AI literacy is often framed as a specialized skill needed only in specific fields or by people who actively use artificial intelligence as part of their role. But events earlier this month demonstrated how artificial intelligence is already permeating the world, including those who have never consciously chosen to use it, and why artificial intelligence literacy is now important in all professions.
After a magnitude 3.3 earthquake struck northwest England on December 3, AI-generated images depicting severe bridge damage were widely shared online. The image was convincing enough for the railway company's experts to suspend service as a precaution while inspections were carried out. Ultimately, no structural damage was found, but the disruption was real. Some of the fabricated images led to operational decisions that had economic and safety implications.
This may seem like a niche episode, but it reveals something fundamental about the environment in which all experts currently operate. Synthetic media has reached a level of plausibility where it can influence real-world systems. In a world where AI is becoming increasingly pervasive, even those who are not actively using AI need to prepare for the impact of its presence. As providers of vocational education, FE colleges are uniquely placed to achieve this.
Beyond the prompt: What's involved in AI literacy now?
AI literacy often comes down to the ability to use generation tools effectively. However, recent research calls for a broader understanding. 2024 reviews published in Computers and Education: Artificial Intelligence AI literacy is described as including a conceptual understanding of how AI systems work, a practical ability to use and evaluate AI, an ethical awareness of issues such as bias and privacy, and critical judgment about when and how AI should influence decision-making.
According to this definition, AI literacy is not about training everyone to be a technician. It's about empowering people from all walks of life to interpret information, assess risk, and make decisions in an environment where AI increasingly shapes the data they see and the systems they rely on.
Learners who have never directly prompted the generation tool may still encounter its output. See AI-generated reports, schedules, diagrams, collateral, images, datasets, and workflows. The question is no longer whether a particular profession “uses” AI, but whether the people in that profession can navigate a world filled with AI-mediated information.
Misinformation with serious consequences
Railway accidents are not special cases. A University of York study investigated the impact of AI-generated images in emergency situations and found that synthetic images can significantly distort public understanding and impede effective response. In controlled studies, participants often struggled to distinguish between fabricated disaster images and genuine news coverage, and in some scenarios showed delayed decision-making and decreased trust in legitimate information.
The authors warn that as synthetic media becomes more persuasive, frontline workers, from emergency responders to infrastructure teams, will need new capabilities in verification, evidentiary reasoning, and information triage. This is no longer just a traditional media literacy issue. This concerns the operational integrity of services that depend on reliable information flows. The boundaries between online content and real-world outcomes dissolve when deceptive images or confidently expressed AI-generated reports can change the behavior of experts.
Employees are adopting AI faster than they understand it
Evidence from across the labor market supports the urgency of this challenge. Reports from organizations such as the Organization for Economic Co-operation and Development (OECD) and PricewaterhouseCoopers (PwC) consistently show that employers expect AI to reshape jobs in most sectors, while also expressing concerns about workforce readiness and governance. The OECD notes that while the adoption of AI is accelerating, many organizations lack the internal capacity to effectively manage risks, particularly related to monitoring, judgment and ethical use.
Similarly, PwC's A survey of the hopes and fears of the global workforce It highlights the growing gap between the speed at which AI tools are being introduced into the workplace and the confidence workers feel in understanding how to use them responsibly. Integrating AI into daily work has often been reported to improve productivity, but these gains are best realized when employees understand both the capabilities and limitations of the systems they are using.
In this context, AI literacy is not just a “nice to have.” It has become a prerequisite for safe, effective and equitable implementation.
From preventing abuse to functioning in an AI world
Across the FE sector, AI readiness is taking many forms. Initial reactions were understandably focused on preventing plagiarism, academic integrity, abuse, and more. In addition to this, many universities have recognized that generative AI is embedded in the lives and workplaces of their learners and have invested in instruction, staff development, and experimentation.
What is emerging now is something a little different. The focus is shifting from students' personal use of AI tools to the broader environments they enter. These are professional environments where AI shapes decisions, systems, and information flows even when individuals are not actively involved. Whether learners enter healthcare, construction, rail engineering, early stage, creative industries or public services, they will be learning in environments where AI-generated content and AI-mediated systems are common. Preparing students to function confidently and critically in such environments is becoming a core responsibility of further education providers.
What FE providers need to do next
This means building AI literacy across professional curricula, not as an optional module, but as an integrated element linked to real-world tasks and professional standards. Sustained staff development is needed so that educators themselves can confidently model critical and reflective engagement with AI. Employability strategies must also bring validation, critical questioning, digital resilience, and ethical awareness to the fore, along with technical competency, supported by an active dialogue with employers about how AI reshapes workplace expectations.
None of this will turn every learner into an AI specialist. It's about ensuring that no learner is disadvantaged by being unprepared for the systems, tools, and information ecosystems that shape their professional lives.
If AI literacy permeates all professions, it cannot be left to computing departments or isolated advocates. It requires leadership that recognizes AI as a structural change, staff who feel supported to explore and interrogate the impact of AI, and a curriculum that reflects the realities of modern work.
The bridge image incident may seem trivial on its own, but it symbolizes something profound about the times we are entering and the skills our graduates need to succeed.
Written by Dr. Gary F. Fisher. Academic developer of online education. Liverpool School of Tropical Medicine
