- 4 months ago
The Philippines has long been a global powerhouse in IT-BPM/BPO—but the rise of AI is changing the game.
Are we still leading, or are we starting to fall behind?
Join us with Gregg Victor Gabison, Country Manager at Ray Business Technologies, as we unpack what AI means for millions of Filipino workers—and what it will take to stay competitive in the future of work.
📅 Don’t miss this conversation. The future starts now.
Are we still leading, or are we starting to fall behind?
Join us with Gregg Victor Gabison, Country Manager at Ray Business Technologies, as we unpack what AI means for millions of Filipino workers—and what it will take to stay competitive in the future of work.
📅 Don’t miss this conversation. The future starts now.
Category
🗞
NewsTranscript
00:34Good afternoon. Welcome to Beyond the Headlines. I'm DJ Moises.
00:38The Philippines is the second biggest IT BPM or BPO industry in the world.
00:43It created millions of jobs and powered our economy.
00:48But today, AI is rewriting the rules.
00:51Are we still leading or just catching up?
00:54Or are we even catching up?
00:56Joining us today is Greg Gabison, Country Manager at Ray Business Technologies, who brings value, valuable insights in today's conversation
01:05on the future of the IT BPM or BPO industry in the age of AI.
01:11Hello, Greg. Welcome to Beyond the Headlines.
01:13Thank you, DJ. And thank you for this opportunity to be in your show.
01:17I really was looking forward to be in one of your sessions or show, actually.
01:22And this is the perfect opportunity.
01:25I believe so. I believe so.
01:27Because we're going to speak about a topic that's about possibilities, but at the same time, risks.
01:35And I'm talking about artificial intelligence.
01:38So earlier this year, Vinod Khoshla, so he's a venture capitalist in Silicon Valley, says that AI could wipe out
01:46BPO and IT traditional services job in five years.
01:52Is this a bold prediction or an uncomfortable truth?
01:57I would say I'm leading to the other half of it, which is really something that we have to be
02:05aware of.
02:06So I'd like to speak from a digital transformation perspective.
02:11I just don't I do not see AI only as a threat to outsourcing, but it's also something I'm seeing
02:19this one as a wake up call.
02:20And it's actually forcing everyone here in the Philippines from BPO, outsourcing, IT, even to the government and universities.
02:30All these workers, all of us have to rethink how we are going to present Philippines as a work destination.
02:37And let me just tell you this one.
02:39If we are to stay in a low, complex, repetitive work, we are very much vulnerable to getting disrupted by
02:51AI.
02:51I don't want to use the word replaced, jobs being replaced, but I'll journey with that later on.
02:57But what we would like to do, and I would like to say this one as a means of getting
03:02an idea of where I'm driving at,
03:04is that we should be moving towards an AI-enabled services, domain expertise, analytics, cybersecurity, cloud, and human-in-the
03:15-loop operation.
03:16And by doing that, we can really move up to the value chain.
03:21So, yes, it's also part of the set question here now about how vulnerable AI, but I'll backtrack a little
03:29bit this time
03:30because this is also a question that keeps me awake at night.
03:34And this is every time I would see literacy figures, like the most recent and the clearest description is 21
03:44% of our senior high graduates are functionally illiterate,
03:49meaning they have trouble with reading, writing, comprehension, in a manner that's enough to get them by in their daily
03:59lives.
04:00In short, what is really like enough to get them by?
04:05It is a task as simple as filling out a form.
04:08Okay.
04:09Okay, you read, you write, and then you comprehend.
04:12There's a struggle there.
04:14That's 21% of our senior high.
04:16So now, graduates, so now that we are moving towards more sophisticated tools like artificial intelligence,
04:25what are the things that we should do, at least to manage that growing gap?
04:33Because at least for the last number, literacy is not getting better.
04:36It's getting worse.
04:38And AI is becoming more sophisticated.
04:41I don't want to sound political, DJ, but there has to be some government intervention has to come in.
04:50And it's just about literacy delivery, but rather it's a holistic kind of approach that has to be done.
04:58From the perspective of higher education, they're trying also to check out or improve the general education,
05:06which there will be a public hearing about it in the coming days.
05:10I don't want to spill away the thunder from that, but I know there's something that's being worked out.
05:16But going back to the basic education structure, I believe there's a need really to review again.
05:25And other than the content, it's about how we are strategically delivering and enforcing these things.
05:35When I say these things, it's both content and how we are actually arming the teacher themselves
05:42and how these teachers are actually cascading what they're supposed to do to the students.
05:47It's a bit too summarized, but if there would just be a way to really review that,
05:53because they have a very good system, but there's just a need to really review it.
05:59And I believe so, you can work things out for that.
06:02And at least it's a comfort from my head.
06:05There's movement in that area.
06:08So let's go back then to what you just said.
06:10The ITBPM industry or the BPO industry in the Philippines,
06:15they're 80% to 83% call centers or rule-based type of work,
06:24which this type of work also happens to be most vulnerable when it comes to automation and AI.
06:32So in your opinion, at least from what you're seeing,
06:40how exposed are we now to the disruption of AI?
06:49We're very much exposed.
06:51I have to be upfront with that.
06:52And if you say, like, when is the best time?
06:56It should have been yesterday.
06:58I have to be upfront because in the company where I'm in right now,
07:02we've been operating in the Philippines for five years,
07:04but as a company, Ray Business Technologies has been in the operation for about,
07:07this is actually our 16th year of operation.
07:10And our focus is really to help organizations streamline their operation.
07:19And one of the things that we're doing it is simply to automate that entry-level part of their,
07:25especially on the customer service engagement.
07:28And in that customer service engagement,
07:30I know that there are lots of jobs in the Philippines that touch on that particular task.
07:35I just imagine if you take off this particular task,
07:38what would be the result of that?
07:40You're actually going to, unfortunately,
07:43disrupt or displace some of these guys working specifically on that aspect.
07:48The common question also there in relation to what you just said is,
07:52everybody knew like 10 years or even 15 years ago that we have to upskill.
07:59But at least from what I'm seeing, and correct me if I'm wrong,
08:01through overtime, there's little that's been said about upskill to what.
08:08We just have to upskill.
08:10We just have to adapt to artificial intelligence,
08:13but adapt specifically to what.
08:16So now with the majority of the IT BPM or BPO industry is at risk.
08:23If we don't do anything significant from now on,
08:26what are the jobs that if a call center agent is watching,
08:33what are the jobs that he or she could enable herself to stay relevant?
08:40I would like to answer this from this perspective, DJ.
08:46So just like what I've said, those routinary, repetitive tasks,
08:52like answering FAQs, I mean, answering based on FAQs,
08:56answering queries from very menial contexts,
09:03both email and even calls or chats,
09:08these are most likely going to be disrupted.
09:10That's a fact.
09:14How they can pivot.
09:16I just would like to be very specific to it.
09:19So example, you're an agent who knew this one.
09:21But let's say, for example,
09:23this BPO would actually be moving forward, infusing AI.
09:28So what would be your role after that?
