Want an AI-Ready Workforce? Start Here.
Everyone Wants AI Upskilling. Who Is Training the Teachers?
The AI industry loves talking about upskilling. Companies want AI-ready employees. Schools want AI-ready graduates. Governments want AI-ready economies.
But there is a simple question hiding underneath all these ambitions: Who is training the teachers?
I discussed this with Jing Castaneda recently. The current AI conversation focuses heavily on learners and not enough on educators. Yet every reskilling initiative depends on teachers, trainers, faculty members, and instructors who can guide others through change. Without them, large-scale AI education becomes difficult to sustain.
That is why we need to talk about the upskilling of the upskillers. Many institutions have already started building AI capacity. Some universities offer faculty training. Professional organizations host workshops. Individual educators experiment with AI tools in their classrooms. But adoption remains uneven. Some institutions lead. Others lag behind. Some remain resistant.
As a result, AI education often depends on local circumstances rather than national strategy. We can do better.
Part of the problem is that discussions about AI education often blur together two very different goals. First, there is specialist training. These are programs designed for AI researchers, engineers, and technical experts. They create the people who build advanced systems.
Second, there is AI literacy. This is for everyone. Students. Teachers. Professionals. Public servants. Citizens. Most people do not need to become AI engineers. They need enough understanding to use AI responsibly and effectively.
Both tracks are important. But AI literacy should be available nationwide. Just as digital literacy became essential in the internet era, AI literacy is becoming essential in the AI era. The challenge is implementation. Literacy programs need instructors. Specialist programs need instructors. Workforce development programs need instructors. Everything depends on educator capacity.
That means AI policy should become more specific. Instead of broad calls for AI readiness, policymakers should define educator competencies. Instead of focusing only on worker training targets, they should establish teacher training targets. Instead of assuming schools will solve the problem independently, they should support coordinated national programs.
These are practical steps. They are also necessary steps. Technology adoption is not just about software and infrastructure. It is about people.
And the people who accelerate learning are teachers. The AI skills gap is real. But there is an even deeper gap beneath it: the educator gap. If we want successful AI upskilling across society, we need to start with the people who make learning possible.
Before we reskill the workforce, we must upskill the upskillers.
About Me:
Dominic “Doc” Ligot is one of the leading voices in AI in the Philippines. Doc has been extensively cited in local and global media outlets including The Economist, Channel News Asia, South China Morning Post, Washington Post, and Agence France Presse. His award-winning work has been recognized and published by prestigious organizations such as NASA, Data.org, Digital Public Goods Alliance, the Group on Earth Observations (GEO), the United Nations Development Programme (UNDP), the World Health Organization (WHO), and UNICEF.
If you need guidance or training in maximizing AI for your career or business, reach out to Doc via https://docligot.com.
Follow Doc Ligot on Facebook:https://facebook.com/docligotAI