Lee Fulmer, Chief Data Officer and Global Head of Innovation Labs at UBS, shared his experience of augmenting human processes with AI at this year’s CDAO UK conference
AI and augmented analytics are set to play a key role in the future of UBS’ business strategy. But like many data-focused leaders, Lee Fulmer, Chief Data Officer and Global Head of Innovation Labs at UBS, has encountered some people at the investment bank who are nervous about embracing the technology.
Luckily, as a member of Gartner’s Advisory Board and one of Data IQ’s 2022 ‘top 100’ leaders in data, Fulmer has a wealth of experience in overcoming this kind of challenge to deliver digital transformation success.
In his keynote speech at this year’s CDAO UK conference, he outlined why augmented intelligence is such a pivotal technology for UBS and shared his ‘top tips’ for integrating it with existing staff roles and responsibilities.
“Let's talk about applying technology to the human process of analysis,” said Fulmer. “If you think about what technology allows us to do, it allows us to operate at scale. We can process more data, faster than we can as humans.”
He added: “If you use the technology in a way to rapidly sift through all the dross we all have, try to find the [patterns that could be interesting] and then apply human insight to that, you get much better value.”
Communicating the Benefits of Augmented Intelligence
It’s still common for company employees to have concerns about what the adoption of AI may mean for their jobs. But Fulmer argued that the idea that AI will replace people’s jobs is “not true any more than Bitcoin was going to disrupt the banks and make them all go under 20 years ago”.
“What you have to do is work out how you can disrupt your people's thinking,” he recommended. “It's just about how we can say to people, ‘Look, don't be afraid. The robots aren't going to take your job.’”
He argued that there was still space for everybody, but “you have to help people along the way”. The role of the data leader is to design AI-driven processes with people in mind, and to educate staff about what this technology will really mean for them in practice.
“Artificial intelligence, when you talk to people who know what it is, [they] will tell you we are still decades away from recreating what a three-year-old can do,” Fulmer said. “What we talk about when we talk about artificial intelligence is actually programmatic machine learning.
“It’s somebody writing a process that takes data inputs and produces an outcome. Now, the outcome could be variable. But it is still following a process.”
He concluded that “you cannot underestimate, no matter how much tech you throw at the problem, the people equation”.
AI Success Starts with Getting the Right Data
Fulmer said that, while algorithms allow leaders to assimilate much more data than before, not all of that data is useful.
“Because technology has evolved and it's cheaper now to store things, we keep everything, whether it’s valuable or not,” he said.
He said it was vital to establish what data matters and catalog it, adding that the best way to achieve this at UBS was to get a fresh, outside perspective.
“People who don't work in your business might find patterns in that data that you wouldn't see because you're so used to looking at it with a singular focus,” he noted. “That transformation, for us, is what's actually powering our business.”
Ultimately, he concluded that a top priority for data leaders should be identifying valuable datasets and using them to uncover insights the business did not previously have access to. Arming staff with these insights will make them more effective in their roles.
“For decades, people have been using technology to process business information,” he said. “What we, as data specialists, need to do is to drive new business insight.”
