The Complete Guide to Using AI in the Hospitality Industry in Denmark in 2025

Denmark's hotels face a clear 2025 moment: AI is no longer optional but a practical lever to lift guest experience and cut costs, from AI-driven personalization and voice assistants to contactless check‑ins and smart energy controls that can shave energy bills by up to 40% and boost revenue through tailored offers (see Hospitality technology trends and innovations: Hospitality technology trends and innovations for hotels, AI in hospitality market forecast and growth outlook).

European markets - Denmark included in recent country analyses - are part of a rapidly expanding AI-in-hospitality market that forecasters expect to climb strongly over the next five years, making investments in predictive pricing, chatbots and IoT-based rooms a strategic necessity.

Local operators can start small: automate invoices and guest messaging, pilot a predictive-occupancy model, and test Danish-focused prompts and use cases to prove ROI before scaling (see Top AI use cases for Danish hospitality operators: Top AI use cases for Danish hospitality operators).

“Hotels know they need to set loftier goals and innovate. This can't be done without the technology and the right partnerships.” - Nick Shay, Group Vice President, Travel & Hospitality, International Markets

Denmark's hotel sector sits squarely inside a fast‑moving global market: analysts put AI in hospitality at $0.23 billion in 2025 and project it could reach about $1.44 billion by 2029, driven by rapid CAGR figures that signal aggressive investment in personalization, revenue management and operational automation.

At the regional level, Nordic firms - Denmark included in regional analyses - are among the most ready to spend on generative AI (Nordic average projected spend per company was cited at $49.7 million) but they balance ambition with caution: leaders report strong interest in productivity and revenue‑focused use cases while flagging talent gaps, data accessibility limits (only 22% rate data accessibility as good or excellent) and regulatory readiness as real barriers.

Practical hotel applications mirror those industry roadmaps - content generation, merchandizing and AI‑powered customer service are high‑value starting points - but they require careful prompt engineering, fine‑tuning and governance to avoid factual errors and trust issues.

For Danish operators the takeaway is clear: treat pilots as measured experiments, pair them with data and compliance workstreams, and design for scale from day one to capture the growth this market forecast anticipates (The Business Research Company: AI in Hospitality global market forecast, Cognizant analysis of Nordics generative AI adoption, Publicis Sapient generative AI use cases for travel and hospitality).

“It's clear that LLMs have the potential to transform digital experiences for guests and employees much faster than we previously thought,” says Head of Customer Experience for Travel and Hospitality at Publicis Sapient, J F Grossen.

Denmark's AI case is pragmatic: a small, well‑connected ecosystem backed by clear government action makes the country a very favourable place to pilot hotel AI projects.

The national digitalisation strategy (2024–27) and a funded Regulatory Sandbox for AI give hoteliers hands‑on access to regulatory advice - practical GDPR checks, risk classification and AI Act alignment - so pilots don't stall on legal uncertainty; the sandbox model even mirrors EU best practice that has cut time‑to‑market in other sectors EU overview on regulatory sandboxes.

The sandbox is run by the Agency for Digital Government together with the Danish Data Protection Agency and has already completed a first round of projects, for example Tryg Forsikring and Systematic; a second round opened in 2025 with a flexible, four‑month guidance course of up to four meetings and free expert support that produces a summary report to help others scale responsibly announcement of the sandbox second round opening (2025).

Denmark also plugs into EU testing and innovation networks (TEFs and EDIHs) that can supply technical capacity and test sites, so smaller hotel groups can access infrastructure and compliance advice without building it all in‑house national practice guide on AI in Denmark.

That blend of modest market size, early regulatory clarity and practical, project‑level help is one of Denmark's biggest competitive advantages for hospitality AI pilots.

“The experiences from last year's sandbox course have given both us and the participants a deeper understanding of how AI and GDPR interact. That's why we look forward to the next course with great interest.” - Cristina Angela Gulisano, Director, Danish Data Protection Agency

Denmark's new AI bill, introduced on 26 February 2025 and set to supplement the EU AI Regulation if enacted (target entry into force 2 August 2025), brings practical duties hotels must plan for now: the law formalises that AI remains subject to data protection, IP, employment and liability rules, and it names the Agency for Digital Government, the Danish Data Protection Agency (DDPA) and the Court Administration as national supervisors with powers to demand technical information, conduct on‑site inspections, issue injunctions and impose fines - meaning hospitality operators should map every AI touchpoint, classify systems by risk and be ready to demonstrate how models make decisions and which data they use (see the Denmark AI practice guide for legal detail and the enforcement summary at IUNO).

