- 20 minutes ago
Will artificial intelligence create more jobs than it displaces?
As AI continues to reshape the workplace, the Philippines faces a crucial question: Are Filipino workers ready for the jobs AI will create, or are we heading toward greater job displacement?
Join us on Beyond the Headlines as we discuss AI, jobs and the future of work with Matt Watson.
📺 Beyond the Headlines — Look Deeper. Think Deeper.
As AI continues to reshape the workplace, the Philippines faces a crucial question: Are Filipino workers ready for the jobs AI will create, or are we heading toward greater job displacement?
Join us on Beyond the Headlines as we discuss AI, jobs and the future of work with Matt Watson.
📺 Beyond the Headlines — Look Deeper. Think Deeper.
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NewsTranscript
01:30Then comes the milk, steamed smooth, creamy, and balanced.
01:35The perfect latte is not brushed.
01:38It is crafted one cup at a time.
01:41Your perfect latte is ready.
01:44Coffee first, then everything else.
01:47How many Filipino jobs can AI replace?
01:52Good afternoon.
01:53Welcome to Beyond the Headlines.
01:55I'm DJ Moises.
01:56And shout out to Coffee First for supporting conversations that matter.
02:01So artificial intelligence or AI will create more jobs than it will displace.
02:06But there is no guarantee that the people displaced by AI will have the skills to do the job AI
02:14creates.
02:15That's why economies head to two possible directions.
02:19The age of co-pilot, where AI amplifies human capital.
02:23The other direction is the age of displacement, where jobs are lost to AI.
02:28So where is the Philippines headed?
02:30Where is Cebu headed?
02:31Let's look deeper and think better.
02:35Today, we're talking about the future of work with Matt Watson, entrepreneur, technology executive, and founder and CEO of FullScale.
02:43So hello, Matt.
02:44Welcome to Beyond the Headlines.
02:46Hey, thanks for having me.
02:48And I hope I can get some of that coffee first.
02:50I always need coffee.
02:52When you will be here, you mentioned earlier that you will be here in December.
02:56So we'll make sure that you get to have your coffee first.
03:00Awesome.
03:02Yeah.
03:02So thank you for making time for this conversation.
03:06Because we're going to talk about the current state of the ITBPM industry in the Philippines.
03:13At least the industry, how you know it, as you know it.
03:19So roughly in the Philippines, the industry is employing 1.9 million people and has been generating annual revenue of
03:28$40 billion.
03:31So when you look at the ITBPM industry currently, how vulnerable is it for AI to actually displace a portion
03:42of the work that's being done in Cebu and the Philippines?
03:47Well, I think from my perspective, you know, software developers have been spending the last three, four, five decades trying
03:57to replace everybody else's jobs.
03:58That's what software developers have always done, right?
04:00And, you know, we figure out how to automate things, streamline things, all that kind of stuff, using technology.
04:07And AI is just the newest tool to help do that, right?
04:12But what's interesting about AI is people are more specifically worried about how it replaces software developers, which is probably
04:19a first, right?
04:20Like, we're usually replacing everybody else's jobs or automating other people's jobs.
04:23And now everybody's worried about it, how it affects our jobs.
04:28So it's a very interesting time.
04:32And, you know, at FullScale, we have about 300 software developers that work for us.
04:35So we see this, you know, firsthand every day and the effects that we're seeing from it.
04:42So the IMF actually says that one-third of Filipino workers are highly exposed to AI.
04:52If you are to translate this the way you view it, what does highly exposed actually mean?
04:59Yeah, I would say the way I would describe it is you have to think about is your job a
05:08set of tasks or is your job where you own figuring out what those tasks are to do, right?
05:15And if you're just the person who just does the tasks, then you're the one who is exposed, right?
05:22You're the one that is likely to need to be upskilled or be replaced or at risk, right?
05:28But if you're the one that is using that human judgment to figure out what work needs to be done
05:33and how we do it, how we solve the problem, what tasks need to be done,
05:37then you know what, you have more work than you've ever had to do before because AI is creating more
05:42work for us in some ways.
05:44But yeah, it's the people that are just doing the tasks that are the ones that are exposed.
