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Right now there is no “killer” use case for using ChatGPT in the enterprise — that is, one that will have an enormous impact on the top and the bottom line — according to EY’s global chief technology officer, Nicola Morini Bianzino.
But that could soon change: The next six to twelve months will bring an explosion of experimentation, he predicted, especially once companies are able to build on top of ChatGPT using OpenAI’s API. And the killer use case that emerges could be around generative AI’s impact on knowledge management — that Bianzino describes as the “dialectic of AI.”
“Knowledge companies tend to store knowledge in a very flat two-dimensional way that makes it difficult to access, interact, and have a dialogue with,” he told VentureBeat in an interview. “We tried 20, 30, 40 years ago to build expert systems. That didn’t go really well because they were too rigid. I think this technology promises to overcome a lot of issues that expert systems have.”
As ChatGPT and similar tools evolve and improve, and can be trained on an enterprise’s data in a secure way, it will change the way we access and consume information inside the enterprise, he explained.
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“I think we will get to a point when we can actually have a conversation about the company performance with an AI agent,” he said. “You interrogate the system, the system is capable of maintaining a state of the conversation, and then every question allows you to dig deeper into the problem and understand it better, as opposed to let me run a report on sales in this particular region for the last month, which doesn’t usually provide a lot of insights.”
A significant impact on enterprise software
This opportunity for the future of generative AI would have a significant impact on enterprise software, Bianzino explained, because organizations would have to start thinking about new ways to structure data inside an enterprise that go beyond traditional analytics tools.
“To be fair, there are nice dashboards, much better data structures, but not an enormous amount of value,” he said of current tools.
On the other hand, Bianzino suggested imagining a future where a ChatGPT or equivalent could be “invited” to a board meeting and could be asked questions.
“The feature I am so impressed with is the ability of the tool to maintain the state of the conversation,” he said. “With a regular, more conversational agent, you ask a question and get an answer. With ChatGPT, you can go deeper, you can say, tell me, what went wrong last week? And then you say, we didn’t hit our targets, okay, which products we didn’t sell? And then you can say, what about the weather in the region? So you can go down a tree of analysis that is not a predetermined one.”
ChatGPT would have to overcome enterprise hurdles
At this point, the opportunity Bianzino describes is theoretical. There are many different hurdles that ChatGPT and other generative AI tools need to overcome, from potential ethical implications to the accuracy issues even OpenAI CEO Sam Altman has admitted.
The generation of text and documentation would also need to be trained and aligned to the proper ontology of the specific enterprise, Bianzino explained, and would need to be securely contained, stored and controlled within the enterprise. But if it could be, he said, it would create an enormous amount of value.
“When you think about an organization like ours, we have 360,000 people, we have lots of tools and capabilities built in the more than 100 years of our history,” he said. “But that knowledge is distributed now, you can’t really touch it, it’s the soul of our organization, but it’s immaterial.” If you could systematize it into an ontology and make it part of a technology solution, you can increase enterprise value significantly, he continued.
“Whenever I talk to mining clients, or other types of clients in the resources space, right, they all lament the fact that there are not as many engineers coming through academia as there were in the past,” he said. “They’re worried they’re going to lose the knowledge of the people that are retiring — so think about storing that knowledge and making it accessible through a tool that allows them to easily access that value.”
Experimentation and an explosion of use cases is on the way
Bianzino says EY is currently working on the possibilities: “We’re putting a team on it, and we’re experimenting on where we can take it — we need to understand better how to structure the data behind it to extract the highest value possible from the interaction,” he said, and added that it’s not yet clear whether unstructured data like videos or music can be processed. “But I’m very optimistic that you can roll out something like that within a short time frame for a business like ours.”
While it’s early days in the generative AI landscape, Bianzino encourages organizations to play with tools like ChatGPT, even just for fun.
“One of my children showed me yesterday that you can create a story with ChatGPT,” Bianzino said. “If you start playing with it, I think you start understanding the potential.”
Enterprise leaders, such as the CTO and CIO need to be on top of these trends, he continued, because unlike something like quantum computing, which still might be 10-15 years in the future, the real opportunities of generative AI may only be 6-12 months away.
“This is going to be big,” he said. “Right now, there is no killer use case…but I think it’s going to move very fast.”
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