Kevin Nolten is president of the Cyber Innovation Center, advancing cyber education, emerging technology and workforce development programs.
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AI is already reshaping how organizations hire, train and operate, but workforce readiness is still being built too late. Demand for AI-related skills has grown more than 200% over the past decade, yet most workforce development still happens at the point of hiring or within higher education, forcing organizations to catch talent up instead of building a foundation early. This disconnect is showing up across workforce programs and employer partnerships nationwide as companies move quickly to integrate AI while the talent pipeline struggles to keep up.
At the same time, the nature of work is shifting. AI is unlikely to replace entire occupations at scale in the near term, but it's rapidly redefining how work gets done. The more immediate shift is not job elimination, but job evolution. Workers who understand how to leverage AI to enhance productivity, decision-making and creativity are more likely to have an advantage over those who don’t. As a result, hiring decisions are increasingly favoring individuals who can work alongside AI—not because roles have changed, but because expectations within them already have.
More than 500,000 cybersecurity roles remain unfilled in the United States, with similar shortages emerging across AI-driven fields. Employers consistently report spending more time getting new hires up to speed on tools that are already core to the job, slowing adoption, impacting productivity and introducing risk. At the center of this challenge is how we define and develop AI literacy.
AI literacy must be redefined beyond a purely technical skill tied to coding or advanced analytics, especially if it's going to be introduced early enough to meaningfully impact workforce readiness. As AI becomes embedded across operations, it's shaping how people think, make decisions and manage risk. It's less about how systems work in theory and more about how they are applied in practice, including exercising judgment, understanding limitations and knowing when to trust or validate outputs. In high-stakes environments like cybersecurity, that judgment can directly impact risk exposure and organizational resilience.
That foundation must be built earlier. With how integral this technology has become, I believe this foundation starts in K-12 and community-based settings, where skills like critical thinking, adaptability and responsible technology use can develop over time.
Technology shouldn't just be used; it should also be questioned. Although today’s students are digital natives, comfort with technology does not translate to understanding how it works or what is responsible use. Waiting until college or the workplace to introduce these concepts misses a critical window. Momentum around AI literacy frameworks continues to grow, but the larger challenge is implementation at scale, ensuring students gain meaningful exposure to these concepts long before they enter the workforce.
We can't continue treating workforce readiness as a challenge to solve only at the point of hiring. If AI literacy is becoming a baseline workforce competency, industries need to help define what that looks like and work more closely with educators, workforce development organizations and community partners to build those skills earlier. Through my work with the Cyber Innovation Center and workforce development initiatives across the country, I've seen firsthand the value of bringing employers, educators and community leaders together to align training with real-world workforce needs before talent gaps emerge.
That doesn't mean turning every student into an AI engineer. It means helping people develop the judgment, adaptability and critical thinking needed to use these tools responsibly and effectively. Programs that connect education to industry needs can expose students to these concepts earlier, create clearer pathways into technology careers and strengthen the talent pipelines organizations will increasingly depend on.
The challenge is ensuring those efforts are scalable, accessible and aligned with how technology is actually being used in the workplace. I believe organizations that invest in strengthening these pipelines today will be better positioned to address future talent shortages, accelerate adoption and build more resilient workforces. Just as importantly, they can help ensure AI is deployed in ways that drive innovation while maintaining trust, accountability and responsible decision-making.
This is not just a workforce issue, either. AI and cybersecurity are central to national security, economic competitiveness and global leadership. Investing early in building AI-literate workforces helps to innovate, defend critical infrastructure and respond to emerging threats.
Closing this gap requires coordination across sectors, with employers, policymakers and communities aligning education to workforce needs from the start. For business leaders, that means looking beyond hiring and investing earlier in how talent is developed.
AI is not just changing how work gets done; it is exposing how late we are in preparing the workforce to use it responsibly. Organizations are already feeling the cost, risk and inefficiency of building these capabilities after the fact. That approach no longer holds in environments where AI is already shaping decisions and risk in real time.
History won’t remember what we say today, but it will remember what action we took. The organizations that work toward embedding AI literacy upstream before individuals enter the workforce will likely be the ones that operate with greater resilience and confidence.
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