AI Enters the Deep End: Winners Stop Sloganizing and Start Using It
For the past two years, almost every company has been talking about AI.
It's in presentations, annual reports, and on websites—as if not mentioning AI means you're behind the times. But those who shout the loudest are often not the same ones who actually deliver results.
I host "Global Face-to-Face," and this season, almost every episode discusses AI. But what truly makes me think, "this is the real point," is never about some grand vision a company announces. Instead, it's about cases where AI has been integrated into a specific scenario to solve a concrete human problem.
My show has discussed the plight of elderly people living alone. There are over 600,000 such households in Taiwan, and the most dangerous time for seniors is often not illness, but when they fall and no one finds them. A guest on the show once said something that deeply resonated with me: the loneliness of an elderly person living alone "isn't a news story, but a long-term condition." And AI is designed to address precisely such moments—using millimeter-wave sensing and fall detection, the system alerts caregivers the moment a senior falls, rather than waiting for family members to discover it.
You see, this is what AI entering the deep end looks like. It's not glamorous; it won't make stock prices jump overnight. But it targets a very specific person, at a very specific moment—an elderly person who has fallen and can't reach the phone.
The difference between slogan-driven AI and implemented AI lies here. Slogan-driven AI talks about "we want to build an AI ecosystem" or "we want to become an AI hub"—the subject is "we," and it speaks to their ambitions. Implemented AI talks about "this elder was found within seconds of falling" or "container dispatch at this port reduced by X amount of time"—the subject is "that specific person, that specific problem."
The deep end is called the deep end because anyone can talk about concepts, and anyone can make a PPT. But to truly connect AI to an elderly person who might fall, a congested intersection, or a queuing port, what's needed isn't a vision. It's about breaking down the scenario finely enough to know "whose specific problem needs to be solved."
There's a saying I always remember: the people who won't be replaced by AI in the future are those who know how to use AI. This also applies to companies. The companies that won't be eliminated are not those that talk about AI most beautifully, but those that genuinely use AI to address a specific pain point.
So next time you see a company announce "full embrace of AI," don't be quick to admire. Just ask one question: what specific person, what specific problem, is your AI solution actually helping to solve? Only when there's an answer to that question can you truly say they've taken the plunge.