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Report | Doc. 16240 | 09 September 2025

Artificial intelligence and migration

Committee on Migration, Refugees and Displaced Persons

Rapporteur : Mr Petri HONKONEN, Finland, ALDE

Origin - Reference to committee: Doc. 15952, Reference 4805 of 15 April 2024. 2025 - Fourth part-session

A. Draft resolution 
			(1) 
			Draft resolution adopted
unanimously by the committee on 24 June 2025.

(open)
1. The Parliamentary Assembly acknowledges the transformative potential of artificial intelligence (AI) across a range of sectors, including migration management. AI systems – capable of autonomous decision making and complex data analysis – are increasingly used in border surveillance, visa processing, biometric identification, natural language processing and integration support. These applications promise enhanced efficiency and service accessibility for migrants, refugees and asylum seekers.
2. The Assembly emphasises, however, that technological innovation must not come at the expense of fundamental rights. If wrongly used, AI can reinforce structural inequalities, infringe on privacy and undermine asylum protection. The Assembly therefore reiterates its call for all Council of Europe member States to sign and ratify the Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law (CETS No. 225, hereinafter the “Framework Convention on AI”), which aims to ensure the development and deployment of AI in line with human rights standards and explicitly prohibits AI applications that violate the right to seek asylum, as stated in Article 5.
3. AI-driven modernisation must be carried out in a way that minimises dangerous effects and risks for migrants, refugees and asylum seekers, such as discrimination and bias, and that does not unintentionally reinforce existing stereotypes or prejudice. States should rather harness the potential of AI to foster a more inclusive, secure and humane migration system.
4. Recognising the profound impact that AI can have on individual rights and liberties, the Assembly stresses that AI should support – not replace – human decision making in migration and asylum processes, even if in some cases, AI may offer greater security and effectiveness than human decision making alone, by reducing the scope for human error. All AI tools must be transparent, accountable and subject to oversight, and be deployed in alignment with key international instruments, including the European Convention on Human Rights (ETS No. 5, hereinafter the “Convention”), the 1951 United Nations (UN) Convention relating to the Status of Refugees as amended by the 1967 Protocol (“Refugee Convention”) and the Charter of Fundamental Rights of the European Union (EU).
5. Noting that the EU Artificial Intelligence Act classifies migration-related AI as high-risk technology, the Assembly underscores the need for additional safeguards. The use of AI in migration, asylum and border control management must not allow for the bypassing of international obligations, in particular under the Refugee Convention. Nor should they be used to in any way infringe on the principle of non-refoulement, or to deny safe and effective legal avenues into States’ territory, including the right to international protection.
6. It is important therefore that AI systems in migration and asylum procedures undergo human rights, democracy, and rule of law impact assessments before their deployment. The Assembly recommends the use of the Council of Europe HUDERIA methodology to identify and mitigate risks, including algorithmic bias and privacy violations. Oversight must be embedded throughout the life cycle of AI systems with independent evaluations and mandatory human review.
7. The Assembly calls for a prohibition on the use of AI tools such as automated credibility assessments, emotion recognition and risk profiling based on nationality or ethnicity. These technologies lack scientific validity and are incompatible with Articles 3 and 14 of the Convention.
8. Noting the critical importance of data protection, privacy and security in the use of AI for asylum procedures, the Assembly emphasises that sensitive data, including biometrics, interview transcripts and country-of-origin information, must be end-to-end encrypted and must not be shared with the country of origin in case of risk of persecution, in accordance with the Data Protection Policy of the Office of the United Nations High Commissioner for Refugees (UNHCR).
9. Artificial intelligence applications in migration management must thus balance efficiency gains with rigorous protection of human rights at all stages of the migration journey. The specific issues related to the use of AI in the field of migration must be addressed for each distinct stage of the process, from pre-departure activities to transit, arrival, stay, circulation, temporary or permanent return and sustainable (re)integration. Priority should be given to safeguards against bias and human oversight and to ensure the dignity of migrants, refugees and asylum seekers, as follows.
10. At the pre-departure stage, AI tools used in visa and asylum screening should undergo human rights impact assessments before deployment. Systems like the European Travel Information and Authorisation System (ETIAS) should provide for manual review in cases flagged as high risk. All screening tools must be transparent and free from discriminatory outcomes. AI-powered chatbots can provide real-time multilingual information to migrants, refugees and asylum seekers, provided they disclose their automated nature and comply with ethical standards to avoid spreading misinformation.
11. As regards labour migration via the appropriate channels, AI tools may be used to streamline, in a fair and accessible manner, the application process for employment and residence permits. AI may further support the detection of exploitative recruitment practices by identifying predatory employers and alerting the relevant authorities. AI tools such as visa checkers should be bias-audited and provide transparent outcomes that can be contested.
12. The Assembly encourages the ethical use of AI in climate migration forecasting through the analysis of environmental and socio-economic data to improve humanitarian planning in accordance with its Resolution 2401 (2021) “Climate and migration”. AI tools such as those developed by the International Organization for Migration (IOM) can provide policy makers with a clearer predictive picture of climate-driven displacement patterns. Such predictive models can inform proactive support measures.
13. AI may also be used to identify and disrupt smuggling networks through responsible data analysis.
14. During the transit stage, the Assembly stresses the need for strict regulation of AI surveillance technologies. Predictive policing and biometric identification must be limited to strictly necessary and proportionate use, and all biometric data must be encrypted and restricted to authorised personnel. The Council of Europe Framework Convention on AI limits biometric categorisation to strictly necessary and proportionate cases. AI systems like the European Union’s European Border Surveillance System (EUROSUR) that monitor border movements must comply with the IOM’s 2023 Data Protection Principles.
15. Surveillance technologies for migrants, refugees and asylum seekers in transit must be regulated with a view to protecting their rights, and AI-driven mass surveillance, such as drones and facial recognition, should be prohibited. AI may be used in a positive sense to support humanitarian corridors by using conflict mapping to identify safer transit routes.
16. The Assembly recognises the essential role of eu-LISA (the European Union Agency for the Operational Management of Large-Scale IT Systems in the Area of Freedom, Security and Justice) and other EU bodies in managing migration-related databases such as the Schengen Information System (SIS), the Visa Information System (VIS), and Eurodac (the European Union’s centralised biometric database). Co-operation between EU and non-EU Council of Europe member States is important to ensure consistent data protection standards and respect for humanitarian obligations.
17. The Assembly expresses once more its deep concern and sorrow over the deaths at sea of migrants, refugees and asylum seekers. It calls on member States to employ AI technologies to enhance search and rescue capabilities, and to uphold the dignity of deceased individuals, in accordance with the principles laid down in its Resolution 2569 (2024) “Missing migrants, refugees and asylum seekers – A call to clarify their fate” and Resolution 2612 (2025) “Saving the lives of migrants at sea and protecting their human rights”.
18. At the arrival stage, AI can be used to support individualised, fair and rights-compliant asylum procedures, while never replacing the role of human caseworkers in interactions and decision making. AI-generated documents should be accessible in applicants’ languages and in plain language formats.
19. Biometric systems and language recognition tools should be subject to routine bias audits to ensure equitable treatment, while facial recognition tools, such as those used in smart border tunnels, should undergo demographic testing to ensure compliance with non-discrimination requirements and adhere to EU-wide audit standards.
20. AI systems in asylum processing should be verified and corrected for skewed datasets to avoid discriminatory proxies, and AI-generated evidence must be verified by humans, with access to judicial review. The use of tools such as emotion recognition or lie detectors should not be included, and predictive tools assessing the likelihood of absconding must not be used to justify detention, especially of minors. Impact assessments such as HUDERIA should be carried out prior to any roll-out of new systems.
21. During the stay period, inclusive integration policies, in accordance with Assembly Resolution 2502 (2023) “Integration of migrants and refugees: benefits for all parties involved”, can be supported by the ethical use of AI, which can play a key role in accelerating the self-reliance of migrants, refugees and asylum seekers and boosting the resilience of host communities. Tools may be co-developed with refugee communities and NGOs and made accessible offline (telephone hotlines without internet access for example) and through voice interfaces to bridge digital divides.
22. AI labour-matching tools should prioritise ethical criteria such as family unity and cultural fit. Gender-sensitive design is essential to avoid reinforcing labour market segregation that directs women into low-wage sectors. Continuous feedback loops should help address misplacements. Annual audits of AI systems used in welfare and housing are essential to detect and correct bias. Predictive analytics can support equitable urban planning, helping to prevent segregation and foster innovation and safety in diverse communities.
23. The Assembly calls for the creation of independent oversight bodies such as the EU Artificial Intelligence Board, which should include civil society and legal and technological experts and should monitor the implementation of AI-powered systems in migration, asylum and border control management based on the guidelines of the Office of the United Nations High Commissioner for Refugees (UNHCR), on the Council of Europe Framework Convention on AI and on relevant EU regulations.
24. Robust redress and compensation mechanisms must also be available to allow for the contesting of AI-generated evidence through expedited legal channels. Legal aid should be expanded to cover algorithmic disputes.
25. For circular migration and return stages, AI chatbots used in return support programmes should comply with fairness standards, avoid nudging techniques and provide unbiased information. Migrants, refugees and asylum seekers should retain control over their data, with the ability to delete or transfer information upon exiting programmes and a guarantee against the sharing of biometric information with the country of origin. The sharing of biometric data with countries of origin must be banned if there is any risk of persecution. AI-based assessments of environmental conditions may assist in determining the safety of return destinations.
26. Sustainable reintegration requires robust post-return monitoring. States should implement community-informed impact assessments and ethical AI tools to track outcomes related to employment, housing, and well-being. Offline-accessible AI assistants must support migrants to navigate reintegration services.
27. In line with its Resolution 2343 (2020) “Preventing discrimination caused by the use of artificial intelligence”, the Assembly underscores the importance of specific action to prevent discrimination and disproportionate negative impact on groups such as women, minorities and the most vulnerable and marginalised individuals, including migrants, refugees and asylum seekers.
28. Such potential discrimination in AI should be addressed at the design phase, which can usefully benefit from the participation of civil society organisations representing migrants, refugees and asylum seekers to increase trust and reliability. Awareness raising and training for asylum officers, NGOs and AI developers will strengthen ethical AI deployment.
29. Member States must safeguard against the misuse of AI for disinformation, manipulation or cyberattacks that exploit migration vulnerabilities. Geopolitical threats, including those linked to the Russian Federation’s aggression against Ukraine, demand increased vigilance and resilience in migration policy frameworks to avoid a negative impact on the protection offered.
30. As regards the general climate of opinion around migration issues, States should ensure that AI-powered chatbots are used ethically to provide accessible, accurate and multilingual migration information, and ensure that these tools are not used to manipulate narratives or asylum decisions. Here too, participatory design in chatbot development is to be favoured.
31. To support the above measures, awareness raising and capacity building among all public and private stakeholders – particularly public authorities and officials, developers, small and medium-sized enterprises and start-up AI enterprises – on the use of AI in migration management is essential, based on the relevant regulatory frameworks and practical implementation.

