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Here’s what makes the AI threat to Philippine BPO a little confusing: the industry is still growing.

In 2025, Philippine IT-BPM crossed $40 billion in annual revenue and employed roughly 1.9 million Filipinos. This year, revenue is expected to reach $42.3 billion while employment climbs to around 1.96 million.[1]

Strictly speaking, those figures cover IT-BPM, the broader industry that includes what we commonly call BPO. But BPO remains at the heart of the story.

So far, there has been no dramatic collapse of the Philippine call center. Companies are still hiring. The industry is still bringing billions of dollars into the country. What is changing is the way the work gets done.

AI is already being used to suggest responses, search company knowledge, summarize conversations and help agents deal with customer concerns faster. In many cases, it isn’t replacing the person speaking to the customer. It is helping that person do more.

That sounds like good news, and in many ways it is. But for an industry that spent decades growing by adding people as business increased, higher productivity creates a more complicated question: if every employee can handle more work than before, will growth still create as many jobs?

The rise of Philippine BPO is one of the country’s biggest economic success stories.

Multinational companies found an unusually good combination here: an educated workforce, strong English, familiarity with Western culture and labor costs that were much lower than in the United States and other developed markets.

Once the industry reached scale, it became even more attractive. Companies were no longer outsourcing to a country that was still figuring out how to do the work. They were tapping into a deep pool of agents, trainers, managers and specialists who had already spent years serving global clients.

The work expanded too. What started largely with voice-based customer service moved into finance, healthcare, technical support, analytics and other business processes.

For much of that history, the economics were fairly straightforward. If a company won a big new account, it usually needed more people to serve it. More business meant more seats, and more seats meant more Filipino jobs.

One of the most useful real-world studies of generative AI followed 5,172 customer-support agents working for a Fortune 500 software company.

The workers were given an AI assistant that could monitor customer chats and suggest responses in real time. They were free to ignore the suggestions. The customer was still talking to a person.

Productivity increased by about 15%.[2]

The gains were much larger among newer and lower-performing workers, whose productivity improved by around 30%. Employees with roughly two months of experience using the AI tool could perform at a level similar to workers who had been doing the job for more than six months without it.[2]

And this wasn’t some distant experiment with little relevance to the Philippines. About 80% of the agents in the study were based here.[2]

That matters because a lot of what makes someone good at customer service is learned through experience. A new employee can study the product manual, but there are things you only pick up after dealing with hundreds of customers, unusual cases and situations where the script doesn’t quite fit.

The researchers found evidence that AI was helping less-experienced workers pick up some of the practices used by stronger agents. It could also improve the English fluency of international workers.[2]

In practical terms, knowledge that once took months to accumulate can increasingly be available to a new employee when they need it.

That is a big productivity gain. It also changes how quickly experience becomes valuable.

It is tempting to jump from those numbers to a simple conclusion: if workers become 15% more productive, companies will need 15% fewer people.

The economics are not that clean.

A company could keep the same workforce and serve more customers. It could improve response times, lower prices or win more accounts. It could move people away from repetitive concerns and let them spend more time on complicated ones.

Or it might simply decide it does not need to hire quite as many people next year.

The researchers behind the customer-service study estimated that the company they observed could, in theory, handle the same amount of work with around 12% fewer worker-hours. But they also acknowledged that lower costs and better service can create more demand.[2]

That is why productivity by itself does not tell us whether employment will rise or fall. What it does tell us is that the same amount of work can now be done with less human effort.

Whether employment still grows depends on what businesses do with that extra capacity and how much new demand they can create.

Personally, this is the part I would watch most closely. I’m less worried about a dramatic wave of layoffs than I am about BPO continuing to grow while creating fewer entry-level jobs than it used to. That kind of change would be much quieter, but for young Filipinos trying to enter the industry, it could matter just as much.

When people talk about AI taking jobs, they tend to picture layoffs. The actual transition could be much less visible.

Imagine a BPO company that would normally hire 1,000 new agents next year. Its existing employees become more productive with AI, so it hires 850 instead.

Nobody necessarily lost a job. The company may even be growing. Its revenue could be higher than it was the year before.

But 150 jobs that might once have existed are no longer there.