05:52So some companies are hiring, you know?
05:55So that means that with artificial intelligence, they have more work to do.
06:02But some companies also are reducing headcount, which also would tell us that these companies potentially have the type of
06:12work that's being automated or being made efficient because of artificial intelligence.
06:19In your view, what should a company do so that the company will be heading towards expansion rather than reduction?
06:31Yeah, I think it's a mixture as a company.
06:35We're always trying to figure out how to cut costs and provide a better service for our clients.
06:41And, you know, for example, you talk about the call center side of things, right?
06:47I know there's obviously maybe a million people in the Philippines that work in call centers.
06:53You know, I was talking to somebody that was trying to automate phone calls for a law firm.
06:58And I asked him why.
07:00I'm like, somebody who has major issues in their life, needs to talk to a lawyer, wants to spend a
07:05lot of money on a lawyer.
07:07They don't want to talk to AI.
07:09They want to talk to a human being.
07:12And, you know, they don't want their first impression of calling a lawyer that they talked to some AI bot,
07:18right?
07:19And as a lawyer, I think they can probably afford to pay somebody to answer the phone.
07:24You know, I mean, lawyers make a lot of money.
07:27And so I think, you know, there are certain types of industries and phone calls and stuff like that that
07:34I just can't see handing it over even to AI.
07:38Now, I think there are other things I think a lot of us would love to hand over to AI.
07:42Like, I don't want to go and press one, press two, press three through the menu prompts and then talk
07:47to somebody and all this junk.
07:49Like, let me just tell AI, cancel my account.
07:51I'm done.
07:53Like, I think there are some places where we would all actually appreciate it.
07:57So, you know, I think it's a mixture of all the things.
08:01And I think the other thing that people have to remember with AI is it's making it easier and cheaper
08:09to do things that before, as a business, we wouldn't have done or wouldn't have justified to do.
08:14But now we're doing them like we're doing more work because we can do this work now or before I
08:21wouldn't have spent, you know, I wouldn't have hired somebody full time to do this work.
08:25But now because of AI, I'm able to do additional things.
08:28Right.
08:28Like I'm investing in different things that before wouldn't have made sense before AI.
08:33Does that make sense?
08:34And so I think we're also going to see more investments in things because of AI as well.
08:40So in the Philippines, if we look at the ITBPM landscape, about 80 to 90 percent of what we do
08:49here, and that's also true even here in Cebu, are either call center or voice work or back office work.
08:56And we all lump them into rule-based work.
09:00Some people, they call it transactional work, but I think it's more relevant now to call them rule-based work
09:07because these are also the type of work that are readily going to be automated for the purpose of efficiency
09:19and being effective in the type of process that we are handling.
09:24Are you seeing this trend to continue in, let's say, in two years or three years that much of the
09:31work that's being done in the Philippines will be largely rule-based?
09:36Well, I mean, it's really hard to predict the future of all of this, right?
09:41And, you know, as we mentioned earlier, I think the people that are doing a lot of repetitive tasks are
09:47the ones that are highest at risk.
09:49And software developers have been trying to automate those things forever.
09:53Yes.
09:54But what's interesting is because of AI, we're able to do even more.
09:59And I think what most people find from using AI is you need a human in the loop a lot
10:04of times to still review what it does and approve it.
10:10But, you know, it's really hard to predict the future, and I think we're going to see the answer to
10:15all these things is actually yes.
10:16I mean, some people are going to lose their jobs, some people are going to be upskilled, some people are
10:20going to have new jobs.
10:21But companies are also going to have more work to do because of AI and technology.
10:29And I think that's largely been the case.
10:31When technology has been more affordable, people use more of it.
10:36I mean, that has been the history of things.
10:39When things become more affordable, it just gets used more often.
10:44So the dynamics in the Philippines, correct me if I'm wrong, at least from your observation, is we tend to
10:50be more of a consumer, consumer of technology rather than being creators of technology.
10:56So in the context of artificial intelligence, Filipinos tend to be consumers of generative AI such as chat GPT, for
11:08example, but not necessarily developers of AI, which is probably very different from what you're seeing in full scale.