09:30You know, the very good example,
09:32I would like to take this one from a very exact use case
09:39from the company where I'm in.
09:41So we had this client before.
09:43They had issues in answering emails, just simply emails.
09:49At that time, at their present setup,
09:52only two out of three of the 10 emails were answered
09:55by their human customer service agent.
09:58So imagine seven to eight other emails are not being answered.
10:03So that's a very low statistics.
10:06When we presented our product, we call it ION.
10:10I'm not going to market it, but basically just to set an example.
10:13The result was overnight, immediately,
10:16although the time that elapsed to give an answer
10:20was about two minutes at the time for a very simple question.
10:23But in terms of accuracy and being able to answer,
10:28it was nearing 100%.
10:29So what does it tell you?
10:31So AI really works.
10:33But what would be the role?
10:34So what would be the role of these agents?
10:36Actually, what happened was they were there to be on standby
10:40if there are escalations or something that AI could not be able to answer,
10:45which is very true because that particular role requires judgment,
10:50requires empathy.
10:52Those are the things that AI cannot replace.
10:57And we have those guys.
11:00And also from a perspective of, remember,
11:03these agents of ours, BPO agents of ours,
11:06from a functional perspective,
11:08they're very aware of their tasks, their roles,
11:13with respect to the company that they are servicing.
11:17So from that aspect,
11:19we can have this one as functional consultants.
11:22And the other question, I'd just like to dive in,
11:24what would be those skills that they need
11:27if they're made to move up the ladder?
11:30A lot, and I would like to take away this thinking that
11:33you have to be a computer science guy.
11:36You have to be an IT guy.
11:38IT guy, partially, but not totally a computer science guy
11:43wherein you have to dig deeper,
11:45you have to go deep and understand the context of computer science.
11:48Don't do that because that would take another four or five years.
11:51But it's simple.
11:53No, no, I don't want to use simple.
11:54It's quite straightforward.
11:55Doable.
11:56Doable.
11:57You just have to make sure,
11:59well, your role will, since you know the process,
12:01all you have to do is we have this role as the analytics,
12:06an analyst.
12:08So all you have to do is that
12:10given those information that AI has produced,
12:13you have there those information in front of you.
12:16And it's your call.
12:18You have the function to determine whether,
12:21I mean, to help your clients whether,
12:25what to do next.
12:26That would be the kind of role that you can play.
12:28And then the next question that I will be asking,
12:32so this is,
12:33I was about to say I'll use qualify,
12:35but it also sounds quantify,
12:37so it depends.
12:38But whenever people say in the past
12:41that artificial intelligence is not going to replace human,
12:45from my observation, it's true.
12:48But instead of needing five people,
12:52you just need two.
12:54Because efficiency has already been introduced.
12:59So technically,
13:01there is some replacement that's happening.
13:05Technically.
13:06And then yesterday,
13:07I don't know if I forgot to tell you about it,
13:10but I also watched a documentary on YouTube,
13:13and it's a legit source.
13:15Okay.
13:16Part of the persons interviewed in the documentary
13:20used to work as a QA.
13:22Okay.
13:22And because listening to the call
13:25and auditing the calls according to parameters
13:30can be done already by a robot,
13:33so she lost her job.
13:37So in that context then,
13:41and then by the way,
13:42part of the things that she also shared was
13:44little digital because she's one of the best QA,
13:46at least from what she said.
13:47Okay.
13:48She was in fact teaching AI.
13:50Okay.
13:51In fact,
13:52she's teaching AI.
13:53And then by the time AI became ready,
13:55it's her role
13:56that was replaced.
13:59So as we move forward with AI,
14:01there are certain,
14:03I don't know,
14:03misconception,
14:04or this is valid,
14:05empathy,
14:06which you mentioned,
14:07and communication,
14:08and cultural alignment,
14:10these are things that AI cannot replicate,
14:16about what a human can do.
14:18But as AI will continue to learn,
14:20do you think the gap will continue
14:22to still be significant?
14:25I could not really tell
14:27in the next 10 years,
14:29probably,
14:30because as we are seeing
14:32how fast technology is evolving.
14:34But one thing is for sure,
14:37at the end of the day,
14:39the human factor
14:40is still very critical.
14:41That's a fact.
14:42And I would like to go back
14:43to your example
14:44on the QA role.
14:47I'm seeing it from a,
14:49my experience
14:50and the way I see it
14:51is that their role
14:53will even become more,
14:56they would be doing more
14:57of the QA role.
14:58I have to be upfront,
14:59but at a faster pace.
15:01Because these information,
15:03like for example,
15:03the sentiment reports
15:05or that would be generated
15:07based on a certain
15:10sets of information
15:11that are being seen,
15:14their role would become
15:15more critical.
15:16While AI can be able
15:17to provide those insights,
15:19but at the end of the day,
15:22it would be this QA guys
15:23would have to come in
15:25and say like,
15:26I think my feel is
15:28we have to move forward
15:29or we have to do something else.
15:31I'm seeing that part.
15:35Though it's becoming
15:36very thin right now
15:37in terms of following
15:40whatever AI has given
15:43as an information
15:44and to that part
15:46where the human
15:47has to come in
15:48and make that move
15:50or decision.
15:51Because the other thing,
15:53and I'm sorry
15:53to the viewers now,
15:55I love getting humans
15:58just to set that,
15:59but the context
16:00of this conversation
16:01is really for us humans
16:03to evolve
16:04into people
16:06that machines
16:08cannot replace.
16:09That's the context.
16:10So I love humans.
16:11So going back
16:12to that question,
16:14there's also
16:15the business gains
16:17also that companies
16:19who have started
16:21leveraging AI
16:22because the robots,
16:24they don't file a leave.
16:26and then they can work
16:2824-7.
16:30So in the area
16:31of efficiency,
16:33it's a big check.
16:35And then the other thing
16:37also that they do
16:38is because
16:39they operate
16:40on a set of rules
16:41like QA,
16:42for example,
16:43these are the parameters
16:44you need to check.
16:45The accuracy
16:46at a faster rate
16:48is seen to be
16:50better
16:51also than
16:53a human being.
16:54So this
16:56plus the lack
16:58of context,
16:59at least from
16:59what you're seeing,
17:00which one currently
17:01weighs more
17:02on a business
17:03standpoint?
17:05Which is
17:06having
17:07accuracy,
17:08speed,
17:08and then
17:09no absenteeism,
17:11does not get sick,
17:13etc.
17:13over the other
17:14one,
17:15there are just
17:15certain minor
17:16contexts,
17:17so I used
17:17already minor
17:18so you can
17:18tell the violence,
17:19minor contexts
17:20that they miss
17:21but customers
17:23don't normally
17:23notice them anymore.
17:26I have to be
17:28honest,
17:28this is where
17:29our company
17:30got in.
17:35volume increases
17:36in terms of
17:37transactions
17:38or something
17:39like that,
17:39that's where
17:40humans tend
17:41to fail.
17:43Yeah,
17:44because there's
17:44fatigue.
