The country’s unique challenges are revealing universal truths about why a successful AI strategy must prioritize partnership over replacement.
Winston Thomas
As AI adoption accelerates globally, companies are grappling with a complex question: how do we balance the efficiency of automation with the irreplaceable value of human judgment?
While companies worldwide search for a solution, a unique case study is emerging in the Philippines, a nation where digital life is a core part of daily existence, and a highly regulated environment demands careful, deliberate action. Here, the challenge of forging a successful AI-human partnership goes beyond a strategic priority. It becomes a live experiment in building trust, ensuring authenticity, and navigating a landscape rife with digital pitfalls.
A recent panel at the Chief Digital & Data Officer Philippine Summit offered a rare look into how Filipino companies are tackling these issues head-on. The conversation showed that Philippine companies are under the same pressure as their global peers to implement AI effectively. However, the country’s unique media landscape and consumer behavior add a different layer of complexity.
Apple Esplana-Manansala, president and chief executive officer of The New Channel Media Corp, highlighted a key issue: “There’s been a lot of fake news, and [AI] is really used just to promote things that we actually don’t need.” With Filipino consumers spending an average of 13 hours daily on social media, creating authentic, high-quality content that cuts through the noise is a critical business challenge.
Durjoy Patranabish, vice president and head of global business for Tiger Analytics, who was the moderator of the discussion, framed this challenge by focusing on what remains constant: “How do I deliver experience? Which is, you know, needs to be top class at the end of the day, and that’s how business will flourish.”
Lessons when AI goes wrong
Financial institutions, operating in a highly regulated environment, learn expensive lessons when AI systems fail. Ralph Embalsado, Head of Upsell at Tonik Digital Bank, spoke about the necessity of human checks. “There should always be someone to look into it.” he warned. “Because if you trust [the AI] too much, it can go sideways, and we’ll pretty much mess up.”
In a sector with strict regulatory oversight, the cost of an AI system failure is simply too high. But Durjoy also added that a lack of adoption can be a failure point as well: “We have seen where a leader… has become more of a laggard because they were not progressive enough to adapt to these new technologies.”
Boris Voskresenskii, senior vice president of AI and data at Salmon Group, shared his experience transforming manufacturing operations with machine learning. He noted a common human resistance to AI adoption, and one way he overcame it was with a simple but powerful incentive: money. “We started with challenges where the best team that used AI more gets money. And after that, even the worst team starts using AI more.”
Voskresenskii also discovered that trust is a separate issue from adoption. In his experience, recommendation systems often clashed with deep-seated beliefs and practices that are not always data-backed but rely on the knowledge of seasoned workers. “This experience is usually not based on data in some cases,” Voskresenskii explained. “It’s often based on some practices that people get to learn from previous people.” The solution was to transition from a recommendation system to an automation system with human override capabilities. This approach allowed the performance results to build trust organically, as workers saw the benefits firsthand.
Media companies and the fight for authenticity
For media companies, the proliferation of AI-generated content poses an existential threat. Esplana-Manansala confronts this challenge daily at The New Channel, where original content is the key to business survival in the Philippines’ oversaturated media landscape.
“If you use the existing technology, for example, for graphics or even for video,” Esplana-Manansala noted, “the tendency is you’re going to come across another video that’s almost similar to what you’re doing. So your credibility might be questionable as a media company.”
Her company’s strategy combines strategic AI deployment with a focus on human expertise: they hire senior writers and video professionals and use AI for routine, non-critical tasks. This human oversight prevents costly errors, as she illustrated with a recent anecdote where an AI-generated presentation confused Singapore with Tokyo.
“There are a lot of times when AI will fail, probably because of confusion,” she added. “And at the end of the day, it’s a computer generating the stuff for you.”
Perfecting customer service with AI-human synergy
Financial institutions are achieving breakthrough results with hybrid AI-human customer service models. Embalsado’s team at Tonik is building intelligent chatbot routing systems that analyze customer intent. “Based on those particular questions, we will find which one’s a buying signal, which one is not, and which one is a fraud indicator,” he explained. “On those buying signals, we will convert them to more profitable loans.”
Voskresenskii is advancing this approach at Salmon Group by creating an integrated “human-AI synergy” system. Their chatbots handle initial customer queries but seamlessly transfer complex issues to human operators. The human operators, in turn, receive AI-powered response recommendations from their internal chatbot. “The human operator also has his chatbot, and the human operator sees what this chatbot recommends to answer the client, and with that, we are creating this human-AI synergy and can help our client very quickly with lower costs.”
Durjoy added a key insight here about the human-in-the-loop for these new technologies: “the human being is still… orchestrating the whole response to the end user. But [that person] now has multiple tools to use.”
Executive lessons for the AI era
The Filipino experience offers a robust set of lessons for CDOs and business leaders worldwide. The panel’s insights show that a successful AI strategy is less about the technology itself and more about the human systems designed to support it.
- Embrace the human-in-the-loop: Don’t view AI as a replacement for human staff, but as a force multiplier. As the panel highlighted, even the most advanced systems still require human oversight to prevent costly errors and ensure compliance, especially in regulated industries.
- Acknowledge and incentivize trust: Resistance to new technology is often a trust issue, not a skill issue. Leaders should build trust organically by allowing AI systems to prove their value over time and by creating clear incentives for adoption.
- Prioritize authenticity: In an age of mass-generated content, authenticity is the new competitive advantage. The best-in-class companies will use AI to handle routine tasks, but invest in human creativity to deliver unique, high-value experiences that build lasting brand credibility.
- Prepare for a hybrid future: The most effective models, as seen in customer service and manufacturing, are not fully autonomous. They are “human-AI synergies” where AI handles initial triage and data processing, while human experts focus on complex problem-solving and strategic decision-making.
Ultimately, the panel’s message is a clear one: prepare for AI’s inevitable advance by continuing to improve human capabilities. As Esplana-Manansala put it, “There will come a time when you will have bots talking here on stage. But until that happens, we should continue to improve ourselves as the AI will just try to copy us.”
This story came out on https://thenewchannel.com/highlights/.
For more NEW stories, follow TNC on social media or search #TNCnow.