Guest blog post by FHRD Member, RSM Malta
Why Judgement Is Becoming the Most Valuable Workplace Competency
AI is changing what work looks like and, with it, the skills and competencies that matter and how organisations select for and develop them. This places growing pressure on how HR teams define, identify and nurture a good hire, particularly in Malta’s talent-scarce market.
How AI is changing which competencies matter
Two years ago, knowing how to use a chatbot or spreadsheet macro could make a candidate stand out. Today, generative AI tools are increasingly familiar across both education and the workplace. Simply knowing how to use an AI tool is therefore becoming a baseline skill.
But knowing how to prompt does not necessarily make someone valuable.
Skills and competencies are not the same thing. The World Economic Forum continues to rank analytical thinking as the top core skill, considered essential by seven in ten employers, while around four in ten of today’s job skills are expected to change by 2030.
Skills may be changing quickly, but underlying competencies such as analytical thinking, judgement and critical reasoning remain highly transferable and increasingly important.
Take verification. It may once have been viewed primarily as a senior responsibility, exercised over somebody else’s work. Today, it can be a first-week requirement exercised over your own.
A finance officer who accepts an AI-generated report without checking it against the underlying figures may create more rework than the tool saved. The people who stand out are therefore not simply those who can generate an answer, but those who can identify when an AI output is wrong and explain why an answer is reliable when it is right.
They have judgement.
Judgement still rests on domain knowledge
Judgement does not come from a workshop on how to use AI tools. It develops through domain expertise, experience and critical thinking.
A compliance officer’s assessment of an AI-flagged transaction depends on understanding the regulation behind it. A hotel revenue manager evaluating an AI-generated pricing forecast needs to understand the season behind it and, in Malta, the difference a major conference or cruise call can make to a particular week.
Research increasingly highlights the importance of maintaining critical engagement when working with AI. When users defer too readily to a tool, there is a risk that the process of questioning, testing and reasoning becomes weaker.
Domain expertise remains an important safeguard, yet it is precisely what graduate hires have not had time to build.
This creates a challenge. Expertise is traditionally developed partly through performing routine tasks, observing patterns, making mistakes and receiving feedback. If AI increasingly performs some of that work, organisations need to consider how junior employees will acquire the experience required to exercise sound judgement later in their careers.
Similar concerns have emerged in other fields where technology has reduced opportunities for hands-on practice. For the junior analyst, trainee accountant or graduate lawyer, the question is therefore not simply how AI can make them more efficient today, but how organisations can ensure they continue developing the capabilities they will need tomorrow.
The selection toolkit is under pressure
This raises an important question for HR teams: how do you identify candidates who have these capabilities?
Well-designed aptitude tests can still provide useful insight, particularly when properly supervised. Work samples and case studies also remain valuable, but increasingly so when candidates are expected to explain and defend their output.
An unsupervised written situational judgement exercise completed at home may now reveal less about a candidate’s unaided reasoning because AI can readily assist with producing a polished response.
What increasingly separates candidates is whether they can explain how they reached a conclusion, challenge assumptions and defend their thinking when questioned.
Recruiters are already adapting, with some employers returning at least one stage of the recruitment process to an in-person setting. But an interview alone does not solve the problem. A CV review followed by a friendly, unstructured conversation remains vulnerable to bias and inconsistency.
Structure matters.
Practical steps for a short-staffed HR team
One relatively simple approach is to give candidates a deliberately flawed AI-generated output during an interview and ask what they would check.
Include three types of error: one straightforward factual mistake, one flaw in the reasoning and one answer that might be correct generally but is wrong in the Maltese context, such as a tax treatment, public holiday or local filing deadline.
Then assess whether candidates can distinguish between “this is wrong” and “this cannot yet be verified”, and whether they can explain what source or information they would use to check it.
The local example is particularly useful because it can help distinguish genuine domain knowledge from generic scepticism.
Second, when setting a case study or work sample, consider allowing candidates to use AI rather than attempting to ban it. Ask them to explain how they used the tool and then have them defend their conclusion live against a question the system could not have anticipated.
A report may be generated in seconds, but someone still needs to be able to stand behind every line of it in a meeting. The purpose is to test whether the candidate has genuinely understood and absorbed the output rather than simply produced it.
Third, organisations can go further and allow candidates to use AI during part of the assessment itself, then evaluate how effectively they use it. This might include the quality of their prompts, whether they verify the output and whether they identify and correct mistakes.
Some large employers are already experimenting with AI-assisted recruitment assessments, particularly for technical roles.
A simpler version can work just as well. Ask: “Tell me about a time you overrode a tool, or accepted what it told you and later regretted it.”
Whichever approach is used, candidates should be assessed against a written marking guide and, where practical, by more than one interviewer. This helps make the interview more structured and the assessment more consistent.
Core competencies must be developed and protected
Anyone who feels their sense of direction or mental arithmetic has declined since relying more heavily on technology already understands the idea of cognitive offloading. Abilities can weaken when they are no longer exercised regularly.
AI extends this discussion into areas such as creativity, problem-solving and critical thinking, precisely the competencies organisations increasingly value.
Research in education illustrates the potential risk. In one experiment, students with unrestricted access to a generative AI assistant performed significantly better while using the tool, but performed worse than students who had never used it when the assistance was later removed. Students using an AI system designed to provide guidance rather than direct answers did not experience the same decline.
Other research into AI-assisted writing has similarly raised questions about recall, cognitive engagement and the extent to which people feel ownership over work produced with substantial AI assistance.
The distinction that matters is therefore between using AI simply to obtain an answer and using it as part of the process of reaching one.
People are more likely to internalise an output when they have been genuinely involved in shaping, questioning and refining it. That habit can be built into how teams work, not only how they recruit.
Teams might ask employees to show how AI was used in producing important work or ask someone to restate the conclusion of an AI-assisted analysis in their own words. Being able to understand and stand behind a conclusion should become a normal expectation rather than an occasional check.
There are also significant opportunities.
Research suggests that AI-enabled coaching can support goal attainment and potentially make structured development more accessible to organisations and employees who may not otherwise have access to individual coaching.
What technology cannot easily replicate is tacit organisational knowledge: the unwritten understanding that develops through mentoring, paired work, observation and honest review conversations.
For junior employees in particular, these interactions provide an important opportunity to develop the practical judgement that automation may otherwise make harder to acquire.
They are not simply inefficiencies to be removed. They are part of how capability develops.
The changing role of HR
The tools will continue to change. Refining HR processes around them is therefore not simply a matter of introducing an AI policy. It is an ongoing people and operational challenge.
As AI reshapes how work is carried out, HR increasingly needs to act as an internal adviser, helping the organisation understand not only which skills it needs today but how roles, competencies and development pathways may need to evolve.
Talent management is becoming a moving target. Organisations that regularly reassess how they recruit, develop and evaluate people will be better positioned to adapt as that target continues to shift.
How RSM Malta can help
At RSM Malta, we support organisations in navigating both the opportunities and risks created by an evolving technological and regulatory environment.
AI offers considerable potential, but meaningful value creation requires more than adopting a new tool. Organisations may need to reconsider operating models, processes, roles and structures, strengthen talent and performance management practices, establish appropriate governance and manage the accompanying organisational change and risk.
Our Digital, Human Resources and Governance, Risk and Compliance teams work with organisations to consider these challenges as part of a wider transformation rather than in isolation.
To discuss how RSM Malta can support your organisation in responding to the impact of AI on technology, people and risk management, contact our team.
Article written by Yashar Dominic Klipp – Consultant, Specialised Executive Services and Kelly Spiteri– Manager, Digital Operations
