The changing meaning of workplace readiness

For many years, a university degree served as a clear entry point into professional life. A graduate completed an engineering course, entered campus recruitment, and carried that qualification into the early stages of a career. The degree offered employers a familiar way to assess educational background, and a broadly understood signal of preparation.

That model is becoming less sufficient. A graduate may enter a first job with a strong degree and good academic record, only to discover that the work demands capabilities that were not fully measured in college. The role may involve interpreting unclear requirements, working with changing AI tools, collaborating across functions, making decisions with incomplete information, and communicating ideas before they are fully developed. Academic credentials remain relevant, but they do not always provide a complete picture of workplace readiness.

The announcement often comes before the change

Organisations are increasingly discussing skills-based hiring, with greater attention to what candidates can demonstrate rather than where they studied. Job descriptions may place less emphasis on specific degrees, while recruitment communication may focus more on skills and capabilities. The transition, however, can be gradual. When hiring managers compare two candidates under time pressure, a recognised university, familiar qualification, or conventional career path can still provide an easy reference point. Assessing capability directly takes more time. Reviewing a portfolio, examining a work sample, or conducting a structured exercise requires a different process and clearer evaluation criteria. This does not necessarily mean that organisations are unwilling to consider skills. It means that changing recruitment language is easier than changing the mechanisms used to make hiring decisions. For skills-based hiring to become consistent, employers need reliable ways to assess capability and help hiring managers use them confidently.

AI fluency is becoming a basic workplace skill

AI is increasingly being used for research, drafting, analysis, coding, customer support, documentation, and other activities. As these tools develop, employees across functions are likely to encounter them in workflows. The challenge is not simply learning one particular tool. AI systems are changing quickly, so useful knowledge can become outdated. Employees therefore need an ongoing habit of experimenting, learning, checking results, and understanding where human judgment remains necessary. This is relevant across sectors, including technology, banking, manufacturing, professional services, and other industries. Two people with similar job titles may increasingly have different levels of effectiveness because one has developed practical familiarity with AI-enabled workflows while the other has not yet incorporated them into everyday work. AI fluency should not replace domain expertise. Understanding a business, customer, process, or profession remains important. The stronger combination is subject knowledge supported by the ability to work with evolving technology.

What can close the gap

The difference between skills-based hiring as an idea and skills-based hiring as a working practice depends largely on assessment. Employers need methods that allow them to evaluate capabilities efficiently.

Structured assessments, practical problem-solving exercises, portfolios, work samples, and role-specific simulations can provide evidence that a conventional resume may not show. Technology can also help organisations review information and identify relevant evidence more efficiently, provided these systems are designed and used carefully.

The objective is not to remove credentials altogether. Rather, it is to create a broader evidence base. A degree can describe a person’s educational experience; a project or work sample can show how that person applies knowledge. Using both can give hiring teams a clearer view of suitability.

The individual responsibility question

Skills-based hiring also changes what candidates are expected to demonstrate. Building a portfolio, completing certifications, working on projects, or developing AI capabilities can require time, money, and access to technology. Not everyone starts with the same resources.

Organisations can reduce some of the burden by providing training, accessible learning opportunities, internal mobility, and transparent assessment methods. Individuals can benefit from developing evidence of what they can do rather than relying only on qualifications. The degree is unlikely to disappear as a signal of education and persistence. What is changing is the amount of information employers and employees need beyond it. By 2030, employability may depend less on holding one static credential and more on combining foundational knowledge with practical capability, technological fluency, communication, judgment, and a willingness to keep learning.

(The author is Founder & Managing Partner, Marching Sheep)

ABOUT THE AUTHOR

Sonica Aron

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