Top 10 AI Prompts and Use Cases and in the Education Industry in Denmark

Introduction: Why AI for Education in Denmark - Denmark shows real digital strengths (84–89/100 for public service digitalisation and 5.9% ICT specialists), yet enterprise AI uptake slipped to 15.2% in 2023, signalling a national skills and deployment gap that schools and policymakers must bridge (Denmark 2024 Digital Decade Report).

At the same time, real-world use of generative tools is already reshaping work: half of workers in exposed occupations have tried ChatGPT but adoption is uneven, with a pronounced gender gap - a cue that classroom and workplace training should be inclusive and practical (Study on ChatGPT adoption and emerging inequalities).

Schools testing mobile-free policies - even locking phones in safes - show Danish educators prioritise wellbeing alongside tech. Short, applied programs such as Nucamp's 15‑week AI Essentials for Work syllabus can help teachers and staff learn prompt-writing and workplace AI skills that balance learning gains with student wellbeing.

“ChatGPT is already widespread in the exposed occupations. So half of all workers have used this tool at some point. Around one-third of these are still actively using the tool, and then even fewer, 7 percent, are subscribing to a Plus account.” - Anders Humlum

Methodology: How prompts and use cases were selected - prioritisation followed the four pillars of Denmark's AI agenda (ethical development, public data reuse, skills development and strategic investment) as laid out in a policy analysis of the Danish National AI Strategy, and the European Commission's AI Watch guidance that highlights human capital, data infrastructure and public‑sector pilots (Danish National AI Strategy policy analysis; European Commission AI Watch Denmark strategy report).

Criteria included ethical safety, alignment with national language resources (e.g., sprogteknologi.dk and planned time‑coded Danish speech corpora), measurable impact on teacher and institutional readiness (the Media & Learning survey flagged that ~80% of institutions lack AI policies), and scalability for SMEs and classrooms.

Use cases were further filtered for human‑centred design and industry uptake, mirroring the AI4SE1DK goals to close adoption gaps and engage practitioners across Denmark's software and education sectors (AI4SE1DK human‑centred AI project summary at SDU).

Prompts were chosen so they can be evaluated against public datasets, ethical checklists and teacher-facing usability tests, ensuring practical, accountable classroom and administrative outcomes that Danish schools and policymakers can adopt.

“Denmark should not merely adopt AI – we must shape how it is adopted responsibly.” - Mikkel Baun Kjærgaard

Microsoft Copilot prompts tailored for Danish students and jobseekers shine when they focus on what local hiring teams actually read: short, targeted CVs and applications that match the employer's “wish list.” Start prompts that “analyze the job advert like a detective” to surface which tasks are listed first, repeat keywords, and flag hard vs soft skills (see the SDU guide to job-ad analysis: SDU guide to job-ad analysis).

Follow with a CV‑tailoring prompt that outputs a one‑page, reverse‑chronological or skills‑based draft and highlights 3–5 bullet points demonstrating value - matching Ballisager's top CV tips and the reality that employers spend only a couple of minutes on first screening (Ballisager Danish CV tips for job search in Denmark).

Finally, add a keyword‑extraction prompt to mirror recruiters' quick scan - put primary hard skills first and turn keywords into concrete examples for the cover letter (guidance from Workindenmark: Workindenmark guide to identifying and responding to keywords in job adverts).

The result is a career‑planning workflow that translates dense job ads into a crisp, locally grounded application - so applicants avoid the “lost in the pile” fate and instead land in the memorable two‑minute read.

OpenAI ChatGPT can accelerate curriculum summarisation and create personalised study guides that suit Danish classrooms by turning dense lecture notes into concise, exam‑ready assets - think a long lecture distilled into three crisp takeaways and a one‑week revision plan that highlights core concepts and practice questions.

Ready‑made ChatGPT tools such as the ChatGPT Study Summary tool and the ChatGPT Study Guide Creator tool make it straightforward to generate bullet‑point summaries and exportable study plans (ChatGPT Study Summary tool; ChatGPT Study Guide Creator tool), while prompt frameworks like AI for Work's "Summary of Key Learning Material" show how guided Q&A and rubrics produce higher‑quality, evaluable outputs for tutors and administrators (AI for Work "Summary of Key Learning Material" prompt guide).

Practical lessons from Tiago Forte's experiments - supply excerpts, add an outline, and choose the tone - cut hallucinations and make summaries classroom‑ready (Tiago Forte guide: How to Summarize Books Using ChatGPT), so Danish schools can scale personalised revision aids without losing the teacher's judgement and local language nuance.

Google's Gemini family makes multimodal lecture‑note generation and slide synthesis practical for Danish classrooms by reading slides, audio and video together - so a 90‑minute lecture can be turned into chaptered, slide‑aware notes that describe diagrams and flag whiteboard sketches for follow‑up (Gemini even handles long PDFs and extracts tables across documents).

