Top 5 Jobs in Education That Are Most at Risk from AI in Malta - And How to Adapt

Introduction: As Malta deepens its reputation as a growing tech hub, education roles from lesson planners to administrative staff face real disruption from AI-powered tools that can tutor, generate curriculum materials and analyse student progress in real time; platforms like the curriculum‑aligned S.U.S.A.N./M.A.R.I.A. project even promise Maltese and English support with reported 97.4% Maltese grammar accuracy, so adaptation is urgent and practical.

Local institutions are already emphasising skills over static job titles - the University of Malta's roadmap focuses on creativity, analytical thinking and lifelong upskilling - while market studies list AI, data and cyber skills among Malta's top in‑demand capabilities.

For educators and support staff the route forward is reskilling: short, workplace‑focused programs that teach promptcraft and AI tool workflows can preserve value and unlock new roles; one accessible option is the AI Essentials for Work bootcamp that teaches prompts, tool use and practical AI applications for any workplace.

Learn more about Malta's workforce shift and skills priorities from the University of Malta and the Top Skills in Malta report.

Methodology: The findings draw on a focused review of Malta's publicly available career and labour‑market instruments - principally Jobsplus Work Exposure Scheme and the national career guidance framework - cross‑checked against recent labour‑market analysis to highlight who is most exposed to automation.

Sources were read for practical details (eligibility, co‑funding and on‑the‑job training in the Jobsplus Work Exposure Scheme) and for the structures that shape school‑to‑work transitions (the Guidance System in Malta's three‑fold career guidance model, career orientation weeks and the striking practice of Year 10 students spending five days shadowing a chosen career).

This pragmatic lens prioritised programme features that enable rapid reskilling (work placements, targeted CPD from the Centre for Labour Studies and the University of Malta, and Jobsplus profiling), so recommendations link directly to existing Maltese routes for retraining rather than abstract national policy alone; see Jobsplus Work Exposure Scheme and the Guidance System in Malta for the source material.

Classroom teachers in Malta are at the sharp end of change: generative AI now speeds routine work like lesson‑generation and curriculum mapping - freeing time but also shifting expectations - while rigorous evidence shows these tools can genuinely lift learning when used well.

A 2025 meta‑analysis found ChatGPT produced a large positive effect on learning performance (g = 0.867) and moderate gains in engagement and higher‑order thinking (g ≈ 0.456–0.457), especially when AI is embedded in interactive, project‑based sequences and used over focused 4–8‑week modules (see the meta‑analysis on ChatGPT's impact in education).

In Malta that means teachers should prioritise facilitation, assessment redesign and prompt‑writing skills so AI augments practical problem‑solving rather than replacing classroom judgment; local debate has already pushed for assessments that require students to demonstrate applied skills, not just reproduce facts (read Malta voices on assessment and AI).

Practical steps are within reach - teacher tools that speed up a 60‑minute, MCAST‑aligned lesson plan can be paired with scaffolded, AI‑supported projects so pupils practise analysis and creativity while teachers keep the human feedback that matters (see Teacher lesson‑generation & curriculum mapping).

The bottom line: when teachers blend AI into interactive, evidence‑based activities they protect their role as designers of meaningful learning, turning a potential risk into a classroom advantage that students can actually feel in their confidence and outcomes.

“It's time to change and we cannot keep looking towards the past. Like every disruptive technology, I believe that this was a wake-up call.” – Alexiei Dingli

Assessment and grading staff in Malta face a clear and immediate shift: AI-powered systems are already streamlining routine scoring and feedback, from multiple‑choice to more advanced essay analytics, which can turn evenings of red‑pen marking into near‑real‑time responses while also surfacing learning gaps that matter for instruction.

Research warns these tools are strongest when run alongside human oversight - AI excels at consistency and scale but still struggles with nuance, bias and transparency - so Maltese assessment teams should prioritise rubric‑tuning, audit trails and comfy workflows that let AI do the heavy lifting while humans handle judgment calls and appeals.

Practical starting points include reviewing technical briefs on AI and auto‑grading to understand capabilities and limits and piloting classroom tools that give rubric‑aligned, immediate feedback before scaling up; local teachers can see how AI speeds lesson and assessment design in Maltese contexts via teacher lesson‑generation & curriculum mapping, and broader guidance on tool selection and classroom pilots is summarised in reviews of AI assessment tools for educators.

The sensible path for Malta's exam clerks, moderators and grading teams is hybrid: adopt automated scoring for efficiency, embed periodic human checks for fairness, and run small, MDIA‑style pilots that prove reliability before changing high‑stakes practice.