17:45There's fatigue
17:46and then
17:46they could not
17:47scale up
17:48as far
17:50as AI
17:52is.
17:52But let's
17:53put it this way,
17:54there would always
17:55be some point
17:56wherein
17:57AI will not
17:58be able
17:58to answer.
18:00So that's
18:02where humans
18:02come in.
18:03So example,
18:05for a certain
18:06product
18:07that a certain
18:08client would
18:09ask,
18:10AI would just
18:11be limited
18:12on those
18:12information
18:13that are fed
18:14with.
18:15So whatever
18:16AI is ingested,
18:17that's where
18:19the limitation
18:19is.
18:20And sometimes
18:21if your AI
18:22would be
18:23ingesting
18:23a whole
18:24huge amount
18:25of information
18:26without
18:27properly
18:29training it,
18:30let me just
18:31be of a
18:32generic
18:32kind of
18:33declaration,
18:34you end up
18:35with hallucinations.
18:36So that's why
18:36we have to be
18:37very careful
18:38in what we
18:39feed with AI
18:40or what we
18:40ingest with AI.
18:42And that's
18:43where the human
18:43can come in.
18:44Yes,
18:45because AI
18:47is not 100%
18:48correct.
18:50And although
18:51statistically
18:52right now,
18:53the misses
18:54are getting
18:55lower.
18:57the human
18:58in itself
19:00can come
19:01in to
19:01really be
19:02the ones
19:02to serve
19:03as the
19:03defining
19:04part of
19:05it that
19:05can end
19:06up with
19:06because
19:08let's put
19:08it this
19:09way.
19:09If you
19:10would notice,
19:10if you're
19:10multitasking,
19:11as a
19:12person,
19:13there's a
19:13tendency
19:14that,
19:14again,
19:15you may
19:16not end
19:16up really
19:17fulfilling
19:17those tasks.
19:19But if
19:19you are
19:20just to
19:20zero in
19:21one task,
19:22I tell
19:22you would
19:23be able
19:24to really
19:24go even
19:25beyond 100%
19:26of delivery
19:27and you
19:27can even
19:28do an
19:28extra mile
19:29for it.
19:29So if
19:31the humans
19:31would be
19:32made to
19:32work on
19:33something
19:33that would
19:34be focusing
19:36on certain
19:37things,
19:37the more
19:38high-end
19:39part of
19:40the value
19:43chain of
19:43the transaction,
19:44that's where
19:46we shine.
19:47But for
19:47those that
19:48are multi-transactions,
19:51volumes of
19:52transactions,
19:53AI can
19:53really do
19:54that part.
19:54And I
19:55think,
19:55correct me
19:55if I'm
19:56wrong,
19:56because you
19:57are the
19:58expert and
19:58I meant
19:59it.
19:59To a
20:00certain
20:00extent.
20:01That's
20:01where what
20:02people would
20:03normally say
20:04critical
20:04thinking and
20:05problem-solving
20:06skills.
20:07Precisely.
20:08And correct
20:09me if I'm
20:10wrong,
20:10that's a
20:10caution also
20:11to our
20:12viewers,
20:13if we
20:14have not
20:14developed so
20:16much our
20:16critical
20:17thinking,
20:18and that
20:18is to
20:18question the
20:19status quo,
20:19and then
20:21at the
20:21same time
20:22to check,
20:23to make
20:25decisions over
20:27a certain
20:27pattern,
20:28or to
20:29actually find
20:29solution to
20:30a hiccup,
20:32then that's
20:32when potentially
20:33we will be
20:34replaced.
20:34But if
20:35that's our
20:35expertise,
20:37then chances
20:38are we
20:39remain relevant.
20:40Correct,
20:40correct.
20:41In fact,
20:41one thing I've
20:42learned with
20:43the present
20:43company that
20:44I'm in is
20:45that we
20:47should always
20:47be a bit
20:48pessimistic of
20:49certain
20:50things.
20:50We just
20:51don't take
20:51things as
20:52face value.
20:53Very good
20:53point.
20:55That's how
20:55AI is.
20:56I mean,
20:57as long as
20:57the information
20:59are there,
21:01then all
21:01things are
21:02taken in.
21:03But that's
21:04also the
21:05good,
21:06I mean,
21:07that's where
21:07the dynamics
21:08of both
21:09AI and
21:09the human
21:10come in.
21:11These are
21:12the things
21:12that AI
21:12can do
21:13at the
21:14entry-level
21:14point,
21:15and that's
21:17why I
21:17always emphasize
21:18the role
21:19of QA.
21:20If you
21:22talk about
21:22a QA
21:22role,
21:23they're
21:24very
21:24particular
21:25in things.
21:26They don't
21:30leave any
21:32stone unturned.
21:34And by
21:35doing so,
21:36and I
21:37believe that
21:38for any
21:38AI,
21:39when they
21:39operate,
21:40there would
21:40always be
21:42times wherein
21:42there are
21:43some holes
21:44in its
21:45suggestions.
21:46And basically,
21:48the human
21:49factor,
21:49the human
21:50role comes
21:50in.
21:51Now,
21:52I'll go
21:52back to
21:52empathy,
21:53communication,
21:54and cultural
21:55alignment,
21:55because those
21:56are the
21:57human traits
21:57that are
21:58seen to
22:00be what
22:03machines
22:04cannot replicate.
22:06But correct me
22:07if I'm wrong,
22:07Dr. Gregan,
22:08I'm not,
22:09again,
22:09an expert to
22:09this.
22:10But when
22:10generative AI
22:11was developed,
22:12I read
22:13somewhere that
22:14there is
22:15like a
22:16metric that
22:17the developers
22:18also use in
22:19such a way
22:20that a
22:21reader of
22:22the text
22:23that's
22:23generated
22:24could not
22:25distinguish
22:26anymore
22:27whether it's
22:28written by
22:29AI or
22:31written by
22:31a human
22:32being.
22:32I forgot
22:33what's that
22:33metric.
22:34And the
22:34reason,
22:34the context
22:35of the
22:35question is
22:35not to
22:35quiz you,
22:36but if
22:37that metric
22:38exists,
22:39so that
22:39means there's
22:40a measure,
22:41I would,
22:42correct me
22:42if I'm
22:42wrong,
22:43I would
22:43anticipate
22:43that that
22:45metric will
22:46continue also
22:46to be used
22:48as a
22:49basis to
22:50eventually
22:51replicate
22:52communication,
22:53empathy,
22:54and cultural
22:55alignment.
22:56I have to
22:56be,
22:57again,
22:57again,
22:58you're
22:58placing me
22:59on the
23:00spot,
23:00but it's
23:02okay,
23:02it's okay,
23:03because at
23:03least I
23:04have some
23:04kind of
23:05homework to
23:05work on
23:06after this
23:07talk.
23:08But let's
23:09put it this
23:09way,
23:10from a
23:10consumer
23:11level,
23:11I'd like
23:12to answer
23:12that from
23:12a consumer
23:13perspective,
23:13because I'm
23:14not really
23:14aware of
23:15it,
23:15although we
23:16have something
23:16going on
23:17also from
23:18our end
23:19and the
23:19production
23:20line.
