Maharlika's CEO estimates that 1.9 million Filipino BPO jobs are at risk from AI, and the article explores the dilemma of accountability when AI systems fail, drawing parallels to engineering liability.
TL;DR: Maharlika's CEO puts a number on AI job risk — 1.9M Filipino BPO jobs. The real fault line isn't skill, it's who's accountable when the machine gets it wrong. Consing runs the Philippines' sovereign wealth fund, and he doesn't dodge the number — he states it plainly on camera. What's easy to miss underneath it: Outsource Accelerator's own data shows the global outsourcing industry is still growing overall, even as AI quietly thins out individual roles inside that growth. An industry chart can look completely healthy while the people under it get priced out one at a time. That's the actual fracture point — not whether the work can be automated, but whether there's still a human name attached when the automation gets something wrong. That fracture point — a name attached when things go wrong — isn't a new idea to me. I watched it play out somewhere else entirely, thirty years ago. I was reminded of that incident of the Highland Towers residential block on top of a hill that collapsed back in 1993. Huge local news in Malaysia. 48 died. The uproar caused the authority to cast the blame on the property developer and the consultants. And most of the liability landed squarely on the Civil/Structural Consulting Engineer. Consequently, he was sued and fined a huge sum of damages. His Professional Engineer (PE) license revoked, and he went into bankruptcy. Most of us in the construction line was shaken by the news. We often joked about the disproportionate liability a C&S consultant carries compared to other consultants. If there's a paint job failure on the building — causing harm to the occupant — the Architect might get sued for public hazard for a time. If there's a machinery malfunctioned in the compound inflicting bodily damage to someone, the mechanical/electrical engineer might get hammered for just a period. But to the structural integrity of a building? It's a lifetime liability to the C&S Engineer — even after he retired decades later. I can still remember the indignant tone of my C&S Consultant friend, as he recounts that Highland Tower story — how empathetic he was towards that disgraced PE. He thinks it was hugely unfair to condemn the poor guy because — logically speaking — they were meant to only design according to the existing condition at that time. And during that time, there wasn't any surrounding development. He said: they are not prophets — how do they know what will happen in the future? Now let's flip the script. Imagine if AI is doing the designing. Who should we sue if Highland Tower 2.0 happens? To sue means you need a defendant human being to be liable, isn't it? Thank God for the PE Board sanctioned Engineers to be in place. That's the regulatory moat we're talking about. https://preview.redd.it/hydd0vqyoqkh1.jpg?width=1024&format=pjpg&auto=webp&s=19760958e83e8ddc09e44b5f5947fd58a5549d6f __________ At this point I don't ask whether AI can do the job. I ask a different question — if it screws up, whose signature is on the line? A VC I featured a few weeks back named the exact same short list — physical presence, licensing gates, relationships nobody can copy-paste — as the only moats AI genuinely can't absorb; worth the four minutes if that idea's new to you. Drop your take below 👇 Clip credit: John Dang / Breaking Ground PH — full video on their channel. DM for credit or removal requests.
The Philippines' offshoring and BPO industry continues to grow despite concerns about AI-driven automation, showing resilience in the face of technological disruption.
A report from Ramp and Revelio Labs finds that companies heavily investing in AI are growing headcount faster, including entry-level roles, countering fears of AI-driven job losses, though the data skews towards tech-forward firms.
The article argues that the most dangerous AI job losses may be invisible, as AI eliminates organizational friction layers—such as information routing and coordination—before replacing expertise, leading to gradual cognitive displacement rather than immediate firings.
Despite predictions that AI would replace customer service roles, offshore call center employment in the Philippines has nearly doubled over the past decade, illustrating Jevons paradox where AI-driven efficiency lowers costs and increases demand for such labor.
Nearly 80,000 tech workers were laid off in Q1 2026, with approximately 48% attributed to AI and automation. Industry leaders debate whether AI-driven job cuts represent genuine productivity gains or serve as a convenient excuse for poor business performance.