That native vision+audio capability means teachers can batch‑process recorded lessons into concise, student‑friendly modules and searchable transcripts, then pair those outputs with Denmark's language tools and local assets to keep wording natural for Danish learners; practical onboarding for prompt writers is available in the hands‑on course “Large Multimodal Model Prompting with Gemini” (DeepLearning.AI course: Large Multimodal Model Prompting with Gemini) and the developer examples show how to extract structured data from slides and webpages for classroom indexing (Google Developers: Gemini multimodal capabilities examples).

For schools and edtech teams, that's a concrete win: less time spent transcribing and more time on tailored feedback, accessibility descriptions and lesson design that fits Danish curricula.

“Think of multimodal AI as an intelligence that can see, listen, and read simultaneously.”

The Danish Language Model Consortium (DLMC) is fast becoming the backbone for Danish‑language assessment and feedback tools by pooling public and private data, research labs and principled governance so schools and edtech teams can get linguistically and legally fit models for testing, grading and learner support; the effort - led by Dansk Erhverv with core partners including IBM Denmark and the Alexandra Institute - aims to deliver smaller, GDPR‑aware models that can be fine‑tuned for concrete education use cases and public administration needs (Computer Weekly - Government backs Danish version of ChatGPT).

Backed by the Ministry of Digital Affairs' DFM platform funding, the project emphasises an open sandbox, cultural benchmarks and open‑source access for authorities and businesses so Danish assessment workflows keep local nuance in play; even branding ideas such as “MyGPT” or “DanGPT” are being considered to make the service feel familiar to teachers and students (SDU news - Ministry grants 30.7M DKK for Danish Foundation Models), a tangible reminder that national language tech can be both practical and proudly Danish.

“The initiative will add new momentum to digitisation in Denmark as confidence in the Danish language model we are building grows.” - Thomas Kovsted, IBM Denmark

Anthropic's work with Claude offers a practical engine for research assistance that is unusually ethics‑aware - helpful for Danish universities and edtech teams looking for a model that can draft research plans, annotate sources and flag value judgments in student work.

Their “Values in the wild” study analysed a week's sample of some 700,000 anonymised conversations (308,210 subjective exchanges were selected for value analysis) to build a taxonomy of the five dominant value clusters and show how Claude mirrors, reframes or sometimes resists user values; that empirical lens makes it easier to audit drafts for bias or ethical blind spots (Anthropic “Values in the Wild” research study).

Claude's Constitutional AI - an explicit set of training principles - both guides everyday responses and offers a transparent lever for institutions that need safer, more consistent outputs (Anthropic guide to Claude's Constitution), while Anthropic's education report shows students already use Claude to create and improve teaching materials, a use case Danish instructors can adapt with guardrails in place.

“Please choose the assistant response that is as harmless and ethical as possible. Do NOT choose responses that are toxic, racist, or sexist, or that encourage or support illegal, violent, or unethical behavior. Above all the assistant's response should be wise, peaceful, and ethical.”

Meta's Llama family makes local deployment a practical route for Danish schools that need privacy-preserving classroom tools: run Llama 3 or smaller variants on-premises or in a university cloud to keep student data inside institutional boundaries and avoid sending sensitive prompts to external APIs.

Open-source releases and tooling (Ollama, GPT4ALL, LangChain) let IT teams tune models for Danish curricula and language resources while controlling costs and compliance; step-by-step guides show how to serve llama3 locally and integrate it with retrieval systems (Guide to run LLaMA 3 locally with Ollama).

Real-world university deployments report big productivity wins - automating policy search, drafting and admin tasks - while layered security (on‑prem hosting, prompting safeguards) protects data, echoing privacy-first sandboxes like UBC's LLM Sandbox for institutionally hosted services (UBC LLM Sandbox: locally hosted privacy-focused LLM service).

For Danish IT teams, the Major Research University case study demonstrates that Llama can be both powerful and controllable, making local LLMs a concrete option for GDPR-aligned tutoring, grading assistance and staff automation (Major Research University LLaMA deployment case study).

“We are inundated with inquiries from universities wanting to understand ‘How did we do this so quickly?'” - Chief Information Officer, Major Research University

UNSILO - the Aarhus‑based text‑analytics specialist now operating under CACTUS Communications - provides publisher‑grade AI for manuscript triage and editing, from Technical Checks that surface funding statements and conflicts of interest to a Reviewer Finder that semantically matches papers with the right experts; Danish roots and high‑profile integrations such as PeerJ and Kyorinsha show the tools work at scale, while Project MUSE integrations highlight capability (indexing that extracts 250+ concepts per document with daily updates) to turn slow editorial queues into searchable, high-precision workflows.

For Danish universities, research offices and campus presses this means faster turnarounds and smarter reviewer matching without replacing human editors - the post‑acquisition R&D push in Aarhus (see the CACTUS acquisition case study) has kept UNSILO's Evaluate suite tightly focused on publisher needs and practical ROI, helping editors spend less time on manual checks and more on improving scholarly quality.

