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AI is reshaping the Philippines' outsourcing industry, raising questions over the future of the industry.
For 15 years, single mother Lisa made a living from content writing.
She began writing straight out of college, freelanced for years and eventually followed a path taken by many young Filipinos: joining a multinational in the country's booming outsourcing industry.
Lisa says she never felt the need to use artificial intelligence (AI) in her work.
"I can say that I am able to do my job, I meet deadlines. In my opinion, there is no need for [AI]," she told the BBC.
Eight months into her latest role, and one month before the position was due to become permanent, she was made redundant.
In the months before, Lisa says a public relations agency had been tasked with producing AI-generated material that she and her colleagues were asked to edit. She says her skills were used to train the AI on the company writing style.
"I feel like I dug my own grave," she says. "We were the ones who trained the artificial intelligence that replaced us."
Lisa, not her real name, is one of several former outsourcing employees the BBC spoke to who asked to remain anonymous. They signed confidentiality agreements in return for severance pay, and fear that speaking publicly could hurt their chances of finding work in an industry which has a small network.
Their experiences offer an insight into a question confronting emerging economies like the Philippines: what happens when AI begins to automate the jobs that helped lift millions of people into the middle classes?
Building an industry
Every evening around 5pm, streams of workers wearing company lanyards spill out of high-rise offices in the district of Cubao in Manila.
It's one of several areas of the capital where multinational companies have premises β providing all sorts of outsourcing work including call centres, accounting, software development and marketing copy services for clients thousands of miles away.
For over two decades, these business districts have symbolised one of the Philippines' biggest economic success stories.
Beginning in the early 2000s, the country was promoted as an English-speaking alternative to India for what's called business process outsourcing (BPO).
Successive governments offered tax incentives, invested in infrastructure and encouraged multinational companies to set up large operations.
Global groups like Accenture, Concentrix and Teleperformance built sprawling campuses, employing hundreds of thousands of Filipinos.
Today, the outsourcing industry employs roughly 1.9 million people, and generates $40bn (Β£30.1bn) in revenues every year, accounting for about 10% of the Philippines' economy.
But experts say the industry is disproportionately vulnerable to the impact of AI.
The International Labour Organization estimates that 12.7 million Filipinos - more than one in four workers - are employed in occupations exposed to generative AI, the highest share in South East Asia.
The organisation expects many roles to change rather than disappear but the types of service jobs that people do in the Philippines leaves it particularly at risk.
Jack Madrid, president of the IT and Business Process Association of the Philippines (IBPAP), admits that AI is being adopted by the sector.
More than two-thirds of IBPAP's members are already running AI pilots, he says.
"Agentic AI has the potential to automate at a much more accelerated pace," Madrid says. "Obviously, there's a layer of jobs that are automatable or have been automated."
But he adds that the vast majority of affected workers have been redeployed within the same organisations.
Madrid says any weakness in hiring reflects more than the impact of AI.
"We've seen a slowdown in investment decisions on whether certain job functions or processes should be offshored," he says, pointing to slower global demand and uncertainty over how companies will ultimately deploy the technology.
Even so, he acknowledges the challenge. "We cannot do enough to be prepared," he says. "The importance of reskilling" cannot be overstated.
The pressure to automate
Mary, another former content writer whose name we've changed, says her employer encouraged the use of AI as a productivity tool.
Instead of making her job easier, she says it created additional responsibilities.
"We had to edit more, fact-check more because the data AI produced was inaccurate," she says. "Technically it was more work for us."
Like Lisa, she was later made redundant.
Companies are under pressure to implement AI, to reduce costs and increase productivity, experts say.
Teleperformance, the world's largest call centre operator and one of the Philippines' biggest private employers, has said AI offers an opportunity to augment rather than replace its workforce.
The company expects AI to handle routine interactions while human agents move into more complex roles.
Teleperformance has also said it plans to retrain employees.
Accenture has similarly said that generative AI will reshape almost every job rather than eliminate positions.
The firm has promised to invest billions of dollars in AI capabilities and workforce training.
Concentrix - which is the biggest outsourcing firm in the Philippines - says its AI systems should remain under human oversight and has committed to training employees in the new technology.
Some Filipino managers are uneasy about AI and want to slow down adoption, according to Paul Quintos, from the University of the Philippines-Diliman.
They are concerned about how much of the domestic workforce might be displaced.
"But there's tremendous pressure from foreign clients to adopt AI," he says. "It's a major cost-cutting measure."
Philippine outsourcing companies compete directly with rivals in India and elsewhere for contracts from multinational corporations.
Increasingly, those clients expect suppliers not only to provide cheaper labour, but also to integrate AI into the services they deliver.
Despite hundreds of billions of dollars being invested globally in AI, Quintos says there is still limited evidence about how much productivity many workplace tools actually deliver.