There are early signs that companies are thinking along those lines. A survey cited by the Bangko Sentral ng Pilipinas found that 67% of responding IT-BPM companies had incorporated AI tools. Among firms using AI, 29% reported no structural change to their workforce, while 13% reported job gains from new work such as AI fine-tuning and data annotation. Eight percent reported reductions in employee numbers.[3]

Industry representatives also told the BSP that AI could mean less recruitment in the near term because companies can increase output with the people they already have.[3]

That distinction matters. The first meaningful impact of AI on Philippine BPO may not be thousands of existing agents being shown the door. It may be fewer new workers getting through it.

We shouldn’t get ahead of the evidence.

There is no mass AI-driven employment collapse happening in Philippine BPO today. The industry added workers in 2025 and expects employment to grow again this year.[1]

The International Labour Organization reached a similar conclusion across Southeast Asia. Its July 2026 assessment found significant exposure to generative AI, but little evidence so far of widespread job disruption. Employment has continued to grow in many highly exposed occupations, although it found some early signs of weaker outcomes for younger workers in certain entry-level roles.[4]

That word, exposure, is important.

A job is made up of many different tasks. AI being able to do some of them does not mean the entire job disappears.

A customer-service agent, for example, does more than retrieve information. There are unclear policies, frustrated customers, unusual circumstances and judgment calls where the obvious answer isn’t always the right one.

As AI gets better at the routine work, those harder parts of the job become more important.

This is where the usual advice to “upskill” starts to feel incomplete.

People don’t become experienced specialists overnight. They usually begin with simpler work, learn the business and gradually take on more difficult situations. An agent who starts by handling straightforward customer concerns might eventually move into quality, training, operations, leadership or a more specialized role.

If AI begins doing more of the basic work, companies may eventually need fewer people at that starting point.

So how do we develop the experienced workers we will need later?

There is an encouraging possibility. The same customer-service research suggests that AI can help people learn much faster.[2]

Perhaps the career path doesn’t disappear. Perhaps workers simply become capable of handling more difficult work sooner.

But that only works if there are still enough opportunities for people to enter the industry in the first place.

The Philippines did not become a BPO leader simply because wages were lower here.

Communication mattered. Strong English mattered. Familiarity with Western culture mattered. The ability to understand an American customer and respond naturally became part of what international companies were paying for.

AI is beginning to change that too.

The customer-service study found that AI improved the English fluency of international agents.[2]

Now consider another outsourcing country where wages are even lower than in the Philippines but communication has historically been a disadvantage. Give those workers real-time grammar correction, translation, tone suggestions and instant access to company knowledge, and part of the gap starts to narrow.

That doesn’t mean the Philippines suddenly loses its edge. Good customer service involves much more than grammar. But English alone may become less of a competitive moat.

The harder-to-copy advantage will come from what people actually know.

Someone who understands why a complicated insurance claim was rejected is more valuable than someone who can simply check its status. The same is true of someone who can recognize possible fraud, interpret a difficult policy or deal with a customer whose situation falls outside the usual process.

The question is no longer just whether Filipinos can communicate well. It is whether we can build expertise that remains valuable even when everyone has access to AI.

There is another side to this story that deserves more attention.

The industry may lose some work to AI and still gain new work because of AI.

TaskUs is already an interesting example. Alongside its traditional customer-experience and digital-operations businesses, it has built an AI Services business around work related to developing, testing and operating AI systems.

In the second quarter of 2026, that business grew 25.8% year on year and remained TaskUs’ fastest-growing service line for the sixth quarter in a row.[5]

That makes sense when you think about what outsourcing companies are actually good at. They take a process, organize people around it, build quality controls and run it at scale for somebody else.

Twenty years ago, that process might have been answering customer calls. Later, it might have been finance or technical support. Today, it can include evaluating AI output, reviewing data or stepping in when an automated system makes a mistake.

The nature of the outsourced work changes, but the underlying capability is still useful.

That could become one of the Philippines’ biggest opportunities. The question is whether enough new work will emerge, and whether Filipino workers can move into it quickly enough.

Back in 2022, the industry’s Roadmap 2028 envisioned Philippine IT-BPM reaching $59 billion in annual revenue with 2.5 million employees by 2028.[6]

Four years later, the outlook is more cautious.

IBPAP now sees 2028 revenue ranging from $43.3 billion in a downside scenario to $50.5 billion in its best case. Employment could range from 1.85 million to 2.14 million.[1]

AI isn’t the only reason those expectations changed. The global economy changed. Investment decisions slowed. More countries entered the outsourcing market. Clients themselves changed the way they buy services.[1]

Still, the revised numbers show the kind of industry that may be emerging.