B. Draft recommendation 
			(2) 
			Draft recommendation
adopted by the committee on 24 June 2025.

(open)
1. Noting the rapid advancement of artificial intelligence (AI) in migration management as in other areas, the Parliamentary Assembly recommends that the Committee of Ministers encourages the signature, ratification and implementation of the Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law (CETS No. 225) by all member States and other States.
2. In light of Resolution … (2025) “Artificial intelligence and migration”, the Assembly urges the Committee of Ministers to prepare a recommendation guiding member States on the use of AI in migration management, followed by concrete actions that prioritise transparency, accountability and human rights protection.
3. The Assembly urges the Committee of Ministers to ensure that migration-related policy instruments incorporate strong and enforceable safeguards and calls for the establishment of a code of good practice on the use of AI in migration management and in procedures affecting the rights of migrants, refugees and asylum seekers, which could form part of the above recommendation.
4. The Assembly recommends that the Committee of Ministers plans – within the Council of Europe – awareness-raising programmes on the implications of AI in migration management for ombudsman institutions and equality bodies. These activities should strengthen their capacity to safeguard human rights. Similar awareness raising and training should be rolled out for migration officers, caseworkers and NGOs; the Council of Europe HELP programme (Human Rights Education for Legal Professionals) and the EU Digital Europe Programme may be useful instruments in this respect.
5. The Assembly recommends strengthening co-operation with all the relevant bodies and agencies of the European Union and the United Nations on the application of AI in migration management. It emphasises also the importance of co-operation between the Council of Europe and civil society on this question, which would be particularly valuable in the design of any forthcoming instruments.

C. Explanatory memorandum by Mr Petri Honkonen, rapporteur

(open)