11:16But at least if we are to look at more Filipinos being consumers rather than creators of technology or, in
11:24that case, artificial intelligence, what do you think we need to do or what type of mindset do we need
11:30to change for us to move to the higher value chain?
11:36Well, at full scale, we're building lots of stuff with AI for our clients.
11:41So we've got a lot of Filipinos building a lot of very advanced AI-oriented software for our clients, which
11:48are largely U.S.-based companies.
11:51They're not Philippines-based companies.
11:53But I think from a software development perspective, what we see is basically everybody has to move up one step
12:02in their job, if that makes sense, where a lot of software developers worry about each line of code and
12:07what the code did,
12:08where now they have to step up one step, where it's like we're not worried about the lines of code
12:14anymore, we're more worried about the architecture of how the code works,
12:19because I can just ask AI to write those lines of code, right?
12:21So, and I think in a lot of things, it's like everybody's going to have to upskill and move kind
12:26of one step up.
12:27And again, it's having the judgment and the job is knowing like what the job is to do.
12:34How do we solve this problem?
12:36And then I may be asking AI to go do the work, but I'm still helping decide what needs to
12:41be done.
12:41And I think that's going to be the lift is a lot of people are going to have to move
12:47up that next step.
12:48And the challenge is a lot of people have never had the opportunity to do that before, right?
12:52And so that is the challenge is do they work at a company right now that understands that and is
13:00letting them move up to that next step,
13:04giving them the opportunity to do that work?
13:07Does that make sense?
13:07So for Filipinos who are working in a call center at this time,
13:14and I know that you mentioned earlier that we cannot really like 100% make a forecast,
13:20but at least on what you're seeing on the development side,
13:24how soon can contact centers be able to, or those working in contact centers,
13:32be able to see the change in their work with the development such as AI?
13:39Around when will they significantly see that?
13:42Will it be like next year or three years from now or still five years from now?
13:48Well, I think there are clearly already AI technologies that can do pretty cutting edge stuff from call center kind
13:57of stuff,
13:58be it outbound calls, handling inbound calls.
14:00I know people that have companies that do some of that kind of stuff and have heard lots of stories
14:06from them.
14:08But it may take three to five years before people would even sign up for those products and implement them
14:14and use them and all that kind of stuff, right?
14:16I mean, it could take years for companies to even adopt that kind of technology.
14:20But I want to bring up something else I think that's a big problem here.
14:24So imagine you work in a call center and you work for a telephone company or whatever.
14:29You get 200 calls a day, whatever it is.
14:32And maybe five or 10 of those are angry customers.
14:35Those are hard conversations to deal with, but they're spread out across the day.
14:39Now imagine AI handles 190 of those calls a day, and now all you get is 200 angry customers.
14:51Can you imagine now that that's your job?
14:53Like, no, you can do that.
14:55Yeah.
14:57I mean, that's part of the reality this year, too, is like there's this, you know, as human beings, like
15:04we work eight hours a day.
15:05But, I mean, let's be honest, maybe for some of us, four, five, six, seven hours of that work is
15:11relatively easier work.
15:13And maybe we have one or two hours of like really hard work a day.
15:16That's stressful, difficult work to do, right?
15:19The other work is important, too.
15:20Don't get me wrong.
15:21But maybe there's like really stressful work for like an hour or two a day.
15:24But if AI removes a lot of that easier work and all you had left was eight hours of stressful
15:29work, like none of us would be able to do it.
15:33Does that make sense?
15:34Yeah, actually, this is the first time that I heard insights like that.
15:41And thank you for bringing that up today because you were right.
15:43Because if artificial intelligence will be managing the straightforward type of work, the rule-based type of work where there
15:53is not much decision that's required, then these are also what we call easy type of calls.
16:00So, yeah.
16:01So, if AI will handle this, then what goes to a human are now the more complex and more stressful
16:08type of work.
16:09And in that case, some of them would be already angry customers.
16:13Yeah.
16:14And ain't nobody going to handle that for eight hours a day or whatever.
16:17There's just no way.
16:19You mentioned earlier about upskilling.
16:23There's not much.
16:24Well, in the Philippines as of this time and in Cebu as of this time, we know that there is
16:29a need to upskill now.
