In the plenary session on the significance of disruptive innovation and AI, 76 percent of poll respondents agreed with the above statement, while 22 percent said they think AI’s effect on financial institutions is still up for debate, and that the benefits are “unclear”.
Only 1 percent of respondents said they do not consider AI a priority at all.
Speaking on the panel, Amber Case, a fellow of the Berkman Klein Center for Internet and Society at Harvard University, noted that the AI and machine learning solutions we have today are not those from science fiction, rather, we are the robot stage of automation and “narrow AI”, with a small knowledge base.
Ultimately, computers will not being doing things for us, but augmenting humans, giving suggestions, information and options as and when humans require them, freeing up our time.
We have not yet reached that stage, Case said. However, she added: “We have co-evolved with technology since the beginning of time, we will continue to do so.”
Standard Chartered’s Alex Manson added, in response to the audience poll, that data is critical going forward, but that it is useless unless it offers insight, leading to intelligence and therefore actions. While the human brain can process information in this way on a small scale, this industry has huge amounts of data, and that’s where AI comes in.
He added that AI is “more than a buzzword” today, and that if people in the business are not a little paranoid about it, they are at risk of becoming complacent.
However, any innovation must ultimately be relevant to customers. He said: “The last thing we want is a bunch of solutions looking for a problem”
On this issue, Axel Lehmann, group COO of UBS, noted that the challenge is not necessarily in the technology—large institutions have the capacity to buy technology or develop it themselves. The problem is how to generate real use cases and develop value from that.
This will not only affect mundane activities, but will go to the core of organisations, affecting aspects like portfolio composition, monitoring and predictive pricing, he said.