1. Introduction

1. The deployment of advanced information technologies – particularly artificial intelligence (AI) – in identity checks, border controls, visa processing and asylum applications is transforming migration management across Europe. These systems increasingly rely on vast datasets, often involving information collected from specific groups or countries, with decision-making processes shaped by algorithmic models. While AI has the potential to streamline administrative procedures, its application in the sensitive and high-risk area of migration raises serious concerns regarding transparency, accountability and fundamental rights. The possibility of biased algorithms, designed to prioritise certain data over others, underscores the need for robust scrutiny and safeguards.
2. AI presents an opportunity to modernise migration management and improve efficiency. However, any technological advancement must be accompanied by a firm commitment to human rights and the rule of law. Systems that pose a high risk of human rights violations – such as AI-enabled social scoring, discriminatory profiling or the generation of illegal or harmful content – should be explicitly prohibited. Migration governance must ensure that such tools do not exacerbate existing inequalities or undermine individual rights.
3. Recognising the urgency and complexity of these issues, the Parliamentary Assembly has taken a proactive stance. On 29 May 2024, the Committee on Migration, Refugees and Displaced Persons appointed me as rapporteur following the reference to the committee of a motion for a resolution “Artificial intelligence and migration” (Doc. 15952). The preparation of this report involved comprehensive consultations with academic experts, civil society representatives and officials from international organisations. 
			(3) 
			On 3 October 2024, in Strasbourg, a joint meeting
of the Sub-Committee on Refugee and Migrant Children and Young People
and the Sub-Committee on Artificial Intelligence and Human Rights
was held to discuss “Artificial intelligence and migration.” The
exchange of views included contributions from Mr Kristian Bartholin,
Head of the Digital Development Unit and Secretary of the Committee
on Artificial Intelligence (CAI) of the Council of Europe; Ms Mariam Tartousy,
Representative of the Advisory Council on Youth (CCJ), Council of
Europe (online); Ms Niovi Vavoula, Associate Professor in Cyber
Policy at the University of Luxembourg; Ms Ludivine Stewart, PhD
Researcher in the Law Department at the European University Institute;
and Dr William Jones, Associate Professor at Royal Holloway, University
of London. On 17 October 2024, during
a meeting of the committee in Ljubljana, an exchange of views was
held with Dr Aleksander Pur, an AI and security expert from the
Republic of Slovenia, and Ms Petra Molnar, Associate Director of
the Refugee Law Lab at York University and Faculty Associate at
the Berkman Klein Centre for Internet & Society at Harvard University (online).
On 27 November 2024, at the “AI and Human Rights” seminar held at
the Parliament of Finland in Helsinki, I gave a presentation on
“AI and migration” and chaired a panel focused on the use of artificial
intelligence in immigration processes. The discussion underlined
the need for vigilance and strong legal safeguards to prevent misuse
of high-risk AI systems such as social scoring. On 29 January 2025,
the committee held an exchange of views with Mr Philippe Harant, Head
of the Strategy, Capabilities and Coordination Unit at eu-LISA,
who provided an overview of the agency’s history and mission, highlighting
its role in the operational management of major European IT systems
from its headquarters in Tallinn, Estonia. On 25 February 2025,
I held an online meeting with Mr Huanzhang Fu, Assistant Director
of the Strategic Innovation Programme, and Ms Julie Tomaszewski,
Innovation and Technology Officer at the Innovation Centre of INTERPOL
Global Complex for Innovation in Singapore. On 11 March 2025, in
Paris, the committee met with Ms Frida Alizadeh Westerling, PhD
candidate in Asylum Law and Technology at the University of Helsinki
and contributor to the Trust-M research project, and Ms Emilie Wiinblad
Mathez, Senior Protection Coordinator with the Division of International Protection
at UNHCR. On 6 May 2025, I conducted a fact-finding visit to Frontex,
during which I met with Jonas Grimheden, Fundamental Rights Officer;
Grigoris Tsioukas, Deputy FRO; Luana Scarcella, Fundamental Rights
Monitor and Team Leader FRO.GEO 2; Anita Danka, Fundamental Rights
Monitor and Team Leader FRO.HORIZON; and Aleksandra Klosinska and
Mara Bottone, Fundamental Rights Monitors with FRO.HORIZON and FRO.Ge
respectively. I also met with Mr Denis Destrebecq, Acting Head of
the Research and Technology Sector; Ms Olga Verboncu, Senior Officer
in the same sector; and Mr Stavros Panagiotidis, Deputy Contact
Point on the AI Act at the EBCG Academy. Meetings were also held
with representatives of the ETIAS Central Unit, including Ms Panagiota
Karadimitriou, Deputy Head of the Assistance Centre Unit; Mr Spyridon
Argyros, Head of the Data Management Office; Mr Ignacio Zozaya,
Head of the Business Management Office; Ms Antonia Budeanu, Compliance
Officer; and Ms Anna Nehring, Risk Screening Officer. In addition,
I discussed relevant issues with Mr Alexandr Fuchs, Head of the
Eurosur Fusion Service Sector at EUROSUR, and Mr Zsolt Bartfai,
Deputy Data Protection Officer. I also met with Ms Maria Janyska,
Chair of the Committee on Administrative and Internal Affairs, and
Mr Łukasz Osmalak, Member of the Committee on Digitalisation, Innovation
and Technology of the Polish Sejm, as well as Polish experts on
artificial intelligence and migration, who shared their national
perspectives on the key issues addressed in this report. I wish
to thank all contributors and members of the committee for their
valuable input and engagement throughout this process. This is the first Assembly report on this issue.
4. The term “artificial intelligence”, refers to “systems that display intelligent behaviour by analysing their environment and taking actions – with some degree of autonomy to achieve specific goals”. 
			(4) 
			European
Commission: Deloitte and Directorate-General for Migration and Home
Affairs, Opportunities and challenges
for the use of artificial intelligence in border control, migration
and security. Volume 1, Main report, Publications Office,