16:31But can you also give us more insights or suggestions about what type of skills should we upskill ourselves to?
16:42You know, so on the software development side, it's relatively straightforward, right?
16:47It's like our developers have to learn how to use AI to build software, which enables them to build software
16:52somewhere between, you know, 50% faster to 500% faster, right?
16:57Depending on the type of work and their skill level and all that.
17:00And so, it's pretty easy to see, like, okay, everybody needs to learn to use the technologies, be it Cloud
17:06Code or ChatGPT, all the different things, all the different tools.
17:12And our employees are actually probably sick of all the training.
17:15We have, like, nonstop training on how to do this stuff.
17:18And so, for our employees, for software developers, I think it's pretty straightforward.
17:22You have to learn to use these technologies and, you know, either you're going to kind of keep up or
17:29you're just going to get left behind.
17:30But if you work in a call center and you're like, hey, all I do is I answer phone calls
17:35all day, like, I don't know how to upskill, like, myself.
17:38Like, I don't know what to do.
17:40I see that's a totally different, totally different than where we're at with the software developers.
17:44Like, if you're in that role, I'm not sure what you can do as an individual.
17:48It's going to be your employer is going to have to help create those new opportunities for them and say,
17:53okay, well, how can I upskill?
17:55How can I learn to use AI?
17:57How can I be more productive and more valuable to the company?
18:01I feel, I don't work on that side of it, but I feel like, you know, they're a little more,
18:06you know, at the mercy of their employer on, like, how this is going to affect them and how do
18:12they do that upskilling.
18:13Where software development, I think, is a little more straightforward.
18:16So, by the way, for our viewers, just in case they get distracted by some of the photos we're showing,
18:22we're showing those are actually AI-generated photos.
18:26So, at least they get the context.
18:27Why are we presenting photos of kids or images of kids?
18:32But anyway, going back to the topic, well, I've also heard that at least companies like Full Scale, and you
18:39mentioned it also, are doing your best to move your developers into the higher value chain so that they would
18:48continue to be relevant.
18:49But in your observation, at least in the Philippines or Cebu in general, do you think in the context of
18:56upskilling, we are moving fast enough?
19:01I think so.
19:02I mean, from our employees that we worked with, I think absolutely.
19:06And I think the other thing to keep in mind is the type of BPO work and call center work.
19:14If you're working for an enterprise client, of course, is different than if you're the, there's a call center team
19:21of one or two that works for some company.
19:23That company is probably not going to make any changes if they only have one or two people that, you
19:30know, do this kind of work, right?
19:31It's totally different than some large enterprise.
19:33It's like, okay, we have 1,000 agents, and because of AI, we're able to go to 700.
19:37You know, that conceivably makes more sense.
19:40But if you're a really small company and you have one to five people, it's not that big of a
19:47benefit to try and eliminate one person or whatever.
19:50Like, you used to have a very small team and you value the very small team that you have, you
19:54don't want to lose any of them.
19:55But if you have hundreds of employees, I think that's more likely with like, okay, were we able to, you
20:00know, reduce 20% of the people or whatever?
20:02I can understand that.
20:04But my point is if it's, it's all the people that do BPO kind of work where they're very small
20:08teams, I see it having much less of an impact because as a company, like, I still need those people.
20:14Like, you know, if I have a marketing assistant, I still need one.
20:17I can't go from one to zero.
20:20Now, hopefully that one is more productive with AI, but I'm not going to go from one to zero, you
20:24know?
20:25Or the other piece also is they can go from five to three, for example, or five to one.
20:33Yeah.
20:33So there was one demo that was presented to me months ago, and it is the type of artificial intelligence
20:43that could translate what I'm saying real time.
20:49And I also have the option to change my accent now from American accent, British accent, depending on which accent
21:02I could actually, I would prefer to have with respect to the clients that I would be talking to.
21:09So for me, this type of AI actually could potentially replace a lot of call center type of work.
21:20But on the development side and what you're seeing in the U.S., because we've been hearing a lot of
21:26stories and development specific to artificial intelligence, which among these stories, at least from what you heard, are just hype?
