The Frontier of Generative AI in Enterprise

The media crescendo surrounding generative AI has reached such a pitch in recent months that it’s difficult to ascertain genuine insight from all the noise. This means it’s more important than ever to go directly to the experts working at the cutting edge to discover the true significance of the latest developments.

Well, the expert opinion is in: believe the hype, because “there’s a big change coming”.

That’s the view of Chris Booth, generative and conversational AI consultant and product owner for NatWest Group’s artificially intelligent agent: Cora.

So where are we now with generative AI, and where are we heading? When assessing the potential impact of generative AI and the disruption that could be coming down the line, Booth says it’s helpful to think in terms of where we are on the ‘sigma curve’.

“What I mean by that is, if we’re at the top, then most of the impact has already happened and we won’t see much change going forward,” he explains. “If we’re in the middle of the curve, then we can still expect to see generative AI applied to other technologies in the future. Or are we at the start of the sigma curve, with big changes to come?

“Overall,” he says, “that’s where I am – I think there’s a big change coming.”

Booth is one of the experts speaking at the Generative AI Summit, taking place at Hilton Syon Park, London, on 16th and 17th May 2023. He’ll be addressing the topic of what generative AI means for chatbots, drawing on his direct experience of working with NatWest’s Cora chatbot.

Powered by IBM Watson, Cora operates in the closed domain, which is where chatbots primarily exist – especially in large organisations – responding to action- or task-oriented questions such as, ‘Can you change my address?’

“It’s basically a large logic tree,” Booth explains. “This means we dictate what buttons are presented and then what button you click obviously changes your path. So that’s closed domain, and it works really well.”

However, closed domain and logic trees can have limitations, says Booth. “Multiple trees are brittle. They can become very difficult to manage and maintain as they grow at an exponential rate. And the larger the tree, the more links you have to manage and it’s a mess.”

But this is where generative AI has the potential to change things massively, Booth insists. While he admits that generative AI is “nothing new” in the natural language processing (NLP) space – and that it’s only in the last few years that models have become good enough to make generative AI “a contender” – Booth is excited by the potential for changes it could bring for the “opposite end” – the open domain.

He explains: “The open domain deals with questions like, ‘What did Obama do before he was president?’ – an open-ended question that can be difficult to answer. And that’s where logic trees really struggle to capture the potential scope and possibilities of how you can answer that question.

“So that’s where generative AI has huge potential for expansion, with the potential of opening new use cases for businesses to approach.”

However, there are challenges and possible drawbacks. Among them are transparency and explainability.

“Generative AI is usually powered by language models – deep AI machine learning,” Booth explains. “And these deep neural networks have billions and billions of parameters, which makes it difficult to distinguish and understand how the AI has come to its decisioning.”

Also, the language models can be prone to ‘hallucinations’ – which Booth describes as “a fancy word for outputting nonsensical and incorrect answers”. From a language model perspective, these can be very difficult to control, he says. And added to these issues are obstacles surrounding cost, privacy and data security.

But despite the challenges, Booth believes everyone will be putting generative AI to practical use at some point. “There’s going to be varying degrees of how quickly it happens. There are already plenty of startups based on ChatGPT and GPT-3. And there are small businesses in marketing, for example, that are going absolutely nuts with ways of slowly automating things.”

What’s more, opportunity is ripe for breakthroughs in the development of generative AI. “There’s the potential to make a massive impact,” Booth insists. And he’s hoping to realise that potential himself. He reveals: “I’ve got a project right now I can’t talk about in detail, but we’re trying to find ways to cover the gaps and weaknesses of language models. If we do, the implications are pretty large.”

Find out more about the big changes on the way at the Generative AI Summit.

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