how it will possibly help teams.
Jump in and prioritize use cases early and be prepared to be flexible and adapt. ServiceNow's Bedi believes business leaders have to experiment and begin using Gen AI for specific use cases and folks to see how well the technology meets the needs of the business. He highlighted the undeniable fact that early understanding of the overlap between genetic AI, use cases and personas helps move use cases from pilot to production.