21:35And which of these stories from what you're seeing are actually real?
21:42Well, that's the thing.
21:43I think all of it is hype, right?
21:46Like everybody hypes up all of this stuff, and it doesn't matter if it was a few years ago and
21:52it's blockchain and Web3 and, you know, there's always some hype of some new technology, right?
21:59And then what we all figure out ultimately is like, okay, where did it actually make sense to use AI?
22:04Like, where did this actually work?
22:06Like everybody thought it could do this and do this and do this, and it was going to be magical
22:10and all these things.
22:12And then eventually we try them and all the things, and we figure out where it's actually good at, you
22:16know?
22:17And it takes a little while to figure that out.
22:20And, of course, the media loves talking about it because it gets impressions and clicks and people talk about it.
22:27And the big AI companies, no doubt, love people hyping it all up because that, you know, drives adoption of
22:34their technology and their stock prices and everything else, right?
22:38So, so much of it is a hype-filled landscape, but the reality is most big technology decisions at a
22:46lot of companies potentially take years to make decisions and implement and all that kind of stuff, right?
22:52And especially large, you know, enterprises, you know?
22:56They're not going to adopt some crazy new phone system and call center stuff the first month after it gets
23:02rolled out.
23:02They're going to wait a long time to make sure it's a legitimate product, and then they'll slowly beta test
23:08it, and then they'll slowly use it, and it's a long process.
23:12You've been building software companies for more than 20 years now, so that means you've also seen so many changes,
23:22technology changes along the way.
23:23When you're seeing artificial intelligence now, is this giving you a different type of pace, for example, in terms of
23:33adoption?
23:34Or this is pretty much how the other technology developments also started from what you've seen in the past?
23:43I think the adoption of it is definitely much more accelerated, right?
23:47You know, I lived through when, like, cloud first became a thing, like, AWS and Microsoft Azure.
23:54I lived through mobile becoming a thing.
23:58Like, when I started building software for, like, cell phones before the iPhone existed, before Android existed.
24:04So, you know, I've definitely lived through some of these waves of technology.
24:09But definitely AI, I think, has caught on much faster than a lot of these things because it's so easy
24:14for everybody to just pick up and start using it and seeing immediate benefits of it, right?
24:21And it affects how we do day-to-day work.
24:24It makes us more efficient at our jobs every day.
24:29So, for sure, the adoption of it has been much faster.
24:34You've mentioned judgment earlier now.
24:37So, when a worker, as of this time, would do a certain task, you know, what do you think are
24:46the skills, you know, I think more specific, aside from judgment, does a person or worker needs to have so
24:54that he or she will never be or not be replaced by AI?
25:01Well, on the software development side, it's easy.
25:04It's understanding the customer and their problem and actually caring about it and having empathy for them and making sure
25:10whatever, you know, software solution you deliver created value for them and getting the feedback.
25:16And ironically, that's something that a lot of software developers aren't very good at or didn't do a lot of
25:23in the past because even software developers were more order takers.
25:27They're like, you know, here's the requirements, the specifications of what needs to be built, gets handed over to a
25:32developer and they would build it and then hand it back to the product team or, you know, leadership.
25:37Where now, that has all changed.
25:40Like, the developers have to be much more involved in understanding the customer, what the customer needs, because that's much
25:46more the job.
25:47If AI can write the code very quickly, figuring out what code to write is very much the job.
25:53And I actually wrote a book about this called Product Driven, and we, you know, train our employees extensively about
26:00all this.
26:00It's part of the upscaling.
26:01It's like, you got to think more, you know, less about the code and more about how it impacts the
26:05users, you know.
26:07And I think that's true for a lot of call center jobs, too, is, you know, it's all about the
26:13customer at the end of the day.
26:15So, well, it's unfortunate or fortunate.
26:19It depends on which side of the equation we are, you know, when we use the word vulnerable with respect
26:27to AI, you know,
26:29and in terms of the type of work we do, because vulnerability tends to associate itself from being attacked, you
26:35know.
26:35But for the benefit of this, for the context of this conversation, at least, because you've covered this in the
26:43earlier part of the interview,
26:46but at least in a nutshell, so that the viewers would be able to put them together or to be
26:51able to effectively synthesize them.