At the same time Denmark is pushing separate copyright-style protections to curb deepfakes - giving individuals rights to have unauthorised AI images or voice clones taken down and to seek compensation - a timely reminder for hotels using guest imagery, voice assistants or marketing avatars to secure explicit consent and robust contractual IP terms with vendors (the World Economic Forum coverage documents the practical risks and recent fraud cases).

Practically: treat pilots as governed projects (DPIAs, human‑in‑the‑loop safeguards, data minimisation, clear procurement clauses), document training data and prompt engineering, and be ready for supervisory visits so guest trust and regulatory compliance travel together - because a single viral deepfake or unauthorised voice clone can blow up reputation and liability overnight.

“a world where our synthetic likeness is incredibly malleable … we need to be reevaluating what it means to be safe as yourself.” - Henry Ajder

Legal essentials for Danish hotel operators start with a clear line: GDPR applies in Denmark and is fleshed out by the Danish Data Protection Act, so every AI touchpoint must be treated as personal‑data processing (see the Denmark overview at DLA Piper: Data protection law in Denmark - GDPR overview).

Practical priorities are familiar but non‑negotiable: map where guest data lives, document legal bases for each use (contract, consent, legitimate interest), run DPIAs for high‑risk or automated profiling, and appoint a DPO when processing is large‑scale or core to your business.

Contracts matter - written processor and joint‑controller agreements with clear security and deletion clauses are required - and technical safeguards such as encryption, pseudonymisation and access controls are expected by the Danish regulator.

Know the timelines too: breaches that risk individuals must be notified to Datatilsynet within 72 hours, and enforcement can be costly (fines up to 4% of global turnover or €20M); courts have already fined hotel groups for failing to delete hundreds of thousands of guest records, making retention schedules and automated deletion more than paperwork.

For hotel‑focused guidance on assigning controller/processor roles, privacy notices and e‑marketing rules, see the industry briefing at Bird & Bird: Data protection for hotels in Denmark - controller and processor guidance, and review a live example of retention and cookie practice in Arp‑Hansen's policy to shape practical safeguards that protect guests and the business alike (Arp‑Hansen Hotel Group privacy and cookie policy - retention and cookie practice example).

Top AI use cases Danish hotels should prioritise in 2025 centre on smarter revenue and back‑office automation: AI‑powered dynamic pricing and RMS tools that adjust rates in real time to capture peak demand and protect RevPAR (see a practical guide to Practical guide to hotel dynamic pricing), integrated personalization engines that turn CRM and booking signals into tailored packages and upsells across channels, and AI that folds ancillary streams (F&B, spa, event space) into unified forecasts so every revenue line is optimised.

Equally important are scalable, cloud‑native pricing platforms and microservices that make hour‑by‑hour rate updates feasible and measurable (Hotel dynamic pricing solutions and development trends), plus practical automation in finance - OCR invoice capture and ERP mapping - that cuts admin time and error rates for Danish operators (Automated invoice and accounting processing for hotels).

Success hinges on clean feeds (PMS/CRS/OTA/CRM), a management‑by‑exception approach so humans oversee edge cases, and continuous A/B testing to keep guest trust intact while lifting yield across the business.

“playing Tetris, but with the advantage that you can see what size blocks of demand are coming through beforehand.”

Choosing AI vendors in Denmark means balancing local expertise with iron‑clad data controls: start your shortlist with domestic consultancies (there are 97 AI consulting firms listed in Denmark, many in the 11–50 employee range) so you get partners who know Danish regulators and market realities (Top AI Consulting Companies in Denmark); then insist on contract language that spells out controller/processor roles, deletion timelines and IP ownership, plus a robust DPA and security SLA before any pilot.

Protect sensitive guest data by using a secure virtual data room for due diligence and vendor file exchange - pick providers with GDPR alignment, AES‑256 encryption, two‑factor authentication, redaction tools and comprehensive audit logs to reduce exposure when sharing training data or contracts (15 Best Virtual Data Room Providers for Danish Companies).

