The CEO of Aboitiz Data Innovation explains how we can harness the power of data and AI, moving beyond algorithms, to achieve tangible, impactful results.
Category
🛠️
LifestyleTranscript
00:00AI is about information.
00:04Just having information theoretically is meaningless.
00:06It's how you use that information which becomes important.
00:19Now what does digitalization mean?
00:21It means, again back to being a geek, more data, more digital touch points.
00:28So the question was, what can we do more?
00:31Where can we go beyond?
00:32Can we truly maximize these opportunities, these data opportunities, using more sophisticated
00:38techniques such as machine learning and AI to better understand our customers, better
00:43engage, sharpen our service offerings, enhance our defense, et cetera, everything.
00:49So that's how this journey started, and in fact we incubated ADI, avoidance data innovation,
00:53I would say in the bank, because we were able to demonstrate practically how AI isn't
01:01just a, it's not just a marketing fanfare.
01:04It's not just a, oh look, you can do AI, but how this can be operationalized, how it can
01:11be truly used by the business, and how in the end of the day it makes a material impact
01:17that can be measured.
01:19And by doing that, it effectively resulted in the question of, ooh, can we also do this
01:25in power?
01:26Can we also do this in food?
01:27Can we also, can we do it elsewhere?
01:37When you speak to companies out there, and in fact I would challenge you now, go speak
01:40to anyone out there and say, are you doing AI?
01:43I'm pretty sure that most people, most organizations would say yes, but then if you ask another
01:49question of, are you using it?
01:51Is it in production?
01:53Is the business making decision based on the output of these AIs?
01:57I would suspect, I may be wrong, that's going to be a bit of a tip-off.
02:01Suddenly you'll be like, no, we're still experimenting, it's all in sandbox.
02:05So now if you think about that, the true challenge isn't actually data, it is an AI.
02:12It's how do you make it work?
02:14How do you make it real?
02:15How do you take a concept into something that is business relevant?
02:21And what we realize is that that's not a trivial question.
02:24Yes, doing the scientific stuff, the engineering, the technology, building, absolutely, and
02:29we do that.
02:30But it's that step which becomes extremely critical of how do we result in it being used?
02:38How do we operationalize it?
02:40So ADI, when it was formed, and because it was formed and incubated within the conglomerate,
02:45wasn't just about we're going to bring smart people together with technical know-how to
02:51do data and to do AI.
02:54But we're also going to focus on that existential question of how do we make sure that the business
02:59is able to maximize the value?
03:01And what is it that it takes to do that?
03:04Whether it is a matter of process, whether it's a matter of elements, sometimes culture,
03:08sometimes it's an element of other things, and also the big question of do you even need
03:15to use AI?
03:16Sometimes it's a very simple step that's necessary.
03:28So look, I want to start off by saying I do not want to discredit or sideline people's
03:36concerns and fears.
03:37I think that would be unjust.
03:42What I would want to do is I want to address that and say two things.
03:47One, anything new can be at times a bit scary, can be a bit alarming, doesn't mitigate the
03:54necessity to focus and address those risks.
03:58But I take comfort if you purely look at our history as a species, we've been able to,
04:06in fact, that's the amazing thing about us, we constantly evolve, we constantly adopt
04:12new things.
04:13I remember I was talking to someone who said to me, oh, but it's going to impact us.
04:16And I looked at them and I smiled and said, I'm pretty sure when even you in your young
04:2020s or late 30s, iPhones didn't exist, you seem to be perfectly fine.
04:25Didn't take away your job.
04:26There's still work.
04:27We can adapt.
04:28It is sometimes difficult seeing the future with the lens of the past.
04:33So that's number one.
04:36Number two, because there are risks and to innovate, you must have governance.
04:42That is why we must have governance.
04:46If we go about and like imagine you start driving in the road without any potential
04:50rules or any potential guidelines or good practices and there's an accident, well, should
04:54we be surprised?
04:56It's not that we shouldn't drive.
04:58It's that we should make sense that we apply common sense and put mitigating controls along
05:03the way that we're able to value and appreciate and enjoy driving.