"There is a term called 'AI washing'," he says.
Some layoffs are presented as being driven by AI when companies are in fact responding to weaker demand or slowing economic conditions, Quintos says.
Attributing redundancies to AI, he adds, can make restructuring appear like technological progress rather than a response to market conditions.
The next transition
Labour groups have told the BBC that existing employment laws in the Philippines govern redundancy but offer little guidance on how companies should introduce AI into workplaces or consult employees over its use.
The Philippines' outsourcing sector is also non-unionised, leaving many workers with little formal say over how new technologies are deployed.
The government says that it, and the private sector have a responsibility to retrain workers, and risks falling behind competitors like India and Singapore.
"To be completely honest, I think we're slightly behind. We have to catch up," says Leandro Aguirre of the Philippines Department of Information and Communications Technology.
"We have to double our efforts to put our people in a position where they will not be displaced but actually thrive in this growing AI race."
The government has committed to upskilling more than 300,000 outsourcing workers, but Aguirre acknowledges that the Philippines may need to rethink the economic model that helped make it an outsourcing centre.
"We relied heavily on foreign direct investment," he says. "But I think we also need to focus on local talent and local companies."
The ambition, he says, is to build home-grown AI companies capable of creating higher-value jobs.
Aguirre rejects calls for sweeping new AI legislation, arguing that existing labour, privacy and consumer protection laws can be adapted more quickly through regulatory guidance.
"The benefits of AI have to trickle down to people," he says. "It can't just benefit employers."
For more than 20 years, the Philippines built one of the world's most successful outsourcing industries by selling the skills of its people to multinational companies.
AI may not end that model, but it is certainly changing it, and risks leaving some workers behind.
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The disaster response agency forgets the weather, embraces pre-crime
The Federal Emergency Management Agency, often criticized for its inadequate response to natural disasters like wildfires, floods, hurricanes, and tornadoes, has been assigned a new mission: βdomestic terrorism.β
Now FEMA is shelling out grant money to state and local authorities to build up capacity to carry out pre-crime operations against βorganized political violence,β as one FEMA information bulletin I obtained says.
The bulletin, dated July 9, instructs local authorities to prioritize βdomestic terrorismβ in their grant applications. Titled βImplementation of National Security Presidential Memorandum-7β¦,β the document echoes President Trumpβs emphasis on rooting out suspected domestic terroristsΒ beforeΒ an attack takes place.
To head off these attacks, the bulletin tells states what to buy: training to spot βsocial media-based indicators,β analysts to monitor βonline behaviors and digital footprints,β and teams for βmanaging persons of concern whose behavior indicates a potential trajectory toward domestic terrorism.β
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Hey, UK folks! Waterstones is having a 3-day pre-order sale that includes the UK paperback of Enshittification (which drops on Sept 1). Use SUMMER26 to get 25% off.
As a technology, AI isn't exceptional. It's not exceptionally wicked. It's not exceptionally good. Take away the accompanying, galactic-scale stock-swindle, and we'd call AI's applications "plug-ins" and we'd use them and abuse them in the same way that we've used every other technology:
https://www.normaltech.ai/
As a destructive economic pathology, AI is extraordinary. AI boosters have spent a baffling and terrifying sum of money β over $1.4T, most of that in the past year β on the promise of making as many workers unemployed as possible, while lowering the wages of the meager survivors of this jobspocalypse. To make things worse, AI can't do the jobs it's replacing: AI is predicated on the premise that the monopolies, duopolies and cartels that control the global economy can deliberately worsen their products without suffering economic or regulatory consequences, because they're the only game in town.
In service to this bubble, AI companies have suborned regional governments into running roughshod over environmental and planning review in order to build endless acres of data centers, many of which will likely end up casualties of the imminent bubble-pop, never to be switched on or even completed. What an indignity to have your farm or house seized through eminent domain, only to see it razed and replaced by a weed-choked empty field, a lonely foundation slab, or an abandoned empty building that could only ever be repurposed for laser-tag or an ICE concentration-camp:
This is just one of the many negative effects of AI that can be traced to the scale of the bubble. Were it not for the imperative to turn more than a trillion dollars of losses into a profit, we would not have the aggressive, site-destroying scraping epidemic. Nor would we see AI crammed into every part of every product and service we use. And of course, in the absence of the investment bubble, businesses wouldn't be firing productive workers and replacing them with defective chatbots.
The single most salient fact about AI is the investment bubble, not the technical characteristics of chatbots or recent advances in statistical inference. AI's investor story is an incoherent tangle of predictions about AI's future, ranging from the outlandish ("Once we spend enough money, AI will become God and solve all our problems, including our profitability crisis") to the dystopian ("The majority of jobs in the economy will be done by our chatbots, and the employers who previously employed those workers will split the wage savings with us").