23:20So first
23:20is that
23:21from a
23:21consumer
23:21perspective
23:22and
23:23observation,
23:24you know,
23:26answers generated
23:27right now by
23:27LLMs are
23:28getting so much
23:29better,
23:30and it's so
23:31hard,
23:31even the
23:32tools that
23:33were present
23:33last year
23:34that would
23:34detect the
23:35difference
23:35of answers
23:37coming from
23:37any LLM
23:38to comparing
23:40it to a
23:40human-generated
23:42answer,
23:43there's not
23:44much distinction
23:45anymore.
23:46It's getting
23:47better and
23:48better.
23:48And as a
23:50result,
23:50those tools
23:51are already,
23:52for the lack
23:53of term,
23:53deprecated,
23:54or they're no
23:54longer something
23:56that you can
23:56see in the
23:57market today
23:57because of
23:59how AI
24:01answers have
24:02evolved so
24:04much.
24:05But also,
24:07from a
24:07production line
24:07perspective,
24:09and I think
24:10every computer
24:11science student
24:12knows this
24:12one,
24:13because before
24:14we were
24:15thinking about
24:18LLMs,
24:19we have
24:19the traditional
24:20machine learning.
24:22And when
24:22you try to
24:24capture,
24:25and it was
24:25under the
24:26topic or
24:28subject about
24:28information
24:29retrieval,
24:30this was the
24:31older generation
24:32of machine
24:32learning under
24:33AI, we
24:34have this,
24:34what we call
24:35a smoothing
24:36value, which
24:37has a range
24:38of about
24:380.01 to
24:400.99.
24:41So meaning
24:42to say,
24:42how would
24:43you present
24:44the answer?
24:45Would it be
24:45something that
24:46would be
24:46biased,
24:47would it be
24:48left-leaning
24:49or right-leaning?
24:50So there are
24:51factors there.
24:52But this is
24:53where it
24:55would try to
24:55see the
24:57balance of
24:57how the
24:58AI would
24:59answer.
25:00So that was
25:00something a
25:01little bit
25:01mechanical.
25:02But right
25:02now,
25:03that's
25:03something that
25:04may not be
25:04applicable
25:05anymore.
25:06And the
25:07other thing,
25:08correct me if
25:08I'm wrong,
25:09since at
25:10least our
25:11education system,
25:12I'm referring
25:13to basic
25:15and secondary
25:16education,
25:18my impression
25:18is teachers
25:19are still
25:20not,
25:21they don't
25:22have a clear
25:23stand whether
25:24to use AI
25:24or not.
25:25It's still
25:27not sure.
25:28and this
25:29is my
25:30own
25:30confession.
25:31It also
25:32takes
25:32somebody
25:33who uses
25:34generative
25:34AI so
25:35much to
25:36actually be
25:36able to
25:36tell that
25:37this is
25:38AI generated.
25:40Correct.
25:40So if our
25:42teachers also
25:42don't use
25:43AI that
25:44much,
25:45then they
25:46will not
25:46be a
25:46friend to
25:47AI to
25:48the point
25:48that in
25:48the same
25:49manner,
25:49if we talk
25:50every day,
25:51I could
25:51already
25:51recognize that
25:52this is
25:52written by
25:53Dr. Greg.
25:56And for
25:57example,
25:57this is a
25:58confession.
25:58So if my
25:59direct reports
25:59are watching,
26:00if I get to
26:00see words
26:01like unwavering,
26:02I'm allergic
26:03to it because
26:04this is so
26:04chat GPT.
26:06And then
26:06the pattern
26:06also of
26:07this is
26:08not about
26:09X,
26:09it is
26:10about Y.
26:11So
26:12chat GPT.
26:14So when I
26:14see also
26:15posts like
26:15this is
26:16not about
26:16X and
26:17this is
26:17about
26:18I and
26:18then
26:18there's
26:18unwavering,
26:20sounds
26:22like.
26:23Sounds
26:24like my
26:24friend.
26:26But
26:26anyway,
26:27going back.
26:27But you're
26:27correct.
26:28But you're
26:28correct.
26:29It takes
26:32one to
26:33really,
26:34it takes
26:35one to
26:35appreciate
26:36generative AI
26:37if you're
26:38using it.
26:38You get
26:39to see
26:39the pattern
26:40or
26:41chat GPT.
26:42So it
26:43means my
26:43best friend's
26:44chat GPT
26:44also tends
26:45to use
26:45three sentences
26:46to describe
26:48one.
26:48So
26:48tend to
26:50be wordy.
26:50But anyway,
26:50going back
26:51to this,
26:51now let's
26:51go on
26:52the
26:52solution.
26:53Now that
26:53we have
26:54underscored
26:54the
26:54importance,
26:56what should
26:56the government
26:57or any
26:58company for
26:59that matter
26:59prioritize at
27:00this point?
27:01Is it
27:01education
27:02or is it
27:04incentives?
27:04So this
27:05is like
27:05incentives for
27:06companies who
27:07are enabling
27:07people to
27:08migrate and
27:10become AI
27:10savvy or
27:11regulation?
27:12And I think
27:12regulation has
27:13something to
27:14do with
27:14foreign direct
27:15investments and
27:16how easy it
27:17is to invest
27:17in the
27:17Philippines.
27:18Well,
27:19let me answer
27:20it this way.
27:20And I like
27:21that question
27:22because I
27:22really thought
27:22about it
27:23this morning.
27:26For
27:26regulation,
27:27that would
27:27be the
27:27last step.
27:28Okay.
27:29For me,
27:30I hope
27:31you'll
27:31respect that.
27:34The
27:34priorities
27:35should be
27:35the
27:35following.
27:36First,
27:36I'm
27:36talking about,
27:37I'd like to
27:38answer it
27:38this way.
27:39I'll start
27:39off with
27:40the government
27:41and afterwards
27:41from education
27:43or university.
27:44So
27:44number one,
27:45governments
27:46should support
27:46reskilling,
27:47upskilling
27:48from the
27:50pedagogical
27:51side that
27:52is in
27:52the
27:52universities,
27:54even up
27:55to the
27:55basic
27:55ed level
27:56that is
27:56exposure.
27:58And then
28:00move towards
28:01some
28:01supporting
28:02digital
28:03infrastructure.
28:04I don't
28:05want to
28:06put some
28:07malice to
28:07it,
28:08but I
28:08really felt
28:09bad about
28:09when I
28:10was listening
28:10to
28:13Dave
28:14Almirol,
28:14wherein
28:15the
28:15ego
28:16for me
28:17is
28:17really
28:17one
28:18of
28:18the
28:18best
28:18implementations
28:19that
28:20has
28:20happened
28:20in
28:22this
28:22year
28:23and
28:23last
28:23year
28:23as
28:24well.
28:24But
28:24unfortunately,
28:24there are
28:25some
28:25funding
28:26issues.
28:26They have
28:27to look
28:27into it
28:27because
28:28it's
28:28actually
28:28helping
28:29out.
