Key Takeaways
- AI job interviews in the Philippines are growing, yet many candidates initially feel uneasy about them.
- AI enhances recruitment by automating tasks like sourcing and screening, but humans still drive final hiring decisions.
- Regional differences exist in candidate comfort with AI interviews; Metro Manila applicants are more accepting than those from other areas.
- Companies often mishandle AI hiring by not defining problems first or expecting AI to solve everything alone.
- AI interviews aim to streamline processes, but should complement, not replace, human involvement in hiring.
Getting matched with an AI recruiter before a human one used to be unusual. Now it’s routine, across the Philippines and internationally. Plenty of candidates find the shift unsettling the first time it happens to them.
This shift was the focus of a recent episode of The Talent Huddle, hosted by Carla Batan. Her guest was Monica Maralit, Chief Operating Officer of PSG Global Solutions. Monica’s career spans nearly two decades in hiring technology. She started with teams of a few dozen people and went on to oversee multinational operations employing thousands. The company she leads today built its own AI interviewing system, Anna. A broader set of AI-driven coaches supports Anna, guiding employees from the application stage through onboarding and early training.
People Still Drive the Hiring Decision
Before any discussion of tools or platforms, one idea grounded the entire conversation: hiring can’t lose its human center. Work occupies most of a person’s waking hours and pulls them away from family. A job worth that trade-off has to be more than a line item to fill.
AI doesn’t step in to replace that. It exists to remove friction in front of it. Sourcing, resume screening, and narrowing hundreds of applicants down to a shortlist worth real conversation. These tasks eat up time without adding much insight. Offloading them to automation gives recruiters room to focus on what only a person can assess: motivation, character, and genuine fit.
Are Filipino Applicants Actually Comfortable With AI Interviews?
One of the more unexpected findings from the conversation concerned regional differences in candidate comfort. When the company launched its AI interviewer, it studied thousands of interview sessions. Some applicants got a straightforward choice: speak with the AI, or speak with a human. The pattern that emerged wasn’t uniform.
Metro Manila applicants tended to opt into the AI interview, often out of curiosity more than preference. Outside the metro, reactions ran more skeptical. Some candidates assumed the setup was a scam, so they’d head to the company’s website instead of completing the call.
That skepticism has eased as AI interviews have become a more familiar part of job hunting.
Does AI Actually Reduce Bias, or Just Shift It?
Who seems most likable on camera doesn’t sway an AI-run first interview. Neither does whether the candidate happens to click with the interviewer that day. AI grades responses against a fixed set of criteria. That sidesteps a category of bias humans struggle to avoid even with good intentions.
But that doesn’t hand AI decision-making authority. The point was made emphatically: AI should never be the party deciding who gets hired. Its job is to surface data, rank applicants, and flag genuine interest, while a human still interprets that output and makes the call. In a properly built system, recruiters review what the AI generates, and a separate layer of oversight keeps the system itself in check.
What Shouldn’t Be Automated, No Matter How Good the Tech Gets
Certain parts of the employee experience need to stay off-limits to automation entirely.
Counseling and mentoring top that list. A conversation about fertility struggles, or the toll of caring for an aging parent, needs someone who has actually lived through grief or joy. AI can produce language that sounds appropriate, but it has no lived reference point behind those words.
Rejection sits in a grayer zone. For high-volume roles where applicants are submitting to dozens of postings at once, an automated “you didn’t meet this requirement” can actually be considerate, it delivers a fast, unambiguous answer instead of silence. For roles carrying more weight, though, a person should be the one breaking the news roughly 80% of the time. Disappointment is an emotional experience, and the way it’s communicated shapes how the candidate remembers the company.
That distinction points to a bigger question hiring leaders should be sitting with: if AI keeps absorbing and doing the uncomfortable conversations, how does the next wave of managers ever build the skill to handle them?
The Most Common Ways Companies Mess Up AI Hiring
A pattern surfaced repeatedly throughout the conversation. When AI adoption goes sideways, it’s rarely the technology’s fault. It’s the rollout.