None of these stories are plausible, which raises an urgent question: why have the world's wealthiest investors been so eager to hand over trillions to finance this bubble?
I have previously written about one reason that billionaires find the AI story so compelling: at root, many billionaires just don't believe most other people are actually, fully real. How could they? Achieving billionairehood requires that you inflict pain on vast numbers of people. If you truly believed that those people were as real as you are, you'd never be able to look yourself in the mirror. Whether it's Leona Helmsley's claim that "only the little people pay taxes," or Elon Musk's habit of calling people who disagree with him "NPCs," the whole ideological project of billionaireism is shot through with a kind of solipsism:
This is true even in one-on-one encounters: for the Epstein Class, the children raped on his island weren't fully real β certainly not as real as their own children. It's even more true for the people that billionaires experience as statistical artifacts, such as Jeff Bezos's vast army of drivers and warehouse workers, with their sky-high on-the-job injury rates and the everyday indignity of their piss-bottles. It gets worse for social media bosses like Mark Zuckerberg, for whom AI's principal appeal is the prospect of ending socializing on social media, swapping your mulish friends for pliable chatbots who will organize their interactions with you to maximize your platform usage and thus the number of ads you see:
I think billionaire solipsism can account for much of the malinvestment in this obvious bubble, but I don't think it's the whole story. Rather, I think there's a whole cohort of investors who don't believe in AI, but believe that other people will believe in AI.
This is a well-established investment principle. As Keynes wrote, the point of investing isn't necessarily to pick the most beautiful contestant to win the beauty contest β it's to pick the contestant that the other judges will hand the crown to:
In other words, you don't get rich from stock speculation by identifying the businesses whose profitability will grow the most β you get rich by identifying the businesses that other investors will pile into, pushing the price up. All you need to do is sell your shares after the price spike, but before anyone else figures out that the business is a turkey. It's like that old joke: "I don't need to run faster than the bear (market), I just have to run faster than you."
From the perspective of a cynical AI investor, the question isn't, "Can AI do your job?" The question is, "Can an AI salesman convince your boss that an AI can do your job?" So long as enough bosses are convinced to fire workers and replace them with AI, AI valuation will continue to climb, and if they time the market right, they can get out before those valuations crash. This proposition gets even sweeter if the CEO of the AI company is in bed with financial regulators and stock exchanges, and can force your financial advisor to buy his worthless AI stock with "little people's" retirement savings:
A bet that bosses will fire workers and replace them with AI is a good wager. Bosses are absolute suckers for this scam. Bosses hate the fact that they can't translate their plans into action without first having a series of ego-shattering confrontations with workers who actually know how to do things, who insist that those plans are illegal, stupid, impossible or will kill people:
For these bosses, AI is the chance to wire the toy steering wheel they play with all day directly into the corporate drive-train. With enough AI slaves, the boss can run the company all on their own:
In other words, you don't need to be a solipsist to bet on AI. It is sufficient to believe that bosses are solipsists, who can be relied upon to empty the corporate coffers in exchange for worker-replacing magic beans.
This is true in many scam sectors. I'm sure that most of the people who finance the supplements that Andrew Tate and Joe Rogan hawk understand that they're just a way to give yourself very expensive piss. They don't have to believe supplements work to believe that there is an army of desperate and credulous young men who will give anything for the promise they dangle.
Likewise, you don't have to believe that Gwyneth Paltrow can help women "regulate their periods" and "correct their hormonal imbalances" by selling them rocks to stuff in their vaginas. You just have to believe that between patriarchy-induced body shame and patriarchy-driven medical neglect, there's an army of desperate women out there who will buy those rocks and risk their lives by sticking them inside their bodies:
AI is even worse than vagina-rocks, of course. When the bubble bursts, when the seven AI companies that make up 35% of the S&P 500 tank, when a third of the US stock market is vaporized overnight, our governments will reflexively turn to austerity, the go-to response to every financial crisis. Austerity is fascism's best recruiting tool:
When the AI bubble bursts, the defective chatbots that replaced skilled workers will disappear with it, leaving us scrambling to get that work done after the workers who understood it have retrained, retired, or exited the workforce. AI is the asbestos we're shoveling into the walls of our civilization and our descendants will be digging it out for generations:
Long after the AI bubble bursts, we'll be dealing with its catastrophic carbon emissions. The Second Law of Thermodynamics isn't up for debate. Once we sink enough therms into the sea, we are losing the ice-caps.
AI is an ordinary technology, but the AI bubble is extraordinary: extraordinarily toxic and extraordinarily dangerous. The source of that danger is financiers, and they are motivated by a mix of solipsism and a belief in other people's solipsism. For them, the most exciting investment hypothesis is that "hell is other people":
If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
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