28:29And
28:31digital
28:32infrastructure
28:33and
28:33addressing
28:34the
28:34digital
28:34divide
28:35is
28:36one
28:37of
28:37the
28:37basic
28:38tenets
28:38to be
28:39able to
28:39move up
28:40to the
28:40value
28:40chain.
28:41And
28:41then
28:42that's
28:43where
28:43regulation
28:44would
28:44come
28:44in.
28:45That's
28:46the last
28:46part,
28:47but I
28:47would like
28:47to go
28:48into this
28:48one first.
28:49After
28:49that,
28:50let's
28:50government
28:51to provide
28:51incentives
28:52for
28:53organizations
28:54that are
28:55creating
28:56higher
28:57value
28:57digital
28:58jobs
28:58because
28:59they
28:59would
28:59become
28:59as
29:00models.
29:01They
29:01would
29:01become
29:01as
29:01proof
29:01of
29:02concepts.
29:02And
29:03the
29:03last
29:03part,
29:03that's
29:03where
29:04regulation
29:05would
29:05come
29:05in.
29:06So
29:06my
29:07take
29:07is
29:07that
29:08let's
29:09not allow
29:10government
29:10to put
29:10a lid
29:11for the
29:11moment,
29:12meaning
29:12regulation.
29:13It should
29:13only come
29:14in once
29:14we're
29:14seeing some
29:15successful
29:16attempts
29:17in this
29:18initiative.
29:18And then
29:19for the
29:19universities,
29:21I'd like to
29:22take out this
29:22notion that
29:24AI,
29:25machine
29:25learning,
29:26or AI
29:27itself,
29:28does not
29:29just belong to
29:30computer science
29:31dimension.
29:32it cuts
29:33across the
29:34different
29:34programs.
29:35And I'm
29:35happy to
29:36know these
29:37guys.
29:37And I
29:38would like
29:38to share
29:39this one.
29:40There's
29:40Michelle
29:41Alarcón
29:42and
29:43Sherwin
29:43Playo.
29:44They're
29:44one of
29:44the
29:44known
29:45individuals
29:45who
29:46really
29:46was
29:47taking
29:47their
29:47time
29:48out
29:48from
29:48their
29:48present
29:49work,
29:50sharing
29:50their
29:50time
29:50both
29:51to
29:51the
29:51government
29:51and
29:52the
29:52public,
29:53helping
29:53out
29:53how
29:54to
29:54be
29:54able
29:54to
29:55shape
29:55up
29:55the
29:55content
29:56in
29:56terms
29:57of
29:57this
29:58AI
29:58literacy,
29:59which
29:59cuts
30:00across
30:00the
30:00different
30:01programs,
30:01not just
30:01from
30:02computer
30:02science,
30:02not just
30:03from
30:03IT,
30:03but
30:03other
30:04programs,
30:05like for
30:05example,
30:05in
30:05business,
30:06engineering,
30:07and even
30:07on the
30:09general
30:10education
30:10part of
30:11it.
30:11And I'm
30:12glad
30:12actually you
30:13touched
30:13on
30:14digital
30:14divide.
30:15And again,
30:16you can
30:17correct me
30:17if I'm
30:17wrong,
30:18but because
30:19in my
30:20other
30:21practice in
30:22Rotary,
30:22so I
30:22get to
30:23visit
30:23remote
30:24schools
30:24in the
30:25mountains.
30:25And yes,
30:27even after
30:27the pandemic,
30:28some of
30:28these schools,
30:29they are
30:29still
30:30with
30:31connectivity.
30:32And this
30:33is just
30:33my way
30:34also to
30:34raise this
30:35important
30:35point.
30:36In a lot
30:37of our
30:37circles,
30:38meaning my
30:38circle,
30:39we only
30:40get to
30:41see what's
30:41within the
30:41city.
30:42But if
30:42we go
30:43in the
30:44remote
30:44areas,
30:45if
30:45connectivity
30:46remains to
30:47be an
30:47issue,
30:48so it
30:48does not
30:49only
30:49widen
30:50the gap
30:51between
30:52the quality
30:52of
30:52education,
30:53especially
30:53that some
30:54of the
30:54classes now
30:55are also
30:55done
30:56remotely.
30:56if
30:57a
30:58typhoon
30:58or
30:59a
30:59remote,
31:01so if
31:02a
31:02child
31:03comes to
31:04connectivity,
31:04then
31:05it will
31:05be
31:06But I
31:06think the
31:07other
31:07thing,
31:07and I'm
31:08glad that you
31:08highlighted
31:09that,
31:10also with
31:11the kids
31:12in the
31:12city
31:13having
31:13more
31:13access
31:14to
31:14technology
31:14and
31:15more
31:15access
31:15to
31:16artificial
31:16intelligence,
31:17if
31:17the
31:18child
31:18does not
31:20have
31:20the
31:21same
31:22access,
31:23then
31:23the
31:23child
31:24in the
31:24city
31:24when he
31:25grows up,
31:28there already
31:29is a huge
31:30divide because
31:31this child
31:31is already
31:32more
31:33efficient,
31:35faster,
31:36and
31:36savvy.
31:37So the
31:38digital divide
31:39also as we
31:40progress
31:40is
31:41urgent,
31:42in my
31:42opinion.
31:43Correct,
31:44correct.
31:44You know,
31:47I'm with
31:48CIBO before,
31:49CEDFIT before.
31:50I used to be
31:50the president
31:50and the
31:51first president
31:52of CIBO.
31:53And
31:54one of the
31:55mandates
31:55that we have
31:57is that other
31:57than trying to
31:58bring in jobs
31:59and human
32:00resource closer,
32:01it was really
32:01on the
32:02context of
32:02addressing
32:03the digital
32:04divide.
32:05And,
32:05you know,
32:06this has been
32:07an age-old
32:07issue.
32:08And we
32:09can never
32:09really
32:10address
32:11all these
32:12things that
32:12are happening
32:13even in the
32:14context of
32:14AI if we
32:15don't address
32:16the foundation
32:17and that's
32:18actually
32:18connectivity.
32:20And I'm
32:20just happy
32:21in the last,
32:22especially during
32:23the pandemic,
32:24that there's
32:24been a
32:25leapfrog in
32:26terms of
32:26connectivity.
32:27But if you
32:28look at it,
32:29that rise,
32:30actually,
32:31I'm seeing
32:32a slowdown
32:34starting in
32:352024.
32:35same
32:36observation,
32:37actually.
32:37And I'm
32:38hoping they
32:38can still
32:39rise up.
32:39So I'm
32:40just plugging
32:42this one
32:42for all
32:43telcos that,
32:44hey,
32:44continue
32:46investing on
32:47or setting
32:47up
32:47infrastructures
32:48in far-flung
32:49areas.
32:49And I just
32:50would like to
32:51also to
32:51take a swipe
32:52at it because
32:53in the
32:53company we're
32:54in,
32:54you know
32:55we're a
32:55work-from-home
32:56organization.
