From Motivation to Implementation: Exploring Practitioners' Perceptions of Artificial Intelligence in Danish Environmental Assessment Practice
Author
Filipsen, Simone Rosenmaier
Term
4. Term
Publication year
2025
Submitted on
2025-05-28
Pages
24
Abstract
Miljøvurdering (Environmental Assessment, EA) – processen med at vurdere miljøpåvirkninger af projekter og planer – påvirkes i stigende grad af bæredygtighedsdagsordener og digital udvikling. Blandt nye teknologier vækker kunstig intelligens (AI) opmærksomhed for sit potentiale til at øge effektiviteten og styrke analyser i EA-arbejdet. Alligevel er AI kun sparsomt taget i brug i praksis. Dette studie undersøger, hvordan danske praktikere opfatter muligheder og barrierer, og hvordan det former deres motivation for at implementere AI i EA. Med udgangspunkt i det teoretiske rammeværk ‘Spaces for practice’, som belyser hvordan regler, ressourcer og relationer former handlemuligheder i praksis, er der gennemført semistrukturerede interviews med 19 danske praktikere: konsulenter, myndigheder og udviklere. Resultaterne viser en stærk interesse for at afprøve AI, især til at automatisere rutineprægede opgaver, skabe mere ensartede rapporter og understøtte videndeling. Samtidig peger deltagerne på væsentlige barrierer: begrænset viden og kompetencer, mangel på retningslinjer og metoder, bekymringer om datakvalitet og -pålidelighed samt organisatoriske begrænsninger. Desuden skubbes ansvaret for at igangsætte forandring ofte mellem aktører, hvilket understreger behovet for fælles retning og tydeligere rammer. Konklusionen er, at motivationen for AI i EA er udtalt, men at realisering kræver institutionel opbakning, fælles standarder og gennemsigtigt samarbejde. AI’s fremtidige rolle i EA afhænger ikke kun af teknologien i sig selv, men også af de sociale og strukturelle betingelser, der gør ansvarlig implementering mulig.
Environmental Assessment (EA)—the process of evaluating the environmental impacts of projects and plans—is increasingly shaped by sustainability goals and digital innovation. Among new technologies, artificial intelligence (AI) stands out for its potential to boost efficiency and strengthen analysis in EA work. Yet adoption in real-world practice remains limited. This study explores how Danish practitioners perceive opportunities and barriers, and how these perceptions shape their motivation to implement AI in EA. Guided by the ‘Spaces for practice’ framework, which examines how rules, resources, and relationships enable or constrain action, we conducted semi-structured interviews with 19 Danish practitioners: consultants, authorities, and developers. The findings show strong interest in trying AI, especially to automate repetitive tasks, improve consistency across reports, and support knowledge sharing. At the same time, participants highlight significant barriers: limited knowledge and skills, a lack of clear guidelines and methods, concerns about data quality and reliability, and organizational constraints. Responsibility for initiating change is also frequently deferred among actors, indicating a need for shared direction and clearer frameworks. The study concludes that while motivation for AI in EA is strong, turning it into practice requires institutional support, common standards, and transparent collaboration. The future role of AI in EA depends not only on the technology itself, but also on the social and structural conditions that enable responsible implementation.
[This summary has been rewritten with the help of AI based on the project's original abstract]
Keywords
Documents