The most frequent misstep is treating the tool as a complete solution on its own. Leadership often expects an AI recruiter to shrink costs or headcount immediately, without touching the surrounding workflows at all. Left unchanged, the process just has AI bolted onto it, and the promised return never materializes the way finance projected.
A second common error is over-purchasing. Companies watch competitors adopt AI and follow suit without pinning down the actual problem they’re solving. The outcome is an expensive system running well under its real capability.
The advice that keeps resurfacing for TA leaders building out their own AI stack. Define the problem first, then find the tool. Skipping that step is how companies end up paying for capacity they never use.
The Blind Spot Most Companies Don’t Catch Early Enough
One honest admission stood out. With hindsight, two things would change. First, measure impact much earlier. Second, treat the tool as an investment for the whole company from day one, not just one department’s project.
It’s an easy mistake to make. A TA team builds something that solves its own hiring bottleneck without checking whether it plays nicely with anyone else’s systems. Finance later discovers a billing mismatch nobody accounted for. Each function optimizes for its own numbers, and the work of connecting systems gets pushed onto whoever inherits the mess later, usually after something breaks.
What This Actually Means for Your Job Search
If you’re applying to jobs right now, here’s what matters. You don’t need to be scared of an AI interview. You don’t need to fake being excited either. If a company lets you choose between AI and a human interviewer, that’s a real choice. Pick whichever you want. If AI is the only option and you’d rather talk to a person, just ask. That’s a fair thing to do.
The bigger question isn’t who ran the interview. It’s whether a person still checks things before the final decision. A company that trusts its own process should give you a clear answer to that. Want to see what a clear, fair hiring process looks like from start to finish? Our open roles page shows what to expect at each step.
The “AI-Native” Hiring Trend Doesn’t Hold Up the Way Companies Think
More companies are writing job posts asking for candidates who are “AI native,” whether that’s a finance leader fluent in automation tools or an HR partner who can code. That bar often doesn’t exist yet at the seniority level most of these postings target.
The fix mirrors the earlier point about tools: define the actual problem before chasing what sounds impressive on a job description. A stronger interview question isn’t how much AI a candidate already uses. It’s how quickly they’re willing to pick it up.
For professionals, the conversation worth having isn’t whether AI eventually replaces them. It’s what they’re actively doing with AI that determines how secure their role stays. Communication, decision-making, and independent problem-solving remain essential, arguably more so now, since AI can only work within the context it’s handed. The judgment call still belongs to a person.
Where This Leaves Us
AI earns its place in recruitment as a tool, not as the final word. Its usefulness comes down entirely to how carefully it’s implemented, overseen, and applied day to day. The companies getting it right aren’t necessarily running the most sophisticated stack. They’re the ones that started from an actual problem, kept a person in the decision loop, and never lost sight of hiring as fundamentally a people process.
As it was put during the conversation, a leader’s job isn’t only to figure out what AI is capable of. It’s to keep asking what it should be trusted with and what it shouldn’t.
If you’re weighing a move right now and want a firsthand look at what an AI-assisted, transparent hiring process feels like, our current opportunities are a good starting point.
Frequently Asked Questions
It’s an automated system, typically voice or video-based, that poses a set of questions to candidates and scores their answers against predefined criteria. Most companies use it as an early screen before a human recruiter steps in.
That depends on the employer. Some let candidates choose between AI and human interviewers; others use AI strictly for the first-round screen. If you’d prefer a human conversation, it’s reasonable to ask whether that’s an option.
Not in a responsible process. AI can screen, score, and rank applicants, but the final hiring call should still involve a human recruiter or hiring manager weighing that information.
Very common in high-volume BPO, IT, and multinational hiring. Metro Manila adopted the format faster than the provinces, though that gap continues to close as more candidates encounter it.
Treat it the same way you’d prepare for a human interview: know your background, rehearse clear and specific answers, and speak naturally. These systems are generally reading for substance and clarity, not just matching keywords.