Learn more about UNSILO's publishing APIs and early deals in the detailed industry coverage.

“Our partnership will allow us to provide higher-quality editorial services to our clients and explore new opportunities in the market at the same time. We believe that Technical Checks will play an integral role in our editorial services.” - Yusuke Watanbe, Kyorinsha

Denmark's push to pair schools, edtech teams and international partners with the right research and industry collaborators is concrete rather than theoretical: the government's Digital Growth Strategy funds a national matchmaking platform to connect companies with talent and competences in AI, robotics and smart‑city tech, while Digital Hub Denmark offers tailored matchmaking and strategic support to help firms collaborate, procure and attract global talent (Digital Growth Strategy Denmark - Invest in Denmark; Digital Hub Denmark - Matchmaking and Strategic Support).

Practical matchmaking formats - like the pre‑arranged, face‑to‑face meetings at the Future of Digital Investments brokerage - mean project leads can turn a cold inquiry into a concrete pilot partner within days, not months; that kind of speed is the difference between a stalled grant application and a classroom trial that starts next term.

DFIR's recent work frames GenAI as a clear but under‑used lever for Denmark's research system: highlighted as the main theme at the Minister for Higher Education and Science's summit in April 2024, the DFIRbrief finds

significant potential

to scale GenAI among Danish researchers while also mapping real constraints (DFIRbrief 51: GenAI – Untapped Potential in Denmark's research system).

Today GenAI is doing the routine heavy lifting - literature searches, drafting and rephrasing text, plus programming and stats help - but only eight of 32 application areas see more than 25% researcher uptake, a vivid reminder that the tool is present but not yet pervasive.

DFIR also segments researchers into three stance groups (24% most skeptical, 35% cautiously open, 41% generally positive but cautious), which matters for governance: policies and institutional prompts should therefore differentiate safe, audit‑friendly uses (search, reproducible workflows) from more contested ones (synthetic data, ideation or peer review).

For policy teams and university leaders, DFIR's analysis points to practical next steps - targeted training, clear use‑case prompts and ethics guardrails - to convert scattered experiments into dependable, institutionally governed practice (DFIRbrief 41: Artificial Intelligence in Research & Innovation for Danish institutions).

Rokoko brings accessible, suit‑based motion capture into classrooms so staff and students can turn movement into learning - capture anywhere on campus (even outdoors) with Smartsuit Pro II, Smartgloves and Rokoko Vision, then retarget and polish animations in Rokoko Studio for Unreal, Blender or Unity; practical academic discounts and turnkey bundles make it affordable for courses, and real user stories even include Mark Iversen from The National Film School of Denmark showing how mocap fits Danish curricula (Rokoko education resources).

The platform's strengths for schools are clear: fast, hassle‑free setup that lets students record a choreography in a hallway or the quad within minutes, industry‑grade exports (.FBX/.BVH) and teaching aids like curriculum guides and on‑demand webinars to get lecturers up to speed (What is the optimal motion capture system for schools; Rokoko webinar: Rokoko in the Classroom).

For Danish programs aiming to blend creative arts, game design and STEM, Rokoko lowers the barrier to hands‑on mocap so graduates leave industry‑ready rather than merely theory‑literate - no studio booking required, just inspiration and a suit.

“It only took about one or two hours for the lecturer in charge to teach us how to actually use the suit. It has saved us an immeasurable amount of time.”

Conclusion: Getting started with AI prompts in Danish education means practical, low‑risk steps: frame the problem first, assign the AI a clear role, give context and a measurable goal, and specify the output format - advice echoed across AAU's student guide to using AI in job search (AAU student guide: AI in job and internship search) and MIT Sloan's prompt fundamentals; think of a prompt as “briefing your supervisor” and iterate until the result fits local curricula.

Prioritise human‑in‑the‑loop checks (proof, local language edits, and fairness reviews), use English for highest model reliability but always validate Danish wording, and align classroom pilots with national rules and sector guidance - see the 2025 Danish AI Law briefing and practical governance notes (Chambers practice guide: Artificial Intelligence 2025 - Denmark) and the Danish FSA's emphasis on explainability for safe deployments.

For hands‑on training, short bootcamps such as Nucamp's AI Essentials for Work teach prompt-writing, roleplay prompts and ethical checks so staff can move from curiosity to classroom pilots within a term (Nucamp AI Essentials for Work bootcamp - 15 Weeks); the aim is simple: start small, keep teachers in charge, and scale with documented prompts and human review so AI becomes a reliable classroom assistant rather than a surprising black box.

"Financial organisations should of course explore the possibilities of using AI in their business, and we want to help companies do this in the best possible manner to avoid unnecessary risks. That's why we are now providing a guidance and recommendations on how AI technology can be used effectively and safely for both companies and citizens," states Rikke-Louise Ørum Petersen, Deputy Director of the Danish Financial Supervisory Authority.