32:57And it's
32:58not that we
32:59value,
33:00although there's
33:01really a
33:02good thing
33:03also that's
33:04happening.
33:04But the
33:05good thing
33:05about a
33:06work-from-home
33:07setup is
33:07that we
33:08have the
33:09capacity to
33:10reach out
33:11to hire
33:12developers
33:13coming from
33:14different islands
33:15in the
33:15Philippines.
33:16And simply
33:17that gives
33:18the other
33:19developers the
33:20opportunity to
33:21work in
33:23an organization
33:25that's global.
33:26And I see
33:27something similar
33:29if you are
33:30talking about
33:30being able
33:32to address
33:32the
33:33connectivity
33:33for education
33:35per se.
33:36And now
33:37also you
33:38mentioned this
33:39on education
33:40also.
33:41So the
33:42other part
33:42aside from
33:43the digital
33:43divide that
33:44I'm also
33:44passionate about
33:45and maybe
33:45my passion
33:46is misplaced
33:47so you
33:48can also
33:49correct me
33:50is,
33:52and I don't
33:52like to put
33:53you on the
33:53spot,
33:53the context
33:54here is
33:54continuous
33:54improvement.
33:55It's not
33:55because it's
33:56bad.
33:56But the
33:57other
33:57observation
33:58also that
33:59I have
33:59when it
34:00comes to,
34:00so this is
34:01my
34:01observation,
34:02when it
34:02comes to
34:03program,
34:03because I'm
34:04supposed to
34:04be pro
34:05micro
34:05credential.
34:06And the
34:07reason why
34:07I'm pro
34:08micro
34:08credential,
34:09not necessarily
34:10because I
34:10don't encourage
34:11people to
34:12finish college,
34:12but I just
34:13actually look
34:14at it as
34:14a quick
34:15solution
34:16to the
34:17problem.
34:17And if
34:19a person
34:19is leaning
34:19towards
34:20micro
34:20credential,
34:21then let's
34:21do it.
34:22That's where
34:22my bias is.
34:23However,
34:24in the
34:24context also
34:25of micro
34:25credentials,
34:26and this
34:26is in the
34:27context of
34:28continuous
34:28improvement,
34:29it's not
34:29that it's
34:29bad.
34:30I also
34:30see that
34:31micro
34:31credentialing
34:32programs of
34:33TESDA is,
34:35correct me if
34:35I'm wrong,
34:36very reliant to
34:37existing companies.
34:40You say existing
34:41companies are the
34:42content providers?
34:43they would
34:44accredit
34:45organizations like
34:47for example,
34:47XP+,
34:48so that
34:49when we
34:50would enable
34:51our people,
34:52and then the
34:52good thing about
34:53it, the
34:53benefit is for
34:54us eventually
34:55to get a
34:56rebate of
34:57the training.
34:58And I see
34:59the good side
35:00of that because
35:01it involves
35:01the industry.
35:03But my
35:03question here
35:04actually is,
35:05what is also
35:06TESDA doing
35:06on its own
35:08to do the
35:09enablement
35:09without having
35:10to rely almost
35:11100% to
35:12existing
35:13companies?
35:15And this is in
35:16the context of
35:16continuous improvement?
35:17Correct,
35:18correct.
35:20FYI,
35:20it's not only
35:21TESDA,
35:21even the
35:22Commission in
35:22Higher Education
35:23is into
35:24micro-credentialing
35:25as well.
35:25That's very
35:26good to know.
35:27So at least
35:28there's already
35:29a fusion of
35:30the,
35:31at what stage
35:32TESDA comes in,
35:33and as well as
35:35where the
35:36Commission in
35:36Higher Education
35:37comes in.
35:37that first
35:38figure.
35:38I'm not in
35:39a position
35:39really,
35:40I'm not in
35:40authority,
35:40but I can
35:41say that
35:42both agencies
35:45respect its
35:46existence.
35:47So meaning
35:48to say
35:50somewhere at
35:51the senior
35:51high school
35:51level,
35:52because I
35:53used to
35:53really look
35:54into it
35:54five years
35:55ago when I
35:55was still in
35:56the academy.
35:56Right now,
35:57I'm just,
35:58how do you
35:59call this,
36:00all those
36:00things,
36:01all those
36:01informations
36:01are already
36:02gray for me
36:03already.
36:04But here's
36:04the point,
36:06TESDA operates
36:07at the level
36:07where that
36:09happens before
36:09tertiary,
36:11meaning somewhere
36:13in senior
36:14high school
36:14education,
36:16that's where
36:17TESDA would
36:17come in,
36:19and a little
36:20bit of overlap
36:21on the first
36:21year level.
36:23So if you
36:24talk about
36:24micro-credentials,
36:26I would see
36:27that these are
36:28the topics
36:29that are
36:29critical to
36:30the formation
36:31of,
36:31let's say,
36:32the nature
36:33of science
36:33in computer
36:34science.
36:35These are
36:35topics.
36:36In fact,
36:36you can see
36:37these topics
36:38within a
36:39certain course,
36:40but these
36:41are very
36:43peculiar or
36:44specific to
36:45the attainment
36:45of this
36:46particular course
36:47or subject.
36:48The good
36:49thing about
36:49micro-credentials
36:50is that you
36:51don't have to
36:52wait to a
36:53certain extent
36:54to be able
36:55to complete
36:57these sets
36:58of topics.
36:58That's the
36:59good thing
36:59about it.
37:00But the
37:00good thing
37:01also about
37:01that approach,
37:02if we
37:03recognize
37:03micro-credentialing
37:04is that
37:05by compounding
37:07all these
37:08topics that
37:09you have
37:09gone through,
37:10this can
37:11be considered
37:13already as
37:13an earned
37:14course in
37:15the higher
37:16education.
37:17That's the
37:17good thing
37:17about it.
37:19So my
37:20point is
37:20that what
37:22I appreciate
37:23right now,
37:23what's happening
37:24is that there's
37:25recognition in
37:25this.
37:26So meaning
37:27to say
37:27delivery
37:28does not
37:29just happen
37:30within the
37:30four corners
37:32of the
37:33room.
37:35And we're
37:36seeing some
37:36kind of a
37:38hybrid approach.
37:39And I
37:40would say
37:41even that
37:42because right
37:43now I came
37:44from the
37:44academe,
37:45you know I
37:45came from
37:45the academe,
37:46and then for
37:46the last five
37:47years I've
37:47been back to
37:48industry.
37:49And I'm
37:50seeing a lot
37:51of realization
37:52in terms of
37:53the depth
37:54of that
37:55skill set
37:55development
37:56in the
37:57industry.
37:58Because they're
37:59actually,
38:01how should I
38:03say this
38:03one,
38:05they're on
38:06the ground.
38:06They're really
38:07doing the
38:08actual work,
38:09applying what
38:10is earned
38:13as a knowledge
38:13and skill,
38:14and putting
38:16it in the
38:16context of
38:17the work
38:17operation.
