Artificial intelligence is changing entry-level cybersecurity work and making it harder for new professionals to gain the hands-on experience employers expect, according to new Canadian research that found 93 per cent of employers surveyed place greater importance on human-centred skills.
The report, published by Rogers Cybersecure Catalyst at Toronto Metropolitan University and funded by the Future Skills Centre through the federal government's Future Skills Program, examines how AI is changing entry-level responsibilities, hiring practices and the development of cybersecurity talent.
Titled Preserving Foundational Skills in AI-Enabled Early-Career Cybersecurity Work, the research identifies a growing challenge for employers and educators: as AI automates routine tasks, newcomers may have fewer opportunities to develop the technical knowledge and judgment needed to advance in the field.
"AI is making many cybersecurity tasks faster and more efficient, but it also raises a practical question about how people get their start in the field," said Charles Finlay, founding executive director of the Catalyst. "If some of the routine work that used to give people hands-on experience is now being done with AI, we need to think about where that experience comes from. People still need opportunities to work through problems, make decisions, and understand the systems they're working with. That's an important part of developing the next generation of cybersecurity professionals."
Entry-level roles are becoming more complex
The research found that tasks traditionally associated with Level 1 cybersecurity positions, including alert triage, query writing and incident investigation, are increasingly being automated or assisted by AI. As a result, some early-career employees are handling more complex investigations and making decisions that require an understanding of business and operational considerations.
Some employers are describing these positions as "Level 1.5" roles, reflecting the changing responsibilities expected of workers at the beginning of their careers.
The shift creates what the report calls an "entry-level paradox": employers want candidates who are ready to contribute in the workplace, while AI is changing the routine assignments that have traditionally helped newcomers acquire that readiness.
Employers consulted for the research also raised concerns about a potential "loss of practice." As AI takes on more routine work, early-career professionals may have fewer opportunities to perform tasks independently, limiting their ability to develop technical expertise, problem-solving skills and professional judgment.
The findings suggest that technical knowledge remains important, but employers are placing greater emphasis on capabilities that help workers apply that knowledge in practical settings. Foundational technical and information technology knowledge was identified as important in 64 per cent of consultation responses.
Meanwhile, 93 per cent of employers identified human-centred capabilities, commonly known as soft skills, as increasingly important. Communication skills were identified by 36 per cent, stakeholder management by 27 per cent and critical thinking by 18 per cent.
The report also emphasizes that AI literacy must be combined with role-specific technical expertise, collaboration and communication. Workers need to understand how to use AI appropriately for their responsibilities and critically evaluate its outputs.
Employers reconsider hiring and assessment
The changing nature of cybersecurity work is also raising questions about how employers determine whether candidates are ready for a job. Nearly one in three employers consulted for the research expressed concerns about assessment and hiring practices as candidates increasingly use AI during technical assessments, certification processes and interviews.
Employers questioned whether traditional credentials and assessments adequately demonstrate a candidate's ability to perform in a workplace where AI is part of the job.
The report identifies several applied approaches employers are considering to evaluate candidates more effectively. These include technical portfolios that provide concrete evidence of skills, simulations that test performance in realistic situations, and scenario-based assessments that examine how candidates approach problems both with and without AI.
Participants also highlighted the growing importance of governance, risk and practical risk assessment. Early-career professionals may need to do more than identify technical vulnerabilities, including assessing and communicating risks and understanding how those risks affect broader business operations.
These expectations could require changes to recruitment, education and training, particularly in how candidates demonstrate their ability to reason through problems, exercise judgment and use AI responsibly.
Pilot training tests practical skills
The Catalyst tested approaches to developing these capabilities through two pilot training iterations involving 55 early-career cybersecurity professionals. The pilots used hands-on simulations, a tabletop exercise and an AI literacy lab to give participants opportunities to practise skills in realistic scenarios.
The research calls for employers, educators and training providers to reconsider how they define and assess job readiness as AI changes traditional career pathways. It recommends creating more opportunities for hands-on learning and operational experience, alongside applied assessments that evaluate reasoning and judgment with and without AI.
The report also points to the need to prepare workers to validate AI-generated outputs, understand risk and apply human judgment when making decisions.
Rather than concluding that AI is eliminating entry-level cybersecurity positions, the research describes a shift in the work and learning opportunities available to people entering the profession.
As those pathways change, employers and educators will need to ensure that efficiency gains from AI do not come at the expense of opportunities for newcomers to practise and demonstrate the skills required for cybersecurity work.
The full report, Preserving Foundational Skills in AI-Enabled Early-Career Cybersecurity Work, is available through Rogers Cybersecure Catalyst.
About the organizations
Rogers Cybersecure Catalyst is Toronto Metropolitan University's national centre for technology safety and security. Founded in 2018 and headquartered in Brampton, the organization works with governments, industry, academic institutions and other partners on technology security programs and initiatives.
The Future Skills Centre is a research and collaboration organization focused on skills development and labour market challenges. It is funded by the Government of Canada's Future Skills Program and was founded by a consortium comprising Toronto Metropolitan University, Blueprint and Signal49 Research.