26:53What type of work, especially at least from what you're seeing in the Philippines, that are most vulnerable to artificial
27:00intelligence?
27:03Well, so let me tell you an example story that I hear and I see on LinkedIn is people will
27:11say, like,
27:13AI is going to replace offshore developers, like hiring developers in the Philippines or India and other places.
27:19And I always kind of laugh at that because I'm like, isn't AI going to replace any developer that just
27:27doesn't use AI?
27:28Like, developers in the Philippines and India can use AI.
27:32So it's not like, you know, only developers in the United States use AI and it's a magical thing and
27:38then, you know,
27:39there are no other developers in the world.
27:41Like, I don't understand why people say that, but that's the mentality that some people have.
27:45They're like, oh, because we use AI now, we don't need these, you know, offshore, you know, or outsourced jobs
27:52or whatever.
27:53But the reality is those people also use the technology.
27:56So if you want to hire a software developer, you know, in the United States, I mean, it costs five
28:03to ten times more money to hire them in the United States than it does in the Philippines.
28:07And you can hire developers in the Philippines that use AI, just like developers in the United States do.
28:12So, but people have this weird perception that, you know, that it's going to replace offshore outsourcing jobs.
28:20But that's not the case at all because all those people also use AI.
28:24Now, in terms of the gap between people who can work with AI and people who are yet to develop
28:31their skills to work with AI,
28:34as of this time, how, how wide or how narrow is the gap that you are seeing?
28:42I think the gap is understanding the business needs, right?
28:45It's understanding the business problem and how to actually use AI to solve it.
28:51And, you know, if you've spent your whole career with somebody telling you what to do, that's, that's the challenge,
28:57right?
28:57Because now we, we all have like, AI is our intern, we have to tell what to do.
29:03And so if you're not used to telling somebody else what to do, and you're used to somebody else telling
29:08you what to do, that's the challenge, right?
29:09Is we all have to change that mindset now of like, we all have an intern.
29:14And you can have like unlimited of them, actually, because you can, you know, ask AI to do endless amounts
29:20of things, basically.
29:23But yeah, it comes down to having the judgment, understanding the business, business problem to be solved, and knowing how
29:29to solve it.
29:30And somebody's got to trust you and give you ownership to go solve it, right?
29:34And so again, that from an employer, that comes down to hiring good people, training them and trusting them, giving
29:40them ownership to say, go figure out how to do this.
29:42How do we get better at this?
29:44And that really, that's a leadership thing at those companies.
29:47And now we're going even down to the, to the, to the talent chain, and I'm referring to students who
30:00are still in, in their primary, secondary education, and even those in tertiary education.
30:08What are the things that you would also want to suggest to the academe in general so that we would
30:15be able to produce also talents from schools and universities who are already AI enabled?
30:23I mean, of course, using, using AI and learning to use AI is important.
30:28I think some of it is also the, the big thing that we focus on internally is what we refer
30:35to as courage.
30:36It's training our employees that how critical it is that they speak up, ask the right questions, provide feedback.
30:44I mean, you can't just say yes.
30:46You can't sit around and wait for somebody to tell you what to do.
30:49If there's a problem, you can't, you can't sit there and be like, well, I don't want to be rude.
30:54I want to be respectful.
30:56I'm not going to say anything.
30:57You know, I don't want to make anybody mad.
30:58Like, it's your job to speak up and fix this thing.
31:02Like, and I think that's part of the culture barrier that we have sometimes and that we have to train
31:07our employees on.
31:09It's like, you've got to speak up.
31:10You know, you've, you've got to bring ideas.
31:12You've, you've got to be able to tell somebody like, there's a problem with this and there's a better way.
31:17And I think sometimes that's, that's one of the most important things that we have to train people on.
31:23And now we're moving towards the last part of our conversation, Matt.
31:28But before we let you go, I'll go back to the intro that we had specific to this episode.
31:35And, and there is, and studies would actually show that there will be more jobs that AI will create compared
31:45to the jobs that it will displace.