In one scenario, Philippine IT-BPM could generate more revenue in 2028 than it did in 2025 while employing slightly fewer people.

Even in a stronger scenario, revenue could rise much faster than headcount.

That would be a meaningful change for an industry whose expansion used to translate quite directly into hiring.

BPO could continue to be a successful Philippine industry without being quite the same job-creation machine it used to be.

So what should the Philippines actually prepare for?

I don’t think telling nearly two million workers to “upskill” is enough. It sounds sensible, but it puts almost all of the responsibility on the worker.

Most BPO employees do not need to become programmers or AI engineers. The more realistic goal is to move more Filipino workers into areas where subject knowledge, judgment and accountability matter.

Healthcare is a good example. An automated system can probably tell someone when an insurance claim was received. Understanding why it was rejected, whether an exception applies and when the case needs to be escalated is a different level of work.

There are similar opportunities in finance, cybersecurity, accounting, technical support and analytics. There will also be growing demand for people who know how to work with AI: checking its answers, catching mistakes, improving processes and knowing when the machine should not be trusted.

But workers cannot make that transition by themselves.

Companies will have to rethink how they train people and how entry-level employees build experience. Schools need to prepare students for workplaces where AI will already be part of the job. Government and industry need to make it easier for workers to build real expertise in sectors where the Philippines can compete globally.

If AI makes companies more productive, then part of that productivity gain should also be used to help people move into the next kind of work. Otherwise, “upskill” risks becoming a convenient way of telling workers to solve a problem they didn’t create on their own.

The BPO success story was never built by workers alone. An entire ecosystem grew around them. The next version will need one too.

Probably not in the way the headlines make it sound.

AI could make the industry more productive. It could help new employees learn faster, allow companies to handle more complex work and create services that barely existed a few years ago.

It can also reduce the amount of human effort needed for some of the work that employs a lot of people today.

Both can be true.

My own view is that Philippine BPO will survive AI. I would even bet that the industry continues to grow. What I’m much less certain about is whether it will remain the same mass-employment engine it has been for the last 25 years.

That distinction matters.

The industry may become larger, more capable and more valuable. But it could also reach a point where every billion dollars of additional revenue creates fewer jobs than it once did.

For a country that has relied on BPO not only for dollars but also as a route into the middle class, that would be a meaningful change.

For the last 25 years, the Philippines became very good at doing the work global companies wanted to outsource. Now that work is changing.

I don’t think the goal should be to protect every task Filipinos do today. That is probably impossible. The real goal is to make sure the next generation of valuable work still comes here.

Because if AI can learn part of the job, the real race is whether the Philippines can move on to the next one fast enough.

What do you think?
Will AI make Philippine BPO stronger — or simply less dependent on people?
Hit reply. I’d like to hear your take.

[1] IT & Business Process Association of the Philippines / The Philippine Star, July 15, 2026. Latest industry outlook covering 2025 performance, 2026 expectations and revised 2028 scenarios. The outlook also discusses AI adoption, investment uncertainty, geopolitics and competition from other outsourcing destinations.

[2] Erik Brynjolfsson, Danielle Li and Lindsey R. Raymond, “Generative AI at Work,” The Quarterly Journal of Economics, 2025. Study of 5,172 customer-support agents examining the impact of generative AI on productivity, worker learning and customer interactions. Around 80% of the workers studied were based in the Philippines.

[3] Bangko Sentral ng Pilipinas, Economic Newsletter, 2025. Industry consultations and IBPAP survey findings on AI adoption within Philippine IT-BPM, including reported workforce changes and the possibility of slower near-term recruitment as productivity increases.

[4] International Labour Organization, “Generative AI and Labour Markets in ASEAN: Significant Exposure, Limited Disruption, Uneven Preparedness,” July 8, 2026. Assessment of generative-AI exposure and observed labor-market effects across Southeast Asia.

[5] TaskUs, Q2 2026 Results, August 5, 2026. TaskUs reported 25.8% year-on-year growth in AI Services, which remained its fastest-growing service line for the sixth consecutive quarter.

[6] Philippine IT-BPM Industry Roadmap 2028 / IBPAP, 2022. Original industry roadmap targeting approximately $59 billion in annual revenue and 2.5 million direct jobs by 2028.