2020, <a href='https://op.europa.eu/en/publication-detail/-/publication/c8823cd1-a152-11ea-9d2d-01aa75ed71a1/language-en'>https://op.europa.eu/en/publication-detail/-/publication/c8823cd1-a152-11ea-9d2d-01aa75ed71a1/language-en</a>. Thus, we can think of AI as any system capable of performing tasks that we would usually consider to be intelligent human behaviour. AI applications today typically involve recognising patterns, making inferences, making case-by-case decisions and engaging in conversation. The amount of data available for AI models to learn from is greater than ever before and continues to grow substantively. At the same time, increasing democratisation of algorithms and platforms has created an ecosystem in which AI solutions can be tested and implemented more easily, by a wider range of people and organisations. 
			(5) 
			Ibid.
5. In recent years, governments have been implementing AI regulations, particularly through international organisations, to avoid human rights violations while maintaining an environment conducive to innovation. The Council of Europe has adopted the legally binding Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law (CETS No. 225, hereinafter “Framework Convention on AI”). 
			(6) 
			<a href='https://www.coe.int/en/web/artificial-intelligence/the-framework-convention-on-artificial-intelligence'>The
Framework Convention on Artificial Intelligence – Artificial Intelligence
(coe.int)</a>. New European Union (EU) legislation in this area, including the recently adopted Digital Services Act and Artificial Intelligence Act (hereinafter the “EU AI Act”), will also affect how AI is used in migration management. 
			(7) 
			Regulation (EU) 2024/1689
of the European Parliament and of the Council of 13 June 2024 laying
down harmonised rules on artificial intelligence. See also the <a href='https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence'>EU
AI Act: first regulation on artificial intelligence | Topics | European Parliament
(europa.eu)</a>. We should also consider the United Nations Educational, Scientific and Cultural Organization (UNESCO) Recommendation on the Ethics of Artificial Intelligence, 
			(8) 
			<a href='https://unesdoc.unesco.org/ark:/48223/pf0000381137'>Recommendation
on the Ethics of Artificial Intelligence – UNESCO Digital Library</a>. as well as the Organisation for Economic Co-operation and Development (OECD) AI Principles. 
			(9) 
			<a href='https://www.oecd.org/en/topics/sub-issues/ai-principles.html'>AI
principles | OECD</a>.
6. In my country, Finland, the impact of AI on human rights in general and on the rights of migrants, refugees and asylum seekers in particular was discussed recently at a seminar held in Helsinki on 27 November 2024. Finland’s Minister for Foreign Affairs, Elina Valtonen, underlined the importance of the Council of Europe Framework Convention on AI as a milestone for responsible AI governance and for reinforcing the protection of individual rights in the digital age. She emphasised that clear regulations on AI would foster innovation, asserting that “ethical artificial intelligence is not an obstacle to development but a foundation for sustainable and long-term innovation”. The seminar, initiated by Ms Miapetra Kumpula-Natri, Head of the Finnish Delegation to the Assembly, provided a platform for discussions among experts and parliamentarians on the impact of AI on human rights, democracy and the rule of law. Mr Tarmo Jukarainen from the Finnish Immigration Service (FIS) presented ongoing efforts to automate immigration procedures in Finland, noting that AI will be introduced gradually following thorough risk assessments. The event also highlighted the critical role of education in equipping future generations with the necessary skills to design and use AI responsibly.
7. In the field of migration management, the scope of artificial intelligence application is quite broad. AI systems are used for document authentication, language processing (such as speech-to-text transcription or machine translation), speech recognition, dialect identification, image recognition, advanced analytics and deep learning, process automation, information provision through chatbots, country-of-origin information research, forecasting of migration and asylum trends, and facilitating health services for migrants, refugees and asylum seekers through telemedicine.
8. Given that migration into Europe is largely impacted by the EU legislation, this report takes into account the current developments in the EU. The EU AI Act states that “AI systems used in migration, asylum and border control management affect persons who are often in [a] particularly vulnerable position and who are dependent on the outcome of the actions of the competent public authorities. The accuracy, non-discriminatory nature and transparency of the AI systems used in those contexts are therefore particularly important to guarantee respect for the fundamental rights of the affected persons, in particular their rights to free movement, non-discrimination, protection of private life and personal data, international protection and good administration”.
9. According to the EU AI Act, it is “appropriate to classify as high-risk, insofar as their use is permitted under relevant Union and national law, AI systems intended to be used by or on behalf of competent public authorities or by Union institutions, bodies, offices or agencies charged with tasks in the fields of migration, asylum and border control management”. 
			(10) 
			OJ L, 2024/1689, 12.7.2024,
ELI: <a href='http://data.europa.eu/eli/reg/2024/1689/oj 17/144'>http://data.europa.eu/eli/reg/2024/1689/oj</a>; Migration is one of the high-risk AI systems referred
to in Article 6(2) of the EU AI Act (see Annex III to the EU AI
Act). Another area covered in that article includes “biometrics.
10. Furthermore, “the use of AI systems in migration, asylum and border control management should, in no circumstances, be used by member States or Union institutions, bodies, offices or agencies as a means to circumvent their international obligations under the UN Convention relating to the Status of Refugees done at Geneva on 28 July 1951 as amended by the Protocol of 31 January 1967. Nor should they be used to in any way infringe on the principle of non-refoulement, or to deny safe and effective legal avenues into the territory of the Union, including the right to international protection”. 
			(11) 
			Ibid.
11. Finally, the “high-risk AI systems should be designed and developed in such a way that natural persons can oversee their functioning, ensure that they are used as intended and that their impacts are addressed over the system’s life cycle. To that end, appropriate human oversight measures should be identified by the provider of the system before its placing on the market or putting into service. In particular, where appropriate, such measures should guarantee that the system is subject to in-built operational constraints that cannot be overridden by the system itself and is responsive to the human operator, and that the natural persons to whom human oversight has been assigned have the necessary competence, training and authority to carry out that role”. 
			(12) 
			EU
AI Act, para. 71.

