According to Beatriz Sanz Sáiz, applying AI isn’t about competing with tech companies that already have a head start. It’s about leveraging the business expertise you already have.
As you would expect from a woman leading global consultancy in data and analytics, Beatriz Sanz Sáiz is a forward-thinking early adopter with a head for emerging technology and innovation. You can see this in charting her career progression, in which a pattern of becoming the youngest person appointed to senior roles quickly emerges. And you can certainly hear it in conversation with her.
Yet, at the beginning of this conversation with Sanz Sáiz during a recent visit to Dublin for Ireland’s National Analytics Summit, she revealed how her pioneering nature could also make her feel like a bit of an outsider in her early days.
“20 years ago, I felt a bit like a green dog,” she said, deploying a native Spanish phrase for a bit of a weirdo. “Nobody was understanding what I was talking about. Just a conversation with a C-suite member on this topic [emerging technology] was so difficult to have.”
Green dog or not, Sanz Sáiz was evidently undeterred from sharing her fresh ideas with senior leaders. During her time at Banco Santander – her first job out of college – she presented the CEO with a statistical analysis of data available within the bank, forecasting which customer behaviours indicated that they were likely to leave the bank. The CEO tried to call her bluff and directly reach out to a client identified as at-risk in the analysis.
“In front of 20 executives … he started calling clients. The CEO of a large bank calling clients!” she recalled. “But this is a matter of probability. I was lucky, because the client was pissed off.”
Data decision-making in the C-suite
Though Sanz Sáiz, who now serves as data and analytics lead for EY Global Advisory, can still find herself the only woman in a room of executives more often than she would like, she does sense a shift in how the C-suite responds to the suggestion of new applications of technology and analytics to their business.
“Now they are open. Now they feel that they need to know because this is about their future, the future of their company,” she said. A positive sign, she noted, is the introduction of new roles such as innovation lead, head of digital transformation and chief data officer.
“Eight years ago, [data officers] were sitting on the technology side. Now, by the end of next year, 80pc will sit on the business side, many as part of the C-suite. It’s seen as something strategic.”
‘There are some sectors which are struggling to get the right talent and so there’s no other choice than to capture the knowledge through AI systems. It’s about the future, it’s about survival’
– BEATRIZ SANZ SÁIZ
Using AI to mitigate loss of experience
While she was reluctant to identify any particular companies leading in the application of artificial intelligence (AI) for data insights, Sanz Sáiz was enthusiastic about the sectors that are best positioned to benefit from this technological shift. From automotive to health and manufacturing to agriculture, there are few businesses for which she can’t see opportunities in this space.
The energy and utilities sector, she said, is one that’s already heavy on sensors and “anything that is heavy on sensors and automation is the perfect field to build AI on top of”. However, Sanz Sáiz also sees a way that AI can assist this industry with its loss of technical talent.
“They are struggling because their employees are ageing and they are not a sexy sector to get into. They are experiencing issues in recruiting talent. So they are somehow applying AI to capture the knowledge of all these experienced employees that are ageing just to guarantee the future.”
This, she said, is one of the greatest applications she sees for AI in the future. “There are some sectors which are struggling to get the right talent and so there’s kind of no other choice than to capture the knowledge through AI systems. It’s about the future, it’s about survival.”
The problem with banking
But where this sector is making the most of the application of AI, there’s another that’s sleeping on the opportunities it presents.
“Banking is a sector that is probably quite mature but, to me, with the amount of data that they have, they should be even more. I don’t think they have leveraged the data that they have at the [right] speed and in the right direction,” said Sanz Sáiz.
And if the banks want to blame the cost and complications of transforming widespread legacy systems for slow-moving tech transitions, Sanz Sáiz isn’t buying it.
“I think that’s maybe an easy excuse,” she said. She believes there’s no reason a traditional business can’t decommission and migrate progressively towards new systems, but “you have to tackle the problem and define a roadmap for transformation, and be smart on how you’re going to compete”.
For her, banking’s approach to taking on new technology has been all wrong. “They have been trying to compete with the fintechs … who will always have better engineers than any traditional bank. And, of course, you can’t keep competing with technology that is 50 years old, and banks have hosts and mainframes from the ’70s and ’80s. The average cost of a transaction is seven times more expensive.”
So, what’s a traditional bank with a legacy business to do? Leverage those years of business experience, that’s what. “It’s not just about investment [but also] how are you going to put AI in the hands of your business experts. Because the way to compete with those [technology companies] is in the business playground, not the technology playground.”
‘There’s a lot of knowledge behind all those legacy systems. Any of these digital giants would kill to get that data!’
– BEATRIZ SANZ SÁIZ
On the one hand, banks are far behind when it comes to learning from applied analytics. “Any of the tech giants, they learn by the second. They get smarter by the second because they have implemented AI in the core processes. Banks, they don’t learn anything, with any customer interaction.”
On the other hand, the long-standing banks have something the fintechs don’t. “There’s a lot of knowledge behind all those legacy systems. Any of these digital giants would kill to get that data!”
It seems that Sanz Sáiz is still, like the graduate from the start of her story, urging banking leaders to modernise and make the most of the tools available to them. Far from a green dog, though, she’s now a leading expert in doling out this advice. Will they listen?
“I think there’s an opportunity. But they need to run. They need to run like crazy.”
Want stories like this and more direct to your inbox? Sign up for Tech Trends, Silicon Republic’s weekly digest of need-to-know tech news.