Brendan McGinty, Director of Industry, National Center for Supercomputing Applications (NCSA), University of Illinois, Urbana-Champaign
Brendan McGinty, Director of Industry at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign, is a strategic leader advancing innovation at the intersection of education, technology, and workforce development. With a background spanning advanced computing, applied research, and corporate collaboration, he champions the integration of AI and emerging technologies to solve longstanding challenges across sectors from healthcare and energy to agriculture and manufacturing.
In an exclusive interview with CIOReview, Brendan McGinty shared his perspective on the evolving role of AI in education, industry transformation, and the future of workforce development.
Redefining Learning and Work through AI
As someone who works at the intersection of education, technology, and workforce development, I focus on how artificial intelligence (AI) can be applied to longstanding challenges. Many of the problems we face whether in energy, agriculture, or healthcare are not new, but the tools we now have to address them are. The key is evaluating both the potential and the risk AI presents, and always weighing what it can offer against what might be lost or misused.
Historically, computing systems were designed for optimization boosting engine efficiency in aerospace, sequencing the human genome, or automating agriculture to increase yield. Today, AI adds an entirely new layer of intelligence to these industries. In energy, for example, it is enabling safer oil exploration and supporting access to alternative energy. In healthcare, AI accelerates drug discovery and enhances research outcomes. Even in farming, AI helps manage autonomous planting and harvesting, maximizing resources. The applications are everywhere and growing.
Tools, Transformation, and Trade-offs
My journey with AI began in the 1980s when I programmed expert systems for nuclear sites. At the time, we used rule-based logic. If this, then that. Today, machines learn on their own through powerful models that were barely part of public conversation just a few years ago. Tools like ChatGPT, Copilot, and Gemini have entered daily life at a remarkable pace.
AI is not taking jobs, it is reshaping what jobs look like. It is the biggest transformation since electricity 
These tools offer tremendous potential, but they also raise valid concerns, especially in education. Are students truly learning, or just outsourcing their thinking? Are the sources reliable? That is the double-edged nature of these models. Their capabilities are clear, but misuse is a real issue. Even so, their power to transform learning, productivity, and how we process information is profound.
For students, access to AI can be a turning point. It helps them shape their learning with text, visuals, video, and real-time support, while exploring multiple subjects at once. Used wisely, AI can make them more independent and capable across fields. The question remains whether they are learning or simply finishing tasks. That tension is here to stay, just like the tools themselves.
Rethinking Learning and Evaluation
These developments are prompting educators to re-examine traditional models of assessment. As AI becomes more integrated into student workflows, the challenge is no longer whether students can use these tools but how they should. For educators, the task is to foster learning environments that reward dialogue, analysis, and collaboration. Simply put, we must design for thinking, not just task completion.
From my perspective, this shift is both exciting and necessary. Teachers have to evolve, just as students are. The classroom must become a space where inquiry is valued over output, and where technology enhances, rather than replaces, critical engagement.
One compelling example I have come across shared by a professor at Harvard involves giving students a single AI-generated essay and asking them to critique it together. Instead of submitting work that may or may not be AI-assisted, students learn to identify weaknesses in logic, structure, or bias. That model not only encourages transparency but deepens understanding.
A Future of Continuous Learning
Although I work at a university, my days often revolve around something far from academic theory. Much of my focus is on corporate settings, helping teams adapt, training workforces, and guiding organizations through the currents of digital transformation. Education, in this context, is no longer a chapter that ends with graduation. It has become a lifelong journey.
There was a time when companies would upgrade their systems once a decade, treating technology as a long-term investment. Today, that cycle has shrunk dramatically. AI-powered tools are being adopted every few months, driven by the power of modern computing and the race to stay ahead. What once felt like a sprint has become a loop of constant evolution.
For learners and professionals, this shift means preparing to re-skill often. Career paths no longer follow neat, linear routes. I like to think of it as climbing a corporate rock wall. It is not about going straight up. It is about feeling your way forward, finding new footholds, sometimes in unexpected directions. The goal is progress, not predictability.
Whether I am working with people in pharma, aerospace, energy, or manufacturing, I see the same pattern. AI is not taking over jobs. It is reshaping the skills we need and the way we think about our roles. It is prompting us to become more adaptive, more curious, and more agile.
Yes, there are risks. Plagiarism, misinformation, and even malicious use are concerns we must take seriously. But that has been true of every major leap forward. When electricity became widespread, when the internet took hold, we faced similar disruptions. We adapted then. We can do it again.
The opportunity in front of us is just as transformative. If we remain thoughtful and focused, we have the chance to build something remarkable. A future that is not only smarter, but also more inclusive, more resilient, and ready for whatever comes next.