AI Is Political Because It Changes Who Gets to Build

I keep hearing the idea that people are becoming lazy because of AI.

They use AI to schedule their day, compose emails, make posters, generate images, do research, write drafts, automate promotions, and manage repetitive tasks. And yes, sometimes people use AI to avoid thinking. A student can submit something they do not understand. A junior developer can accept code they cannot debug. A founder can produce a lot of activity without making a good decision.

But I do not think every use of AI should be placed under the same moral label.

If a founder hires a virtual assistant to manage email, social media, lead management, thumbnails, or video editing, we usually call that delegation. We understand that the founder is trying to reserve their time and cognitive load for customers, decisions, strategy, and the actual work that only they can do.

So why does a Filipino creator or starting founder become “tamad” the moment they use an AI agent for some of the same repetitive work?

AI agents are not the same as human virtual assistants. That distinction matters. A person brings context, judgment, accountability, and a livelihood. AI does not. But the underlying opportunity is still worth looking at: AI can give a person with limited resources a layer of leverage that previously required money, employees, or a bigger organization.

That is important in the Philippines.

We have many people with good ideas, technical curiosity, creative ambition, and very limited resources. They may be working full-time. They may be studying. They may be trying to start a business on the side. They may be a creator who cannot yet hire a team. They may be a junior developer who needs to learn while shipping something real.

AI does not remove the need to learn. It does not remove the need to check facts, test code, protect data, understand customers, or develop taste. The person still needs to own the problem, the direction, and the consequences.

But AI can handle some of the repetitive execution. That can create more room for the human to brainstorm, decide, learn, and build.

The virtual-assistant double standard

A small business owner, YouTuber, or influencer in the United States could hire a Filipino virtual assistant to handle emails, social media posts, lead management, thumbnails, or video editing. We usually call that outsourcing or delegation. We do not automatically call the founder lazy because another person handled the repetitive work.

Now a Filipino creator or founder uses an AI agent for some of those same tasks, and the first reaction is often: “Tamad na kasi umaasa sa AI.”

The comparison is not perfect. AI agents are not human workers, and we should not pretend otherwise. But the economic idea is similar: a person is trying to increase their capacity by handing repetitive work to another layer of execution.

We should not reserve the word leverage for people who can afford to buy labor.

What should stay human

The best AI workflow is not AI doing everything. It is a division of work.

AI can help with scheduling and reminders, but the human should own priorities and tradeoffs. AI can do first-pass research, but the human should check sources and interpret them. AI can draft copy, but the human owns the relationship and the decision to send. AI can scaffold code, but the human still owns understanding, testing, security, and maintenance.

If AI handles the repetitive layer while the person spends more cognitive load on the problem, the idea, the customer, the quality bar, and the next decision, that can be a good use of the tool.

If AI is being used so the person never has to learn, verify, or take responsibility, that is where the lazy criticism becomes useful.

Why this is political

This is why I think AI is political. It changes who can access productive capacity.

High-income countries still dominate AI models, compute infrastructure, and startup funding. The World Bank’s Digital Progress and Trends Report 2025 says developing countries can adapt existing and open-source AI to local economic, cultural, and institutional contexts, but inclusive progress depends on connectivity, compute, context, and competency. Read the report.

This does not mean AI automatically solves the development gap. It does mean the Philippines does not have to wait until every local company has a huge technology budget before experimenting with useful systems.

The Philippine Institute for Development Studies reported in a December 2024 study that 14.9 percent of firms used AI technologies, with adoption concentrated among larger and urban firms, particularly in ICT and BPO. Adoption is still early and uneven, which means capability building matters. Read the PIDS study.

The Department of Science and Technology has described a Philippine AI strategy focused on infrastructure, workforce, innovation, ethics and policy, and deployment, with applications across agriculture, education, smart cities, and creative industries. Read DOST’s overview.

The tools are mostly built outside the Philippines. That is a real limitation. We still need better infrastructure, local context, skills, funding, policy, and responsible adoption. But being a user of global tools does not mean we have to remain consumers.

We can use them to build our own systems, products, companies, and solutions for Philippine problems.

The goal is not to avoid learning

AI can help a small team move faster, but it can also produce wrong answers, insecure code, generic writing, fake confidence, and work that nobody can maintain. A person who cannot explain what the AI produced is not automatically an AI-native builder. They may simply be dependent on a system they cannot inspect.

The goal is not to avoid learning. The goal is to learn while building.

A student can use AI as a tutor, but should still solve problems and explain the answer. A junior developer can use AI for scaffolding, but should still read the code, test it, debug it, and understand the system. A creator can use AI for production tasks, but should still own the point of view, taste, story, and relationship with the audience. A founder can use AI to stretch a small team, but should still talk to customers and decide what deserves to exist.

That is the difference between outsourcing execution and outsourcing your mind.

A window for Filipino builders

For many Filipinos, the old path to building something valuable required resources that were difficult to access: a team, a large budget, specialized software, a technical co-founder, or enough free time to do every task manually.

AI does not remove all of those constraints. But it can reduce the cost of some of them.

That matters for the starting founder who is still working full-time. It matters for the creator who cannot yet hire an editor. It matters for the student who needs feedback while learning. It matters for the small team trying to make a tool for a Philippine school, cooperative, local business, or public service.

The next question is whether we use that access only to make ourselves more efficient employees, or whether we also use it to build something of our own.

Maybe this is one of the windows where we can catch up.

Not by pretending that AI is magic. Not by handing over our judgment. And not by calling every form of delegation laziness.

Use AI to remove the repetitive work. Keep the thinking, the taste, the responsibility, and the reason for building.

Then build on your own.

Questions worth keeping open

Is using AI automatically lazy?

No. Using AI to remove repetitive work is not automatically lazy. It becomes a problem when a person gives up learning, judgment, verification, or responsibility.

Are AI agents the same as Filipino virtual assistants?

No. They are not equivalent. The comparison is about access to leverage: both can be used to delegate some repetitive tasks, but human workers bring context, judgment, livelihood, and accountability that AI does not.

Can AI help the Philippines catch up?

It can create an opportunity, but it is not a guarantee. The Philippines still needs skills, affordable connectivity, compute, local data and context, responsible policy, and people who can turn prototypes into reliable systems.

What should Filipino builders learn first?

Learn how to identify a real problem, use AI tools, verify outputs, understand the underlying work, protect data, and ship something that another person can actually use.