Anthropic recently released a new report on the labor market impact of AI, and one of the more interesting takeaways is that AI exposure is currently much stronger in many white-collar and computer-based roles, while many physical tasks remain less exposed for now.
The report also notes that broad labor market effects, especially on unemployment, still appear limited so far.
That immediately made me think about the Philippines.
Because if you look at our local reality, the country is entering the AI era from a very different starting point.
In more advanced economies, the first wave of AI disruption is easier to picture because so much of their work is already digital, software-based, process-heavy, and deeply tied to computer systems.
In the Philippines, a large part of the economy is still rooted in sectors that are more physical, manual, and harder to replace overnight.
Agriculture is one example of that.
Construction is another.
And that is where I think the conversation becomes more interesting for us.
On paper, that sounds like an advantage right?.
But if Anthropic’s report is right that some physical sectors are less immediately exposed to AI disruption, then countries like the Philippines may have a temporary buffer.
In fact, agriculture still accounted for 20.7% of total employed persons in 2024, which means a large share of Filipino work is still tied to a sector that does not easily get handed over to AI overnight.
But I do not think that should make us comfortable.
Because the bigger question is not just whether AI can replace a farmer tomorrow.
The bigger question is whether the Philippines is using this moment to modernize the sectors that are least likely to be disrupted immediately.
And when I look at agriculture in the Philippines, I still see a sector that remains highly traditional in many parts.
Well, a lot of farming here is still old-style. A lot of it is still manual.
A lot of it still depends on fragmented, small-scale operations.
The World Bank notes that Philippine agriculture is dominated by small farmers and fishers who mostly operate independently, often using traditional production practices and earning low incomes. It also says the average farm size had fallen to 0.9 hectare per family holding, and 57% of farms were one hectare or less. (Data is 2021 quite old but still relevant)
That detail matters because once farms are that small and that fragmented, modernization becomes harder.
Adoption becomes slower.
Access to tools becomes more unequal.
And even when technology is available, scaling it across thousands of small operators becomes a completely different problem.
That, to me, is the real gap.
Because yes, there are machines. Yes, there are rice mills.
Yes, there are harvesters and mechanical tools already in the ecosystem.
But many of those are still mechanical in nature. They are not necessarily connected to a digital layer.
They are not automatically part of a smarter system that gives small farmers better visibility, better forecasting, better pricing intelligence, or better decision-making.
(BTW, i’m just in the topic of farmers but this is just one of the categories, this applies to all sector of the agriculture.)
And this is where AI becomes more interesting than people think.
Because when people talk about AI, most of the attention goes to writing, coding, customer service, media, admin work, and office productivity.
But in a country like the Philippines, the more important long-term question may not simply be which office jobs AI touches first.
It may be how AI can improve sectors that have been left behind for years.
Agriculture is a useful sample of that.
Not because it is the entire topic, but because it reflects a larger Philippine pattern: sectors that are still labor-intensive, under-digitized, and full of potential, but not yet deeply connected to data, intelligence systems, or scalable digital tools.
And that is why I do not think the right takeaway from Anthropic’s report is relief.
I think the better takeaway is urgency.
Because there is a difference between being resilient and being late.
If the Philippines is less exposed to immediate AI displacement in some sectors, that may be a short-term advantage.
But if the reason for that is slow adoption, low digital integration, fragmented production, and limited access to technology, then that same “advantage” can turn into a long-term weakness.
I still remember when I was working in video production and we visited a rural area where many of the people were farmers, SME owners, and part of the local agribusiness sector.
Back then, one of their main sources of learning came from community-based gatherings. I no longer remember the exact name of the organization, but it was some kind of local nonprofit or provincial community group.
They would have monthly meetings where government agencies and related groups would brief them on updates, policy changes, new rules, and other important developments.
That was how information reached them. They needed those roundtable discussions just to stay informed.
Today, that friction should already be much lower. Social media has opened access. The internet has opened access.
And now AI has the potential to open access even further. If government can help make these tools easier to understand and more practical for traditional communities, the pace of change could be much faster.
And it is not because people in these sectors are incapable. In many provinces, there are entrepreneurs who have the money and the means to adopt new systems. What often slows things down is not capacity, but mindset.
It is the deeply rooted habit of doing things the same way simply because that way still works.
There is still that thinking of, if it is not broken, do not fix it. Of course, it is case to case. But if that friction is reduced and people are taught properly, I think adoption can move much faster than many assume.
PIDS has already pointed out that digital agriculture in the Philippines has real potential, but it also warned about uneven adoption and the risk of widening the digital divide if smallholders and vulnerable rural communities are left behind.
And that is exactly the Philippine problem.
Just because AI exists does not mean it is accessible.
Just because internet access is improving does not mean adoption becomes automatic.
Just because some larger companies or pilot programs are already experimenting with modern agricultural tools does not mean the majority of smaller farmers are moving at the same pace.
There are already public and policy efforts pushing digital agriculture and more intelligent systems in the Philippines, which shows that the direction is there.
But broad adoption is still far from the reality of most small operators on the ground.
So when I read Anthropic’s report, my takeaway for the Philippines is not just that some jobs may be safer for now.
My takeaway is that the Philippines still has time to move, but not forever. and I hope we do move forward.
Because if we stay too traditional for too long, what protects us today may be the same thing that leaves us behind tomorrow.
And that is why I think local entrepreneurs should be paying attention.
The next big winners here may not only be the ones building AI for office productivity.
They may also be the ones who look at sectors like agriculture, construction, supply chains, and other under-digitized parts of the Philippine economy and ask a better question: how do we make AI useful here?
Not flashy.
Not trendy.
Useful.
Affordable.
Localized.
Practical.
Because the Philippines is not lacking in potential.
What we often lack is systems, access, and execution.
And if local builders, entrepreneurs, and industry players can figure out how to bring intelligence, data, and digital decision-making into sectors that still run on older ways of working, that is where real transformation may happen.
So yes, Anthropic’s report may show that many physical sectors are less immediately exposed to AI disruption.
But for the Philippines, I do not think the takeaway should be “comfort”.
I think it should be a reminder that while the world is moving deeper into AI, we still have major sectors that remain highly traditional, highly fragmented, and slow to adopt.
That means we still have room to change something.
But it also means we cannot afford to stay in that position for too long.
What do you think about the report Anthropic shared?
Do you agree that sectors like agriculture and other physical industries may be less exposed to immediate AI replacement, or do you think the bigger issue is how slowly countries like the Philippines are adopting these tools in the first place?
And if you are an entrepreneur, a builder, or someone working in these sectors, how do you think AI can realistically help move industries like these forward in the Philippines?
Let us know in the comment section and have a healthy discussion we are curious as well.
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