“The Writing AccuRater is engineered to deliver immediate, high-quality evaluation of student writing, setting a new standard for automated scoring of writing assessments.” – Alistair Van Moere, MetaMetrics

School secretaries and registrars in Malta are prime candidates for rapid change as education workflow automation moves from promise to practice: routine work - student enrolment, attendance tracking, timetable changes, document filing and compliance checks - is increasingly handled by no‑code platforms that digitise forms, route approvals and keep audit‑ready records so staff spend less time chasing paper and more time helping families and teachers.

Platforms that build workflows from a simple prompt, like FlowForma's education automation tools, show how enrolment pipelines and multi‑step approvals can be transformed into a single, transparent process, while AI‑aware document systems such as Docupile automate naming, tagging and archival so a student's file is available in seconds rather than after a drawer search.

Practical next steps for Maltese schools are small pilots (start with registration or attendance), clear retention and access rules to protect privacy, and training that shifts registrars toward oversight, exception handling and data‑driven reporting; the payoff is tangible - imagine a morning that used to be spent on filing turned into time for parent calls or targeted support, all backed by dashboards that keep compliance and auditors satisfied.

Instructional content creators - curriculum designers, e‑learning developers and multimedia teams - are both most exposed and best positioned to benefit: generative AI can draft course outlines, produce images and scaffold quizzes in minutes, so the new premium work is curating, contextualising and auditing those drafts for Maltese curricula and quality.

Practical playbooks recommend an “AI does the heavy first‑draft, humans do the polish” workflow (Edutopia's lesson‑planning guide shows MagicSchool.ai's useful 80/20 practice), while MIT's classroom strategies offer concrete ways to turn machine outputs into deeper learning - generate concrete examples, design targeted practice quizzes and ask students to “teach the AI” as a comprehension task.

To protect learning value, teams should bake in prompt libraries, bias‑checks and clear data policies (Harvard's GenAI guidance stresses prompt design and human oversight), and link pilots to local standards - see how teacher lesson‑generation & curriculum mapping speeds MCAST‑aligned lessons.

Imagine an instructional designer turning a blank syllabus into a scaffolded, standard‑mapped module in the time it takes to brew a kettle; the memorable shift is from content production to quality control, localisation and creating the human feedback that actually moves learners forward.

Private tutors in Malta are seeing the contours of their role change fast as AI platforms scale high‑quality, curriculum‑aligned support: projects like the S.U.S.A.N./M.A.R.I.A. platform promise Maltese‑and‑English tutoring tied to Form‑level syllabi, built‑in analytics for student progress and even voice tutoring (the platform advertises 100 hours of annual voice chat and 97.4% Maltese grammar accuracy), so routine drill and revision can be automated at scale.

That scalability matters - the same research that finds AI tutoring can help close gaps also underlines how services reach more students without geographic or cost barriers, which is both an opportunity and a disruption for one‑to‑one tutors.

The smart response for Maltese tutors is practical re‑positioning: adopt AI to generate scaffolded practice and diagnostic reports, then sell the human premium - exam strategy, personalised motivation, and nuanced feedback that machines still struggle to match - while linking practice to national priorities on upskilling and equitable access.

For tutors who learn to blend real‑time dashboards and curriculum‑aligned AI prompts into weekly plans, the memorable shift is clear: a 60‑minute session becomes less about rote correction and more about high‑value coaching informed by data and local syllabus alignment.

Explore how S.U.S.A.N. frames these tools and read the evidence on AI tutoring's equity gains for context.\n\n \n \n \n \n \n \n \n \n \n

Conclusion: For Malta the practical verdict is clear - AI is neither an instant job‑killer nor a magic fix; it's a tool that will reshuffle tasks and raise the value of human judgement, creativity and leadership.

Policymakers and schools should run small, evidence‑led pilots, pair automated scoring and lesson‑drafting with human auditing, and invest in fast reskilling so registrars, tutors and teachers can move from routine work to higher‑value roles; American University's review of AI in classrooms calls for this balanced, ethical approach and useful frameworks for implementation (American University review of AI in the classroom).

A concrete, workplace‑focused route is short, applied training - like the 15‑week AI Essentials for Work bootcamp - that teaches promptcraft, tool workflows and job‑based AI skills so Maltese educators can adopt safe workflows and keep the human edge (Nucamp AI Essentials for Work (15-week bootcamp)).

The memorable payoff is practical: routines that once ate evenings of marking or mornings of filing can, with careful pilots and oversight, become minutes of automated support and hours reclaimed for one‑to‑one coaching, curriculum design and equity‑focused work.

“We need a future that is broad and democratic, a future in which people widely understand how AI works - its strengths as well as its dangers and limitations.” – Jennifer L. Steele