2. Risks associated with the use of artificial intelligence in migration management

12. The rapid deployment of artificial intelligence in migration management presents significant risks to human rights and fundamental freedoms. The lack of transparency, complexity of algorithms and limited public understanding – especially among vulnerable migrant populations – undermine the ability to question or appeal against AI-driven decisions. This opacity demands robust accountability mechanisms.
13. According to the EU Agency for Fundamental Rights, the use of AI can impact key rights such as human dignity, non-discrimination, access to justice and good administration. Effective safeguards and accessible redress mechanisms must be established to ensure those adversely affected by AI decisions can appeal and know who bears responsibility. 
			(13) 
			Getting the future right – Artificial Intelligence
and fundamental rights. FRA, 2020; <a href='https://fra.europa.eu/en/publication/2020/artificial-intelligence-and-fundamental-rights'>https://fra.europa.eu/en/publication/2020/artificial-intelligence-and-fundamental-rights</a>.
14. Before deploying AI in asylum procedures, States should conduct human rights, democracy and rule of law impact assessments, using tools such as the Council of Europe HUDERIA methodology to address risks like biases, privacy breaches and discrimination. 
			(14) 
			Petra Molnar and Lex
Gill. “Bots at the Gate: A Human Rights Analysis of Automated Decision-Making
in Canada’s Immigration and Refugee System,” Citizen Lab and International
Human Rights Program (Faculty of Law, University of Toronto) Research
Report No. 114, University of Toronto, September 2018, <a href='https://citizenlab.ca/2018/09/bots-at-the-gate-human-rights-analysis-automated-decision-making-in-canadas-immigration-refugee-system/'>https://citizenlab.ca/2018/09/bots-at-the-gate-human-rights-analysis-automated-decision-making-in-canadas-immigration-refugee-system/</a>; and <a href='https://www.coe.int/en/web/artificial-intelligence/cai'>www.coe.int/en/web/artificial-intelligence/cai</a>. The EU AI Act also requires public bodies and private service providers to assess fundamental rights impacts before using high-risk AI systems, though current enforcement remains limited. 
			(15) 
			“For
that purpose, deployers shall perform an assessment consisting of:
(a) a description of the deployer’s processes in which the high-risk
AI system will be used in line with its intended purpose; (b) a
description of the period of time within which, and the frequency
with which, each high-risk AI system is intended to be used; (c)
the categories of natural persons and groups likely to be affected
by its use in the specific context; (d) the specific risks of harm
likely to have an impact on the categories of natural persons or
groups of persons identified pursuant to point (c) of this paragraph,
taking into account the information given by the provider pursuant
to Article 13; (e) a description of the implementation of human
oversight measures, according to the instructions for use; (f) the
measures to be taken in the case of the materialisation of those risks,
including the arrangements for internal governance and complaint
mechanisms”. OJ L, 2024/1689, 12.7.2024, ELI: <a href='http://data.europa.eu/eli/reg/2024/1689/oj 17/144'>http://data.europa.eu/eli/reg/2024/1689/oj</a>. Human rights risks, particularly concerning privacy and discrimination, remain insufficiently addressed at this stage.
15. Given the importance of evaluating AI technologies, equality bodies must be empowered – under Article 77 of the EU AI Act – with resources to detect bias and monitor the misuse or repurposing of data in migration management, which could negatively impact asylum claims. 
			(16) 
			This was
underscored on 11 March 2025 by Ms. Frida Alizadeh Westerling before
the committee.
16. The Council of Europe working group on Artificial Intelligence (CDDH-IA) warns that AI can result in direct and intersectional discrimination, particularly in biometric technologies like facial recognition. Such systems often operate as “black boxes” due to trade secret protections, obscuring their errors and undermining accountability. Professor A. Beduschi cautions that blind reliance on AI could lead to severe human rights violations, such as misidentification, wrongful detention or refoulement to countries where individuals risk ill-treatment. 
			(17) 
			Beduschi, A., International migration management in the age
of artificial intelligence in Migration Studies, Volume
9, Issue 3, September 2021, Pages 576–596, <a href='https://academic.oup.com/migration/article/9/3/576/5732839'>https://academic.oup.com/migration/article/9/3/576/5732839</a>.
17. Because of their algorithms, AI technologies are not 100% reliable. Examples include the EU-funded iBorder Control project, which uses biometric and behavioural analysis and is prone to false assessments, and Germany’s TraLitA transliteration software, which struggles with non-Levantine Arabic dialects – potentially disadvantaging applicants. 
			(18) 
			McGregor,
L. and Molnar, P. (2023), “Digital Border Governance: A Human Rights
Based Approach”, Report for the UN Office of High Commissioner for
Human Rights and University of Essex, <a href='https://www.ohchr.org/en/documents/tools-and-resources/digital-border-governance-human-rights-based-approach'>www.ohchr.org/en/documents/tools-and-resources/digital-border-governance-human-rights-based-approach</a>. These cases illustrate the danger of algorithmic modelling errors and data bias. 
			(19) 
			Report of the Special
Rapporteur on contemporary forms of racism, racial discrimination,
xenophobia and related intolerance, (10 November 2020), UN doc A/75/590, <a href='https://www.ohchr.org/en/special-procedures/sr-racism/annual-thematic-reports'>www.ohchr.org/en/special-procedures/sr-racism/annual-thematic-reports</a>.
18. Moreover, AI systems may unintentionally reveal protected characteristics through analysis of speech, facial features, or digital data, increasing the risk of discriminatory profiling. Such misuse can result in the denial of entry or visa applications, potentially infringing on the right to freedom of movement under Article 2 of Protocol No. 4 to the European Convention on Human Rights, which must be restricted only for legitimate aims and in proportion to public interest. 
			(20) 
			De Tommaso v. Italy [GC], No. 43395/09,
23 February 2017, § 104; Pagerie v. France,
No. 24203/16, 12 January 2023, § 171; Battista
v. Italy, No. 43978/09, 2 December 2014, § 37; Khlyustov v. Russia, No. 28975/05,
11 July 2013, § 64; Labita v. Italy [GC],
No. 26772/95, 6 April 2000, §§ 194-195.
19. The digital divide remains a major concern, as many migrants, refugees and asylum seekers lack the educational resources to understand or navigate AI systems. Without careful design, AI could reinforce rather than resolve systemic inequalities. To counterbalance both AI and human bias, front line officers must receive specialised training and both the development and deployment of AI must be subject to rigorous oversight.
20. Finally, the pace of technological advancement, combined with increasing reliance on digital tools, introduces new vulnerabilities that can be exploited by hybrid actors. As highlighted in the FRONTEX “Strategic Risk 2024 Analysis Report”, while technologies such as Entry-Exit System (EES) and European Travel Information and Authorisation System (ETIAS) have strengthened European integrated border management, they have also exposed critical infrastructure to cyberattacks and hybrid threats.
21. The reliance on complex, opaque and often unregulated supply chains further exacerbates these risks. Additionally, new technologies – including drones and mapping apps – are enabling novel methods of migration facilitation. In a hyperconnected digital environment, the spread of disinformation via social media undermines public trust, influences democratic processes and amplifies the societal impact of migration, making it increasingly difficult to distinguish factual information from manipulated narratives. 
			(21) 
			<a href='https://www.frontex.europa.eu/assets/Publications/Risk_Analysis/Risk_Analysis/Strategic_Risk_Analysis_2024_Report.pdf'>www.frontex.europa.eu/assets/Publications/Risk_Analysis/Risk_Analysis/Strategic_Risk_Analysis_2024_Report.pdf</a>. FRONTEX warns against situations, when technology is employed to dissociate people smugglers from their clients physically – thus allowing smugglers to operate outside the jurisdiction of EU law enforcement – and in terms of information technology (e.g. encryption). 
			(22) 
			<a href='https://www.frontex.europa.eu/assets/Publications/Risk_Analysis/Risk_Analysis/Strategic_Risk_Analysis_2024_Report.pdf'>Ibid.</a>

3. Opportunities for migration management created by artificial intelligence

22. The International Organization for Migration (IOM) notes that the migration experience is usually divided into the following stages: pre-departure, transit, arrival, stay, circular migration and return, and sustainable integration and reintegration. 
			(23) 
			<a href='https://emm.iom.int/handbooks/global-context-international-migration/phases-migration-0'>https://emm.iom.int/handbooks/global-context-international-migration/phases-migration-0#:~:text=The%20phases%20begin%20with%20pre,and%20sustainable%20(re)integration</a>. The United Nations High Commissioner for Refugees (UNHCR) promotes a holistic, route-based approach to managing mixed movements of migrants, refugees and asylum seekers, centred on three key aims: saving lives and reducing harm; providing early protection and solutions to deter dangerous journeys; and supporting States in managing these movements lawfully. 
			(24) 
			A <a href='https://www.unhcr.org/sites/default/files/2024-10/explainer_unhcr_route_based_approach.pdf'>route-based
approach</a>. These actions are grounded in the 1951 Refugee Convention and its 1967 Protocol (“Refugee Convention”), which enshrine the principle of international protection. Human rights instruments affirm the obligation to treat all individuals, including migrants, refugees and asylum seekers, with dignity and to safeguard their rights. 
			(25) 
			This
was underlined by Ms Emilie Wiinblad Mathez (UNHCR) during an exchange
of views with the committee on 11 March 2025 in Paris. Further commitments by States are reflected in the Global Compact on Refugees and the Global Compact for Safe, Orderly and Regular Migration. 
			(26) 
			<a href='https://globalcompactrefugees.org/sites/default/files/2019-12/Global compact on refugees EN.pdf'>Global
Compact on Refugees</a>, and <a href='https://www.un.org/en/development/desa/population/migration/generalassembly/docs/globalcompact/A_RES_73_195.pdf'>Global
Compact for Safe, Orderly and Regular Migration</a>.
23. Drawing on the Council of Europe Framework Convention on AI, the EU AI Act, and the policy frameworks of the UNHCR, IOM and OECD, the Assembly can make specific recommendations to ensure that the deployment of AI in the field of migration aligns with human rights standards, ethics, transparency and accountability. From pre-departure screening to sustainable reintegration, member States must prioritise safeguards against bias, ensure human oversight and uphold the dignity of migrants, refugees and asylum seekers.

