Launching first isn’t the same as winning

Many AI tools are priced for developed markets, so companies in growth markets can’t afford to chase every trend. Anton sees “a lot of FOMO happening right now in the industry,” which pulls companies toward the wrong problems or results in them “throwing money at the problem.” A year ago, everyone rushed to release a first chatbot. Today, “you don’t even need to pay that much” for use cases that go well beyond one. In his first week, Globe’s CEO asked whether the company was ahead on AI. Anton’s reply: “It depends on which race you’re talking about.” On who has the first use case, no. But “you’ve got to look at it more as a long game,” and by that measure he felt Globe was ahead.

Put AI in everyone’s hands

How do you let a thousand flowers bloom and still create value? When Globe began working with AI two years ago, “there wasn’t really a playbook,” so Anton leaned on an analogy. Picture the early Internet era, with companies setting up an “Internet department” where employees filed a ticket for any website they needed, and the department printed it out and delivered it. “Ridiculous, if you think about it.” AI, he argues, is “something that you’ve just got to be able to give to everybody.” His second principle: “Let the people closest to the problems be the ones to solve it.” Top-down value pools still matter, but bottom-up solutions can pay off sooner. When a team in broadband or finance solves a domain-specific problem, he adds, “there’s already value there.”

AI’s value is still an art, not a science

Measures like widgets per hour capture only part of the picture, and it’s hard to separate AI’s impact from everything else. “Right now, it’s an art and not a science,” Anton says. Part of the problem: automation, RPA, and machine learning, once distinct, now all fall under the label AI. Globe’s answer is not “one magic KPI.” Individual use cases carry their own KPIs and ROI, while broader foundational investments are bets that call for “the conviction and belief that it will generate some value at some point.” Value also extends beyond pesos. An employee who builds a personal agent to automate part of their work and gets home for dinner with family becomes “much more engaged and feels happier. That’s sort of the impact.”

Faster output raises the stakes for human judgment

When producing output gets easier, how do people keep questioning it? For Anton, it’s “one of the things that keep me up at night.” His answer is back to basics: “At the end of the day, these are all technology tools, whether it’s AI, whether it was Excel, whether it was the Internet back then.” What counts is “core proper leadership and management principles”: double-checking work and being accountable for what’s produced, not letting the fundamentals slip “just because it’s easier to produce output now.” Where speed makes manual checks impractical, Globe builds in automated controls early, or “fight AI with AI.” The aim is a “human-led, human-driven, human-enabled approach” to how Globe adopts AI.

The Philippines’ real AI advantage: its people

Looking ahead, Anton is optimistic. “Our greatest advantage has been our human capital.” He expects AI to “generate more jobs,” even as “the nature of the jobs” shifts. “There’s always going to be a human capital requirement, even in this age of AI.” A young, highly digitized population with a natural inclination for new technology also helps. Globe wants to get the technology “to as many Filipinos as possible.” There may be “short-term storms to be weathered,” but “if we look at it from a long decade timeline, I think we’ll be fine.” Marco closes on two “value pools”: more value for people from AI, and the value of “some of the strongest, smartest, and most empathetic people on the planet.” Hear Anton and Marco in these short clips and see what other growth-market organizations can take from Globe’s approach.