31:47But the same study would also show that there is no guarantee that the people who will be displaced by
31:54AI will have the, the skills that would be able to, that, that, that would allow them to do the
32:02jobs that AI creates.
32:03That's, that's why there are emerging schools of thought as of this time, that economies are said to be heading
32:11towards two different types of future.
32:14One is the, an economy heading towards the co-pilot economy, which would say that artificial intelligence is in fact
32:23amplifying human potential.
32:25While the other side is if, if, if, if countries don't prepare enough, then they could be heading towards the
32:32economy of displacement in which artificial intelligence will not necessarily replace the job that they do,
32:40but it will just reduce from five people or 10 people initially doing the job to a much more streamlined
32:46or reduced number of people because of the efficiency and, and even speed that AI actually is, is, is, is
32:54allowing, you know, a process to, to be transformed.
32:57So in this context, then, if we look at the Philippine situation, or at least Cebu from what you're seeing,
33:02are we headed towards, uh, the, uh, economy of co-pilot or are we in danger in terms of heading
33:11towards displacement?
33:13I mean, I think it's both. I think it's a mixture of both. Right. I think the biggest companies are
33:18going to figure out how can they optimize and get more done with less people.
33:23But I think smaller companies like ours, we have all the tools, we have all the AI. We're just trying
33:29to figure out how do we do more? You know, we want to do more things like our marketing team.
33:33How do we do more and more and more things?
33:35Because, you know, now the marketing person we have is more efficient. So how can we ask them to do
33:40additional work? And because of AI, we're like, well, now maybe we need another marketing assistant. There's so many things
33:46we could do that we couldn't do before. So I think honestly, I think it's always going to be a
33:51mixture of both. And we're going to see both of them play out at the same time.
33:54But like I said earlier, like software developers, our job has always been to optimize things and replace other people's
34:01jobs because of technology. That's what developers have always done is figure out how to streamline things. Right. So it's
34:09a mixture of both.
34:11That's my bet.
34:13Yeah. So now this is the last question. And I just also wish that you could also articulate something for
34:23our government leaders and business leaders and policymakers who are watching.
34:29What are the areas also that we should start doing now? Or if we are doing them now, what we
34:36should be doing more of moving forward?
34:41Well, I mean, from a business leader, you know, it's always making it as easy as possible to do business
34:48in the Philippines. Right. Make it as easy as possible for us to hire people and do business in the
34:55country. Right. I think that helps create jobs more than anything else. Right. Make it easy to do to do
35:00business there.
35:02But of course, training, the education system, the training, all that kind of stuff.
35:08Probably one of the most important things they could do in Cebu to help the economy is traffic.
35:16Everybody's tired of that topic, but you have to spend money if you can't drive down the street and spend
35:20it.
35:22Well, that's that's that's that's a that that's a statement in a nutshell.
35:27Yeah.
35:28So thank you very much, actually, Matt, for your time. It's evening right where you are, but you're making time
35:34for this show and for giving us a clearer picture, at least of the future of work.
35:41Yeah. Thank you so much for having me. And, you know, we have hundreds of employees in Cebu and we're
35:45a great place to work and, you know, always hiring and continue to grow our business here.
35:50Thank you so much for having me.
35:52Yeah. And then and all the best, because it looks like your company is among those that's headed towards the
35:57co-pilot economy.
35:59Hope so.
36:00OK, so thank you very much, Matt.
36:04So for every job artificial intelligence may eliminate, there may be new opportunities for people who are prepared to work
36:11with technology.
36:13AI is already here. And the question is whether we will be ready when it reaches our jobs.
36:20Because the countries that prepare their people today will have more choices tomorrow.
36:26I'm DJ Moises and shout out to Coffee First for supporting conversations that matter.
36:31Let's continue to look deeper and think better. Have a good afternoon.
36:41It starts with a fresh shot of espresso.
36:45Bold, rich, bold, just right.
36:50Then comes the milk, steamed smooth, creamy, and balanced.
36:55The perfect latte is not brushed.
36:58It is crafted.
37:00One cup at a time.
37:02Your perfect latte is ready.
37:04Coffee first.
37:06Then, everything else.
37:08Coffee first.
37:11Coffee first.
37:27Coffee first.
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