Readying for a new generative AI reality

Businesses and consumers globally are increasingly focused on what a future driven by generative AI might look like.

In short, by using the breakthrough of the large language model to generate words and redefine interactions with humans, generative AI improves the communications between humans and machines to enhance all aspects of life and work.

“It cannot be overstated that this is a huge moment for technology,” said John Burkey, CEO and CTO at Brighten Ai. “Generative AI understands what we are saying and converses with us with insight, involving a level of thoughtful responses and detail that we would never have thought was possible.”

According to Yumei Dou, Founder of InAI Capital, generative AI creates the possibility for large language models to understand human intentions and respond, plus for empowering and reshaping interactions between humans and machines.

“I don’t see much downside. Everyone should embrace generative AI, to use it to increase their efficiencies,” added Dou.

To reinforce this view, rather than replace the work of human beings, Kenny Chien, CEO and Founder at Emotibot Technologies, believes generative AI and large language models will spur positive change. “A key way to assist the future of humans is to help them learn. An AI ‘coach’ should accelerate onboarding as well as ongoing training in all tasks and roles,” he said.

Ultimately, the application of generative AI can save people a lot of time by designing replicable processes, resulting in roles being less task-oriented and more creative, agreed speakers.

Generative AI can augment professionals' capabilities, rather than disintermediate them. As a result, business leaders and investors in nearly every sector will need to understand how these tools will allow firms to accelerate and redesign business processes, plus create more sustainable operations.

To commercialize and monetize this evolution requires human involvement. According to V.S. Subrahmanian, Walter P. Murphy Professor of Computer Science, and a Buffett Faculty Fellow, Northwestern University, the key to enable a more natural conversation to create a product tailored for an individual.

“Every interaction with a customer is an opportunity for a company and its algorithms to learn from whatever the customer is saying and asking for,” added Subrahmanian.

However, in its role as a productivity tool, generative AI requires a very clear problem statement of what needs to be solved, explained Bill Russo, Founder and CEO at Automobility.

In the autonomous driving space, for example, the problem today is how to train the machine to be better at making recommendations about what happens next. “What generative AI will become in the near term, is an AI cockpit,” he added. “If this can be done with voice interaction also, then it will speed up the development process.”

From a sustainability perspective, meanwhile, AI can help solve the problem of gathering, organizing, structuring, and understanding newer data points, such as the gender breakdown of a company’s employees, or its carbon footprint.

Financial industry practitioners, for instance, can then use this tool to meet the increasing demands from stakeholders to incorporate these and similar environmental, social and governance (ESG) related factors into risk management and decision-making processes, explained Jack Lin, President of MioTech.

“This generative AI-led modelling can be applied to give a good estimation of what the future might look like,” he said.

Notably, China is experiencing ground-breaking progress on generative AI, offering a new dimension for industrial digitalization.

This is being fuelled by a swarm of large language models, which are attracting growing amounts of investment into AI research and development, and luring venture capital into AI-related companies.

“We are in the golden age of ‘AI-native innovation’,” said Dr Bowen Zhou, Founder, Frontis.ai (Xianyuan Technology), and Professor, Tsinghua University. “Artificial general intelligence (AGI) is the most disruptive form of AI, with generative AI likely to be the best pathway to AGI.”

In China, this is helping enterprises manage knowledge, improve productivity and insights, and enhance customer interaction, he added.

As a result, it leads to more personalized product recommendations, explained Zhou, who is also an IEEE Fellow, a Former President of JD Cloud & AI, and Chair, Technology Committee at JD.com Group.

As businesses seek to leverage generative AI, Azeem Azhar, Futurist and International best-selling author, as well as creator of the acclaimed Exponential View newsletter, sees today’s era as being driven by four general purpose technologies: computing, energy, biology, and manufacturing.

“These are the most disruptive types of innovation that can be found in an economy,” he explained. “They can be applied in any sector and at any point in the value chain, driving down the costs of economic and industrial activity.”

Against this backdrop, Azhar believes there is a vast opportunity for value creation.

With general purpose technologies, in particular, there is the ability to support most industries, create new ones, provide new infrastructure and foster second-order effects – all with a low cost of input. “AI has similar hallmarks as a general-purpose technology,” added Azhar.

The views expressed are those of the interviewees and do not necessarily reflect those of UBS.