3.1. Pre-departure stage

24. Before international migration occurs, individuals must often navigate complex administrative, legal and logistical steps. The actions taken in the pre-departure stage vary greatly – ranging from long-term preparation to sudden displacement – and presents opportunities for AI to support rights-based migration management.
25. To uphold human rights at this stage, AI should be deployed only after rigorous impact assessments. Transparent visa and asylum pre-screening procedures must be prioritised, and tools like the EU ETIAS system should include safeguards such as mandatory manual reviews for AI-generated high-risk alerts. AI-powered chatbots used for pre-departure guidance, such as those tested in OECD countries, must disclose their limitations to prevent misinformation.
26. AI also offers potential to facilitate legal labour migration, through systems that support advance work and residence permits. Tools like SkillLab’s SkillMap help identify exploitative recruitment practices by analysing employer data and job postings. 
			(27) 
			<a href='https://hias.org/news/trying-to-help-refugees-into-the-workplace-now-theres-an-app-for-that/'>https://hias.org/news/trying-to-help-refugees-into-the-workplace-now-theres-an-app-for-that/</a>; 
			(27) 
			<a href='C:\Users\garabagiu\ND Office Echo\DE-7TO1X6K0\www.weforum.org\stories\2023\01\ai-in-migration-is-fuelling-global-inequality-how-can-we-bridge-gap\'>www.weforum.org/stories/2023/01/ai-in-migration-is-fuelling-global-inequality-how-can-we-bridge-gap/</a>. The EU’s Initiative 1 on AI in visa applications aims to improve efficiency and internal Schengen security through automated background checks.
27. In line with the Assembly Resolution 2401 (2021) “Climate and migration”, AI can also be used for ethical climate migration forecasting, integrating climate and socio-economic data to predict displacement patterns and guide humanitarian responses – not restrictive border policies. 
			(28) 
			Resolution 2401 (2021) “Climate and migration”.
28. AI plays a role in combating smuggling networks, through tools that analyse dark web activity and financial flows, such as in the EU PROMENADE project, which monitors vessel movements using machine learning. However, these technologies must comply with human rights safeguards under the Council of Europe HUDERIA methodology to avoid overreach. 
			(29) 
			<a href='https://home-affairs.ec.europa.eu/news/eu-backed-projects-contribute-countering-migrant-smuggling-ai-2024-12-18_en'>https://home-affairs.ec.europa.eu/news/eu-backed-projects-contribute-countering-migrant-smuggling-ai-2024-12-18_en</a>; <a href='https://www.coe.int/en/web/artificial-intelligence/cai'>www.coe.int/en/web/artificial-intelligence/cai</a>.
29. Visa eligibility screening tools, including those like OpenSphere.ai, must undergo regular bias audits and offer transparency in decision making to allow for contestation. Throughout, data protection and non-discrimination must remain guiding principles, particularly when using AI to analyse biometric data or behavioural patterns. 
			(30) 
			<a href='https://opensphere.ai/immigration-resources/ai-powered-visa-eligibility-checkers-streamlining-immigration-processes'>https://opensphere.ai/immigration-resources/ai-powered-visa-eligibility-checkers-streamlining-immigration-processes</a>; 
			(30) 
			<a href='https://www.statewatch.org/news/2025/january/eu-human-rights-must-be-central-guiding-basis-for-new-ai-guidelines/'>www.statewatch.org/news/2025/january/eu-human-rights-must-be-central-guiding-basis-for-new-ai-guidelines </a> 
			(30) 
			<a href='https://opensphere.ai/'>OpenSphere – AI-Powered Immigration
Assistance.</a>
30. AI-powered chatbots are increasingly used across Europe for multilingual support in visa applications, appointment scheduling and legal advice. Examples include Visabot in the United States, Kamu in Finland and AsyLex in Switzerland, which promote access to justice for asylum seekers. Countries like Türkiye and the United Kingdom have implemented online e-visa systems where AI performs an initial screening, distinguishing between standard and at-risk applications. The flagged at-risk cases are then referred to immigration officers for further review. 
			(31) 
			European
Migration Network (2022). “The use of digitalisation and artificial
intelligence in migration management”: Joint EMN-OECD Inform. European
Commission, <a href='https://emn.ie/publications/the-use-of-digitalisation-and-artificial-intelligence-in-migration-management/'>https://emn.ie/publications/the-use-of-digitalisation-and-artificial-intelligence-in-migration-management/</a>. The AI tools help reduce administrative burdens and support marginalised groups, provided they are implemented with ethical safeguards and offline accessibility.
31. Chatbots are also used to combat disinformation and smuggling. Tools like ACME employ computational argumentation to debunk migration myths, while predictive analytics assist migrants, refugees and asylum seekers with skills training and destination planning. Yet, public authorities must do more to counter false narratives and misuse of AI, ensuring that innovation enhances – not undermines – migrant protection and human dignity, as underscored in the EU “Ethics guidelines for trustworthy AI” and the “Principles for the Ethical Use of Artificial Intelligence in the United Nations System”. 
			(32) 
			<a href='https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai'>Ethics
guidelines for trustworthy AI | Shaping Europe’s digital future</a> and <a href='https://unsceb.org/sites/default/files/2022-09/Principles for the Ethical Use of AI in the UN System_1.pdf'>Principles
for the Ethical Use of artificial intelligence in the UN System</a>.