05:08And then thirdly, and in fact, I was going to say to you, one of the questions I used
05:11to get is, I used to get David, is AI going to be, you know, is it going to take away
05:15all our jobs and going to be the end of humanity?
05:18You know, there's this existential end of the world type of question and I usually smiled
05:23again not to discredit and say, look, if we research, if we, you know, implement and we
05:29deploy AI that is inherently designed to replace us, if one day in the future it replaces
05:36us, we shouldn't be too surprised.
05:39If we research, implement and deploy AI that is meant to augment us, it is meant to help
05:44us in doing things, again, let's not be naive.
05:48Will it take away certain functions?
05:50Yes, just as any technology has in the history, but it would augment us.
05:57If you take the mindset of, oh, okay, I no longer have to do this operational task,
06:01but I now have to think about what are the other things that need to come, challenge
06:06us from a creativity point of view, then guess what?
06:10We're going to go to that next level.
06:12And then as a final point, which does touch as the element of jobs, I'm a data person.
06:20In 2019, I commissioned one of the, actually first, to my knowledge, first in the world
06:26studies that looked into the depth of financial services and the impact of not just AI, but
06:32also automation to jobs.
06:35The outcome was conclusive.
06:37It's going to impact tasks, not jobs, but a job is comprised of tasks.
06:42So if all the tasks can be automated, then sure, it will impact the job.
06:46But actually what you found is that the job changed.
06:50You still needed someone in a branch, but what they did is not the same thing that they
06:56previously did.
06:58So the responsibility and the call out is to employers.
07:03We need to make sure we provide the skillsets and we train everyone.
07:07And as I quote, UBP CEO Edwin Batista, I love this quote is, there is space for everyone
07:14in the bus and we have to give the opportunity for everyone to get on the bus, but then it's
07:19everyone's choice whether they want to get on the bus.
07:22So I'm cognizant of risks, hence the necessity to mitigate, but not only do I think the future
07:31is bright, I think this is the catalyst for us to become better.
07:45Philippines has a vast, vast range of opportunities that can benefit from the applications of AI.
07:55Quite a few number of years ago, I was asked by a reporter, David, why are you so public
08:00about what you're doing?
08:03I mean, shouldn't you be keeping it hidden and just enjoy it?
08:07And my point has been, no, I want the industry to know because the only way for the industry
08:14to progress is by the industry progressing, not just one party of the industry.
08:20The point being is, everything that I've spoken about, whether it is the financial services,
08:24whether it's power, shrimp, everyone can do it here.
08:29And the delta of improvement, the delta of revenue, the delta of efficiency, the delta
08:34of value is potentially significant here.
08:39It's a question of doing it and willing to put the investment into it.
08:42That's number one.
08:44Number two for ADIs, for the first two years of our existence, we were singularly focusing
08:50on our companies, the group's companies.
08:54And for the last several months, nearly a year, we have been able to create a demonstrative
09:03number of use cases and samples of AI, of data that has been deployed or is in the process
09:09of being deployed.
09:11As part of that objective to help the industry, we want to do it for others.
09:15We in fact are doing it for others.
09:17And not only in Philippines, in Southeast Asia, in fact, even slightly on the verge
09:23of Asia.
09:24And that's one of the goals is, I truly believe that one of the exports of Philippines could
09:30be the know-how of making AI work.
09:36We're already doing it, but we've just started.
09:39It could be a lot more, and it could be for others as well.
09:49One of the biggest challenges in AI, and I've said it from board directors all the way to
09:54managers, is that it's not guaranteed.
09:56AI is about information.
10:01Just having information theoretically is meaningless.
10:03It's how you use that information which becomes important.
10:07Whereas the mindset should be that of education.
10:10I am investing in this in my future.
10:14And I guarantee you, as I guarantee to anyone who does it with this mindset, within months
10:19there will be a number.
10:20But the starting point is a starting point of, dare I say, faith.
10:26And that's the challenge.
10:27That is the real challenge.
10:28It's not even about how much money.
10:30That's willingness of, I am putting this on the table to potentially make myself better.
10:36And for those who do it, it pays back.
10:41It pays back.