38:18So what I'm
38:19saying is that
38:20going back to
38:20what you said
38:21is that there's
38:23no better
38:24place where
38:24you can get
38:25experts rather
38:26than the
38:27industry,
38:28in the
38:29companies,
38:29on these
38:30companies,
38:30because they're
38:31really delivering
38:32the actual
38:33work based
38:34on aligning
38:35it, in
38:36some ways
38:36aligning it
38:37to the
38:37theories that
38:38are delivered
38:39in the
38:39university.
38:41And by the
38:41way, I have
38:42to admit,
38:42thank you for
38:43sharing also
38:44the part on
38:45ched and
38:46micro
38:46credentialing,
38:47because that's
38:48one part that
38:48I did not
38:49know.
38:50So at least
38:51now I know
38:51that there are
38:52two parallel
38:54areas that
38:56companies like
38:57myself can
38:58explore to
38:59partner with.
39:00And I would
39:01like to also
39:02to share this
39:02one.
39:03My colleagues,
39:05Sherwin,
39:06Belayo,
39:07and then
39:08Michelle Alarcuan,
39:09they were part
39:10and even
39:12us were
39:13partially or
39:15indirectly
39:16involved in
39:17the development
39:18of this
39:19Philippine
39:19skills framework
39:22for AI
39:23and analytics.
39:24So what it
39:25defines is
39:25that these
39:26are the
39:26different job
39:27roles,
39:27these are
39:28the structures,
39:29and these
39:30are the
39:30specific skill
39:31sets which
39:32would serve
39:33as a reference
39:33for you to
39:34be able to
39:35attain these
39:36job roles.
39:37And the
39:37good thing
39:37about that
39:38is that
39:38that can
39:39be a good
39:39reference to
39:40how you
39:40would approach
39:41micro
39:42credentialing.
39:42And it's
39:43been acknowledged
39:44by the
39:46Commission on
39:46Higher Education
39:47and as well
39:47as TASDA.
39:48That's good.
39:50So now
39:50we're on
39:51the closing
39:52part of
39:52the conversation
39:53but I'd
39:54also like
39:54to hear
39:56your thoughts
39:56also for
39:58MSMEs
39:59like me.
40:00So while
40:00we are in
40:01the ITBPM
40:02industry but
40:02we are not
40:03in the league
40:04of these
40:05huge brands
40:06like Accenture
40:07for example.
40:08So how
40:09can we
40:10also create
40:11what's your
40:11advice for
40:12us?
40:13How can
40:13we also
40:14evolve
40:15and create
40:16more
40:17opportunities
40:18for our
40:19people so
40:20that we
40:20will not
40:21be the
40:21contributor
40:22to the
40:23widening
40:23gap
40:24between
40:25the
40:25industry
40:25and
40:26also
40:27technology?
40:29AI to
40:30be more
40:31specific.
40:32This is
40:33something in
40:34general that
40:35I would like
40:35to share
40:36and somehow
40:38something like
40:39my two cents
40:40advice.
40:41So what
40:43should BPO
40:45or outsourcing
40:45companies do
40:46right now?
40:47so I
40:48would say
40:51if you
40:53try to
40:53check out
40:54if you do
40:55an audit
40:56of your
40:56respective
40:57roles that
40:59you're offering
40:59as a service
41:00to your
41:01clientele
41:02and then
41:03if you try
41:03to see
41:04that this
41:05is something
41:05that you
41:06say like
41:06oh okay
41:07these are
41:08for the lack
41:09of a term
41:10a little bit
41:10menial or
41:11low complex
41:13roles
41:14repetitive
41:15then there's
41:16really a need
41:17to redefine
41:19okay
41:19how they can
41:20upscale
41:21themselves.
41:22I know
41:22it's a bit
41:23so easy
41:24to think
41:24about it
41:25but
41:26there are
41:27a lot
41:27of factors
41:27that has
41:28to be
41:28considered
41:28like
41:29the business
41:30aspects
41:30of it
41:31but at
41:31the same
41:32time
41:32how it
41:32impacts
41:33your
41:34team
41:35so
41:37doing
41:38that part
41:38and at
41:39the same
41:39time
41:39I mean
41:40that part
41:41where you
41:41have to
41:41really
41:42upscale
41:43train your
41:44people
41:44for these
41:45new roles
41:46and at
41:46the same
41:47time
41:48and because
41:49one of the
41:50things that
41:50has to be
41:51considered
41:51is that
41:52while you're
41:52training
41:53people
41:53how would
41:54you be
41:55able to
41:55continue
41:56your
41:57operation
41:57okay
41:58so that's
41:59something
42:00that has
42:00to come
42:00in
42:01so that's
42:01why
42:03I would
42:04always
42:04see
42:05a very
42:06huge
42:07role
42:08not just
42:08from the
42:09government
42:09but
42:09organizations
42:10like
42:10CIBO
42:11okay
42:11because
42:12they are
42:12the ones
42:13who would
42:13serve
42:13as the
42:14go-to
42:15between
42:16these
42:17companies
42:17especially
42:18the smaller
42:18ones
42:19okay
42:19and
42:20during my
42:21time with
42:21CIBO
42:22we're very
42:22conscious
42:23about the
42:24smaller
42:24organizations
42:25that's
42:25why if
42:25you can
42:26recall
42:26one of
42:27the
42:28mandates
42:29of
42:29CIBO
42:30really is
42:31to
42:32focus
42:32on
42:33upskilling
42:33okay
42:34and that
42:35it cuts
42:35across
42:36the
42:36different
42:37memberships
42:38among
42:39its
42:39membership
42:40meaning
42:40different
42:40organizations
42:41and
42:42by doing
42:43that
42:44there's
42:45the
42:45possibility
42:46also
42:46that you
42:46can
42:47actually
42:47touch base
42:47with
42:48the
42:48government
42:48that's
42:49why I
42:49also
42:49mentioned
42:49something
42:50about
42:50providing
42:51incentives
42:52okay
42:52although
42:53what I
42:53mentioned
42:54is about
42:54providing
42:54incentives
42:55to
42:55organizations
42:56wherein
42:57they have
42:57already
42:58started
42:58their
42:58pursuit
42:59for
42:59scaling
43:00up
43:00their
43:01AI
43:02related
43:02roles
43:03okay
43:03but
43:04other
43:04than
43:04that
43:04it's
43:05about
43:05upskilling
43:05and
43:06the
43:06other
43:07thing
43:07that
43:07unfortunately
43:08I
43:08wasn't
43:09able
43:09to
43:09really
43:10work
43:10on
43:10was
43:11really
43:11to
43:11touch
43:12base
43:12with
43:12the
43:12bigger
43:13universities
43:13wherein
43:14if
43:15CIBO