3.2. Transit stage

32. The transit stage of migration is often complex and prolonged, with individuals facing multiple displacements, delays due to conflict, tightened border controls, or lack of resources. Some migrants become stranded – unable to return home, regularise their status, or legally move forward.
33. During the transit stage, AI tools must be used cautiously and in line with human rights. 
			(33) 
			<a href='C:\Users\garabagiu\ND Office Echo\DE-7TO1X6K0\www.consilium.europa.eu\en\policies\artificial-intelligence\'>www.consilium.europa.eu/en/policies/artificial-intelligence/</a>; 
			(33) 
			<a href='https://www.europarl.europa.eu/RegData/etudes/IDAN/2021/690706/EPRS_IDA(2021)690706_EN.pdf'>www.europarl.europa.eu/RegData/etudes/IDAN/2021/690706/EPRS_IDA(2021)690706_EN.pdf</a>. States should avoid deploying emotion recognition and predictive policing technologies unless strictly necessary for national security and must prohibit systems that restrict freedom of movement through speculative analytics. Tools like iSentry should be limited to detecting verifiable threats such as smuggling, and not for generalised behavioural profiling. 
			(34) 
			Idem; <a href='https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4953245'>https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4953245</a>.
34. Cross-border data sharing should be secure and rights-based. Systems such as EUROSUR must encrypt biometric data and limit access to authorised entities. The IOM 2023 Data Protection Principles offer a framework for anonymised, secure migration flow data sharing. 
			(35) 
			<a href='https://publications.iom.int/system/files/pdf/pub2024-033-l-return-reintegration-2023-highlights_1.pdf'>https://publications.iom.int/system/files/pdf/pub2024-033-l-return-reintegration-2023-highlights_1.pdf</a>; 
			(35) 
			<a href='https://www.oecd.org/migration/mig/EMN-OECD-INFORM-FEB-2022-The-use-of-Digitalisation-and-AI-in-Migration-Management.pdf'>www.oecd.org/migration/mig/EMN-OECD-INFORM-FEB-2022-The-use-of-Digitalisation-and-AI-in-Migration-Management.pdf</a>.
35. The use of surveillance technologies in transit zones must be carefully regulated. AI-driven mass surveillance, such as facial recognition and drone monitoring – used along locations like the Calais coast – often infringes on privacy and deters asylum seekers. 
			(36) 
			<a href='https://inkstickmedia.com/for-migrants-artificial-intelligence-becomes-a-roadblock-to-europe/'>https://inkstickmedia.com/for-migrants-artificial-intelligence-becomes-a-roadblock-to-europe/</a>. Under the Council of Europe Framework Convention on AI, biometric categorisation is prohibited in migration contexts unless strictly necessary and proportionate. 
			(37) 
			<a href='https://www.coe.int/en/web/artificial-intelligence/work-in-progress'>www.coe.int/en/web/artificial-intelligence/work-in-progress</a>; 
			(37) 
			<a href='https://edoc.coe.int/en/artificial-intelligence/11926-council-of-europe-framework-convention-on-artificial-intelligence-and-human-rights-democracy-and-the-rule-of-law.html'>https://edoc.coe.int/en/artificial-intelligence/11926-council-of-europe-framework-convention-on-artificial-intelligence-and-human-rights-democracy-and-the-rule-of-law.html</a>.
36. Speaking in Ljubljana on 17 October 2024, Ms Petra Molnar highlighted that refugee spaces often serve as testing grounds for emerging technologies in loosely regulated environments. She criticised the ecosystem of fear that criminalises migration and legitimises pushbacks, often exacerbated by the deployment of AI-powered surveillance and automated decision-making tools.
37. AI can also support humanitarian efforts during transit. For example, AI systems can help design safe humanitarian corridors by analysing real-time conflict data. The UNHCR “Digital Transformation Strategy” stresses the importance of consent and data minimisation when deploying such tools. 
			(38) 
			<a href='https://www.un.org/digital-emerging-technologies/sites/www.un.org.techenvoy/files/GDC-submission_UNHCR.pdf'>www.un.org/digital-emerging-technologies/sites/www.un.org.techenvoy/files/GDC-submission_UNHCR.pdf</a>; 
			(38) 
			<a href='https://ai4good.org/eureka/'>https://ai4good.org/eureka/</a>. However, misuse has occurred – such as drones being employed not to assist rescue operations but to return migrants, refugees and asylum seekers to countries where they risk grave human rights violations, as noted by the UN Working Group on the use of mercenaries. 
			(39) 
			McGregor, L. and Molnar,
P. (2023), Digital Border Governance:
A Human Rights Based Approach, Report for the UN Office
of High Commissioner for Human Rights and University of Essex, <a href='https://www.ohchr.org/en/documents/tools-and-resources/digital-border-governance-human-rights-based-approach'>www.ohchr.org/en/documents/tools-and-resources/digital-border-governance-human-rights-based-approach</a>.
38. Innovative tools like the Aurora chatbot provide migrants with real-time updates on safe routes, border procedures and humanitarian aid, bridging literacy gaps through multimedia formats. 
			(40) 
			<a href='https://www.migrationdataportal.org/did-profile/aurora-chatbot-empowering-transit-migrants-reliable-information-and-humanitarian-aid'>www.migrationdataportal.org/did-profile/aurora-chatbot-empowering-transit-migrants-reliable-information-and-humanitarian-aid</a>; 
			(40) 
			<a href='http://www.data4sdgs.org/festivaldedatos/use-chatbots-improve-humanitarian-response'>www.data4sdgs.org/festivaldedatos/use-chatbots-improve-humanitarian-response</a>. In Latin America, it serves over 1 000 users monthly in countries including Colombia and Panama. Emergency and health-focused AI applications also support migrants in transit. The Karim chatbot offers mental health support using cognitive-behavioural therapy in native languages, while Mexico’s panic button app enables AI-triggered consular interventions for detained migrants via geolocation alerts. 
			(41) 
			<a href='https://qudata.com/en/ai-ml-case-studies/an-ai-driven-chatbot-for-refugees-helplines/'>https://qudata.com/en/ai-ml-case-studies/an-ai-driven-chatbot-for-refugees-helplines/</a>.

