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According to EY’s global chief technology officer, Nicola Morini Bianzino, there is currently no “killer” use case for using ChatGPT in the enterprise – that is, one that will have a huge impact on the top and bottom line.
But that could soon change: The next six to 12 months will see an explosion of experimentation, he predicted, especially if companies are able to build on top of ChatGPT using OpenAI’s API. And the great use case that emerges could be about the impact of generative AI on knowledge management – which Bianzino describes as the “dialectic of AI.”
“Knowledge companies tend to store knowledge in a very flat two-dimensional way, making it difficult to access, interact with, and engage in dialogue,” he told VentureBeat in an interview. “We tried to build expert systems 20, 30, 40 years ago. That didn’t really go well because they were too rigid. I think this technology promises to solve many problems that expert systems have.”
As ChatGPT and similar tools evolve and improve, and being able to securely train on an enterprise’s data will change the way we access and use information within the enterprise, he explained.
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“I think we’ll get to a point where we can actually have a conversation about the company’s performance with an AI agent,” he said. “You question the system, the system is able to hold the state of the conversation, and then each question allows you to dig deeper into the problem and understand it better, instead of giving me a report about sales in this specific region for the last month, which usually doesn’t yield much insight.”
A significant impact on enterprise software
This opportunity for the future of generative AI would have a significant impact on enterprise software, Bianzino explains, as organizations would need to start thinking about new ways to structure data across an enterprise beyond traditional analytics tools.
“To be honest, there are nice dashboards, much better data structures, but not a huge amount of value,” he said of the current tools.
On the other hand, Bianzino suggested envisioning a future where a ChatGPT or equivalent could be “invited” to a board meeting and questions asked.
“The feature I’m so impressed with is the tool’s ability to hold the status of the conversation,” he said. “With an ordinary, more friendly officer, you ask a question and you 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, what products didn’t we sell? And then you can say, what about the weather in the region? So you can go through an analysis tree that is not predetermined.
ChatGPT should overcome business hurdles
At this point, the probability that Bianzino describes is theoretical. There are many different hurdles that ChatGPT and other generative AI tools have to overcome, from potential ethical implications to the accuracy issues that even OpenAI CEO Sam Altman has admitted.
Text and documentation generation should also be trained and aligned with the appropriate ontology of the specific enterprise, Bianzino explained, and should be securely contained, stored and controlled within the enterprise. But if it could, he said, it would create tremendous value.
“If you think about an organization like ours, we have 360,000 people, we’ve built a lot of tools and capabilities over the 100+ years of our history,” he said. “But that knowledge is being spread now. You can’t really get your hands on it. It’s the soul of our organization, but it’s intangible.” If you could systematize it into an ontology and make it part of a technology solution, you could significantly increase business value, he continued.
“Whenever I talk to mining clients or other types of clients in the resource space, they all lament the fact that there aren’t as many engineers coming through academia as there have been in the past,” he said. “They’re afraid they’ll lose the knowledge of the people who are retiring — so think about storing that knowledge and making it accessible through a tool that gives them easy access to that value.”
Experiments and an explosion of use cases are underway
Bianzino says EY is currently working on the capabilities: “We’re putting a team on it and we’re experimenting with where we can take it – we need to better understand how to structure the data behind it to extract the highest possible value from the interaction. he said, adding that it’s not yet clear whether unstructured data like videos or music can be handled. “But I’m very optimistic that you could roll something like that out in a short time frame for a company like ours.”
While the generative AI landscape is still in its infancy, Bianzino encourages organizations to play around with tools like ChatGPT, even just for fun.
“One of my kids showed me yesterday that you can make a story with ChatGPT,” said Bianzino. “When you start playing with it, I think you start to understand the potential.”
Business leaders, such as the CTO and CIO, need to be aware of these trends, he continued, because unlike something like quantum computing, which may be another 10-15 years in the future, the real opportunities of generative AI may not be until 6 -12 months away.
“This is going to be big,” he said. “At the moment there is no killer use case… but I think it will be very soon.”
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