The world our students are entering is changing at a pace unlike anything we have experienced before. Artificial intelligence is no longer a distant concept. I remember, during my time as Director of STEM and Innovation at the Virginia Department of Education, hearing an engineer describe the use of generative AI in an educational technology tool as early as 2017. Even then, I was struck by its potential. The ability to support teaching and learning in ways that could make educators’ work more efficient, allowing them to focus less on tasks and more on impact.
At the time, it felt futuristic. Today, it is our reality.
Artificial intelligence is actively transforming industries, redefining careers, and changing how work is done across all sectors. Research from the World Economic Forum shows that nearly half of all workers will need to update their skills in the coming years. This isn’t just about learning new tools; it signals a fundamental shift in what it means to be prepared for the workforce.
For decades, our education systems have been built to ensure students master content standards that emphasize critical knowledge and fundamental understanding across subjects. That effort remains vital. However, in an AI-driven world, content alone is no longer sufficient.
Today’s learners must develop the skills to apply knowledge in complex, dynamic environments. Increasingly, it is not just what students know, but what they can do with what they know that determines success. This is where durable skills (e.g., analytical thinking, creativity, problem solving, communication, collaboration, adaptability, and resilience) become essential. These are not “soft” skills; they are foundational, enabling learners to navigate uncertainty, continuously learn, and transfer knowledge across contexts.
As artificial intelligence continues to transform the workforce, predicting the specific jobs students will have in the future becomes more challenging. However, we can expect that students will need to be flexible, adaptable, and have a growth mindset - ready to learn, unlearn, and relearn as industries evolve.
At the same time, we are witnessing the rise of Computational Thinking 2.0. Building on essential skills like decomposition and pattern recognition, this next phase reflects an AI-driven world where students need to work with data, understand how algorithms influence decisions, and critically assess AI-generated outputs. It isn't about turning every student into a computer scientist but about preparing each learner to think logically and engage thoughtfully with technology. Together, strong skills and computational thinking empower students not just to adapt to the future of work but to help shape it.
Computer science and STEM education play a critical role in this shift, not simply as subjects but as vehicles for developing students' thinking. Through computational thinking, data analysis, and real-world problem solving, students learn to approach challenges with curiosity, logic, and resilience.
Importantly, the future of work is not about humans competing with artificial intelligence. It is about humans working alongside it. Our responsibility is to ensure students understand not only how to use technology, but how to question it, design with it, and think critically about its impact.
By Dr. Tina Manglicmot, Executive Director, CodeVA