Operationally, follow a structured integration playbook - map data flows, classify AI risk, log queries and outputs, require human‑in‑the‑loop controls and regular audits - mirroring the nine‑step responsible‑assistant approach that ties use‑case definition to continuous QA and compliance checks (Implementing Responsible AI Assistants in Denmark).

Vetting vendors is not a checkbox exercise: demand evidence (pen‑test reports, ISO/SOC certifications, local references) and plan for an extended security partner or in‑country team to run AI‑powered threat detection as part of ongoing risk management - because a single uncontrolled data share can turn a promising pilot into an expensive, reputation‑risking incident.

Governance for AI projects in Danish hospitality must be practical and risk‑aware: treat procurement as a legal process as much as a tech decision, starting with market dialogue and clear, objective award criteria to preserve the EU principles of equal treatment, transparency and proportionality (see the ICLG overview of ICLG guide to Denmark public procurement laws and regulations 2025).

Use risk‑based contract management - document choices, build measurable KPIs, require supplier risk‑management plans and rights to on‑site inspection and corrective action (Scandic's Supply Chain Code is a good model for contractual controls and termination clauses: Scandic Supply Chain Code of Conduct for supplier controls and termination clauses).

For novel AI buys, the innovation partnership or competitive‑dialogue routes allow negotiation while keeping competition fair, but beware the mandatory standstill (typically 10 calendar days) and the Complaints Board remedies that can suspend award decisions - a single challenged award can pause a rollout during the standstill and invite formal review.

Practical mitigations: run a short pre‑market consultation, require certifications and audit evidence from vendors, embed termination and remediation clauses up front, and use procurement tools to automate approvals and supplier monitoring so legal risk, operational risk and reputational exposure travel together rather than separately.

Turn AI curiosity into repeatable value with a clear, Denmark‑first pilot‑to‑scale roadmap: start by selecting one high‑impact, low‑risk use case - think AI‑driven dynamic pricing or automated invoice/OCR for finance - and scope a small, measurable pilot so teams can learn fast without jeopardising guests or bookings; practical pilots deliver real numbers (for example, an AI pricing pilot cited a 17% RevPAR uplift in a published case study on dynamic pricing) so define KPIs up front and run A/B tests to prove causality (case study: AI-driven dynamic pricing for hospitality and F&B).

Build in human oversight, transparent decision‑rules and a talent plan from day one - Boston Consulting Group warns that while Danish leaders expect big gains, only a small share move beyond pilots and many cite talent gaps - so recruit or train reviewers who can manage edge cases and model drift (Boston Consulting Group report on generative AI adoption in Denmark).

Use Denmark's favourable testbed conditions and high adoption rates to partner locally, reuse public research and access pilots at scale - 28% of Danish companies already use AI - then codify successes into standard operating procedures, procurement clauses and KPIs for roll‑out (Invest in Denmark analysis: Denmark tops Europe in AI adoption).

The payoff is pragmatic: a tightly run pilot will surface data issues, governance gaps and quick revenue signals faster than any committee - turn those lessons into a documented playbook, then scale one validated use case at a time.

In short, Denmark's hospitality sector faces a clear choice: treat the next 24 months as a compliance scramble or as a chance to build trusted, guest‑centric AI that wins bookings and avoids costly retrofits - because the legal timetable is now visible (national bills and the EU AI Act milestones converge around August 2, 2025) and regulators are moving from guidance to enforcement.

Practical steps are straightforward and local: run small, measurable pilots inside the national regulatory sandbox, document data and DPIAs, require human‑in‑the‑loop safeguards for guest‑facing systems and lock procurement and IP terms into contracts so a single deepfake or unauthorised voice clone doesn't become a reputational crisis.

Denmark's testing ecosystem and targeted guidance make pilots feasible; marrying that with skills training turns compliance into competitive advantage - consider building talent with a focused course such as Nucamp's Nucamp AI Essentials for Work (15-week bootcamp).

For legal detail and the moving regulatory deadlines, see the Chambers Denmark AI practice guide (2025) and the EU AI Act implementation timeline to plan realistic rollouts that protect guests and revenue.

“AI isn't a tech-department issue; it's a CEO-level conversation about the soul of travel.” - Julia Simpson