43:16can
43:16really
43:16put
43:17in
43:17that
43:18way
43:19of
43:19doing
43:19where
43:20you
43:20collaborate
43:21with
43:21the
43:21bigger
43:21universities
43:22have
43:23that
43:23kind
43:23of
43:24upskilling
43:25up
43:26knowledgeing
43:26okay
43:27that's
43:27my new
43:27term
43:28for
43:28that
43:28where
43:29you
43:29can
43:29be
43:29able
43:30to
43:30really
43:30increase
43:31the
43:31value
43:32of
43:32every
43:33individual
43:33within
43:33your
43:34organization
43:34and
43:35when
43:35talking
43:36about
43:36AI
43:36it's
43:37not
43:37just
43:37about
43:39AI
43:39per se
43:40where
43:40you
43:40from
43:41ground
43:41zero
43:42you'll
43:42be
43:42building
43:42AI
43:43but
43:43it's
43:43about
43:44how
43:44you
43:45can
43:45actually
43:45take
43:46advantage
43:46of
43:46AI
43:47making
43:47it
43:48work
43:48for
43:48you
43:49in
43:49your
43:49organization
43:49and
43:50specifically
43:50making
43:51it
43:52work
43:52for the
43:53different
43:53tasks
43:53that
43:54your
43:54organization
43:55will do
43:55I know
43:56it's
43:56always
43:56easier
43:57than
43:57done
43:57but
43:57from
43:58that
43:59perspective
43:59I
44:00believe
44:00it
44:00would
44:00be
44:01a
44:01sure
44:05execution
44:06if
44:06these
44:07things
44:07are
44:07actually
44:08executed
44:08so
44:09going
44:09back
44:10then
44:10to
44:12the
44:12question
44:12when
44:13we
44:14opened
44:14today's
44:15episode
44:16as far
44:16as
44:17the
44:17industry
44:18is
44:18concerned
44:18so
44:18that's
44:19ITBPM
44:20or
44:20BPO
44:20industry
44:21in the
44:22Philippines
44:22and
44:23as far
44:23as
44:23artificial
44:24intelligence
44:24is
44:25concerned
44:25or
44:25AI
44:26are
44:26we
44:27still
44:27leading
44:28are
44:28we
44:29catching
44:29up
44:30or
44:31are
44:31we
44:31even
44:32catching
44:32up
44:34your
44:35general
44:37observation
44:38I
44:38really
44:39thought
44:39about
44:40that
44:40question
44:42let
44:42me
44:43answer
44:43it
44:43this
44:44way
44:46so
44:49from
44:50this
44:50particular
44:52Miss
44:53Universe
44:53kind of
44:54answer
44:54so
44:55right
44:56now
44:57just
44:57like
44:57what
44:57I've
44:57said
45:00it's
45:01the
45:02right
45:02time
45:03it
45:03has
45:03been
45:04although
45:04the
45:04right
45:05time
45:05is
45:05still
45:05now
45:06but
45:06it
45:06would
45:07have
45:07been
45:07better
45:07if
45:07we
45:07acted
45:08on
45:08it
45:08yesterday
45:10but
45:11and
45:12that
45:12is
45:12what
45:12is
45:13that
45:13correct
45:14thing
45:14that
45:14is
45:14to
45:15move
45:15from
45:15low
45:15complexity
45:16outsourcing
45:17to
45:17for
45:18these
45:18outsourcing
45:18companies
45:19to
45:19moving
45:20to
45:20transforming
45:21to
45:21AI
45:22enabled
45:22higher
45:23value
45:23digital
45:24services
45:24the
45:25winners
45:26will
45:26be
45:26the
45:27companies
45:27workers
45:27and
45:28even
45:29the
45:29government
45:30and
45:30universities
45:31policymakers
45:32who
45:33will
45:33treat
45:33AI
45:33not as
45:34a
45:34shortcut
45:34but
45:34as
45:34a
45:35part
45:35of
45:35a
45:35broader
45:35digital
45:37transformation
45:37strategy
45:38my
45:39take
45:39is
45:40this
45:41it's
45:42always a
45:43collaborative
45:43effort
45:43because
45:45from the
45:46very beginning
45:46when
45:47outsourcing
45:48started
45:49we took
45:50over
45:50in fact
45:51we're the
45:51number one
45:52fund provider
45:53of the
45:54Philippines
45:54that's a
45:55fact
45:55I think
45:56we've
45:57outgrown
45:58the
45:59how do you
46:00call that
46:00the foreign
46:02workers
46:02in terms of
46:03funds coming
46:04into the
46:05government
46:05and
46:06for me
46:08there has
46:09to be
46:09a buy-in
46:10from the
46:10government
46:10as well
46:11to be
46:12able
46:12to really
46:13help out
46:14how we
46:15can really
46:16reach that
46:17part
46:17where we
46:18are able
46:19to deliver
46:19that higher
46:20value
46:21chain
46:22so
46:23thank you
46:24very much
46:24Dr.
46:25Greg
46:25I can
46:25well
46:26I'm
46:27supposed to
46:27say
46:28Greg
46:28no
46:28but
46:28I've
46:29known him
46:30for the
46:30longest
46:31time
46:31as
46:31Dr.
46:32Greg
46:32but
46:32thank you
46:33very much
46:33for your
46:34time
46:34today
46:34you wanted
46:35to say
46:35something
46:35I just
46:36would like
46:36to say
46:37this one
46:37to the
46:39followers
46:39of DJ
46:40that
46:40AI
46:41is not
46:41the end
46:42of BPO
46:43in fact
46:44BPO
46:45right now
46:46is moving
46:46to a
46:47different
46:47kind
46:47of BPO
46:48and
46:48one
46:49that is
46:49smarter
46:50AI
46:51enabled
46:51and
46:52higher
46:52value
46:53so
46:54thank you
46:54for also
46:55ending
46:55this
46:56conversation
46:56in a
46:57positive
46:58note
46:58you know
46:59we've done
47:00that before
47:00and
47:01I am
47:02truly
47:02optimistic
47:03that we
47:04can be
47:04able to
47:04address
47:05all these
47:05challenges
47:06so
47:07thank you
47:07very much
47:07for
47:08joining
47:09us
47:09today
47:09and
47:11sharing
47:11your
47:11insights
47:12and
47:12the
47:13urgency
47:14and
47:15the
47:15possibilities
47:16also
47:16that
47:17we
47:17can
47:17leverage
47:19or
47:19harness
47:19once
47:20we
47:20address
47:20the
47:21urgency
47:21correct
47:22correct
47:22so
47:22thank you
47:23very
47:23much
47:23so
47:24the
47:24future
47:24of
47:25the
47:25ITBPM
47:26or
47:26BPO
47:26industry
47:27will
47:27not
47:28be
47:28defined
47:28by
47:29technology
47:29alone
47:30but
47:30by
47:31the
47:31people
47:31who
47:31choose
47:32to
47:33evolve
47:33this
47:34is
47:34not
47:35about
47:35humans
47:35competing
47:36with
47:37machines
47:37this
47:38is
47:38about
47:38humans
47:39becoming
47:40someone
47:40no
47:41machine
47:41can
47:42replace
47:43this
47:44is
47:44beyond
47:44the
47:44headlines
47:44I'm
47:45DJ
47:45Moises
47:46have
47:46a
47:46good
47:46afternoon
48:02they
48:03they
48:14they
48:17have
48:20they
48:31have
48:32Oh
Comments