3.3. Arrival stage

39. Those travelling through official migration channels are typically subject to inspection at border control points. A valid visa, where required, does not guarantee entry. Border authorities retain the discretion to refuse admission, particularly if they suspect visa fraud, identify national security or public health concerns, or assess that circumstances have changed since the visa was issued. Migrants, refugees and asylum seekers attempting irregular entry are subject to admissibility procedures and those apprehended post-entry may face voluntary return or formal removal. Cases involving asylum seekers and minors are especially sensitive, requiring more nuanced assessments due to the heightened risk of human rights violations upon return.
40. At the arrival stage, the deployment of AI must prioritise human-centric asylum processing. 
			(42) 
			<a href='C:\Users\garabagiu\ND Office Echo\DE-7TO1X6K0\www.ein.org.uk\news\home-office-expand-ai-use-asylum-decision-making-after-promising-pilot-results'>www.ein.org.uk/news/home-office-expand-ai-use-asylum-decision-making-after-promising-pilot-results</a>; 
			(42) 
			<a href='C:\Users\garabagiu\ND Office Echo\DE-7TO1X6K0\www.un.org\digital-emerging-technologies\sites\www.un.org.techenvoy\files\GDC-submission_UNHCR.pdf'>www.un.org/digital-emerging-technologies/sites/www.un.org.techenvoy/files/GDC-submission_UNHCR.pdf</a>. Automated decision making should be restricted and decisions must remain under the responsibility of human officials. While AI can support administrative functions, such as summarising asylum interviews, final determinations must not be delegated to algorithms. The Council of Europe Framework Convention on AI mandates the inclusion of judicial review mechanisms for applicants to challenge AI-generated evidence, including language analysis or credibility assessments. 
			(43) 
			<a href='https://worldmigrationreport.iom.int/sites/g/files/tmzbdl1691/files/documents/Ch11-key-findings_final.pdf'>https://worldmigrationreport.iom.int/sites/g/files/tmzbdl1691/files/documents/Ch11-key-findings_final.pdf</a>; 
			(43) 
			<a href='https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4953245'>https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4953245</a>. The EU Agency for Asylum (EUAA) has developed a tool known as LADO (Language Assessment for Determination of Origin), which applies AI to assess dialects and accents. Such tools, however, must be interpreted with care and subject to human oversight.
41. The increasing centrality of AI in border management across Europe was discussed during the exchange of views of the Committee on Migration, Refugees and Displaced Persons with Mr Philippe Harant on 29 January 2025, who outlined eu-LISA’s efforts in system development, training and innovation. eu-LISA currently manages key components of the EU justice and home affairs digital infrastructure, including the Schengen Information System (SIS), the Visa Information System (VIS), Eurodac and the soon-to-be-deployed EES and ETIAS.
42. According to the eu-LISA report “Enabling Seamless Travel to the European Union”, travel has undergone a profound transformation over the past two decades, with international traveller numbers nearly doubling. In response, AI and related technologies are being applied to enhance both facilitation and security. The digitalisation of the Schengen visa process and the expansion of automated border controls are expected to streamline procedures while reinforcing security protocols. 
			(44) 
			“Enabling
Seamless Travel to the European Union Research Monitoring Report”,
December 2022, eu-LISA.
43. Pre-border screening is a growing priority. With EES and ETIAS integration, international passenger carriers will be granted access to EU security systems, enabling them to verify travellers’ entry rights prior to arrival. This includes the use of AI-powered ETIAS virtual assistants that guide applicants through the online authorisation process, auto fill application forms, validate data and provide multilingual support. Other innovations – such as digital travel credentials and automated border gates for biometric passport holders – aim to reduce delays and enhance efficiency, particularly for air travel. Nonetheless, similar applications for rail, road and maritime transport remain underdeveloped.
44. The European Commission is also piloting AI-driven solutions for asylum administration, including ASYLUM-14, an intelligent search engine to support asylum procedures. 
			(45) 
			Opportunities
and challenges for the use of artificial intelligence in border
control, migration and security, op. cit.
45. To ensure equity and accountability, biometric technologies such as facial recognition must undergo regular bias audits, testing for accuracy across skin tones and genders. As demonstrated by Dubai’s Smart Tunnel, quarterly assessments are vital. 
			(46) 
			<a href='https://www.vfsglobal.com/en/individuals/insights/enhancing-border-management-systems-using-artificial-intelligence.html'>www.vfsglobal.com/en/individuals/insights/enhancing-border-management-systems-using-artificial-intelligence.html</a>; 
			(46) 
			<a href='https://imagevision.ai/blog/securing-borders-integrating-vision-ai-in-transportation-surveillance/'>https://imagevision.ai/blog/securing-borders-integrating-vision-ai-in-transportation-surveillance/</a>. The proposed EU Artificial Intelligence Board should co-ordinate and standardise such testing protocols to meet anti-discrimination standards. Future border technologies will likely involve a combination of AI, blockchain and digital document verification, necessitating strong regulatory oversight.
46. AI is used in a range of asylum procedure functions, including speech-to-text transcription, machine translation, document authentication, dialect identification, information provision via chatbots, country-of-origin research and asylum trend forecasting. During the meeting of the committee on 3 October 2024, Ms Ludivine Stewart noted that national authorities rely on AI to reduce administrative burdens and improve decision reliability. For example, Germany uses dialect recognition tools to determine the person’s country of origin. However, emotion recognition, often used to detect deception, is highly unreliable due to cultural variability in emotional expression and should not be employed.
47. To uphold procedural transparency, those affected by AI-based decisions must understand the technology and have effective avenues for redress. Tools trialled by the United Kingdom Home Office, such as the ACS and APS systems, have demonstrated improved efficiency but risk entrenching bias. 
			(47) 
			<a href='https://www.ein.org.uk/news/home-office-expand-ai-use-asylum-decision-making-after-promising-pilot-results'>www.ein.org.uk/news/home-office-expand-ai-use-asylum-decision-making-after-promising-pilot-results</a>; 
			(47) 
			<a href='https://www.helenbamber.org/sites/default/files/2024-02/memon-et-al-2024-artificial-intelligence-(ai)-in-the-asylum-system.pdf'>www.helenbamber.org/sites/default/files/2024-02/memon-et-al-2024-artificial-intelligence-(ai)-in-the-asylum-system.pdf</a>. Therefore, human oversight must be mandated, particularly for AI-generated interview summaries and country-of-origin reports. Appeals processes must remain fully accessible, as guaranteed under Article 47 of the Charter of Fundamental Rights of the European Union. 
			(48) 
			<a href='https://www.statewatch.org/news/2025/january/eu-human-rights-must-be-central-guiding-basis-for-new-ai-guidelines/'>www.statewatch.org/news/2025/january/eu-human-rights-must-be-central-guiding-basis-for-new-ai-guidelines/</a>.
48. On 11 March 2025, Ms Frida Alizadeh Westerling emphasised before the committee the need to include migrants' perspectives in AI system design. Her research shows that current AI technologies in migration management are largely designed to serve institutional priorities such as efficiency, sometimes at the expense of applicants’ rights. Greater inclusion of migrants’ experiences would help improve trust and the quality of decisions.
49. According to Ms Westerling, certain high-risk AI applications must be unequivocally banned. These include emotion recognition tools, automated credibility assessments and so-called “lie detectors” used in border interviews. These technologies lack scientific validity and, as confirmed by the EU AI Act, violate the principle of human dignity under Article 3 of the European Convention on Human Rights (ETS No. 5, the “Convention”). Similarly, AI-based risk profiling that relies on nationality or ethnicity infringes upon Article 14 of the Convention and must be excluded from use.
50. AI systems deployed in asylum processing must undergo continuous bias audits. If trained on imbalanced datasets, such tools may inaccurately flag discrepancies in applicants’ narratives. The Council of Europe’s HUDERIA methodology offers guidance for resampling data and adjusting algorithms to eliminate discriminatory outcomes.
51. AI also offers potential benefits in managing large-scale arrivals, enabling States and agencies like UNHCR to anticipate migratory flows stemming from conflict or climate events. Tools such as the IOM’s Displacement Tracking Matrix employ mobile phone records, geotagging and social media analysis to assess population movements and predict humanitarian needs. 
			(49) 
			Report of the Special
Rapporteur on contemporary forms of racism, racial discrimination,
xenophobia and related intolerance (10 November 2020), UN doc A/75/590, <a href='https://www.ohchr.org/en/special-procedures/sr-racism/annual-thematic-reports'>www.ohchr.org/en/special-procedures/sr-racism/annual-thematic-reports</a>. These systems help governments identify weaknesses in reception infrastructure and allocate resources accordingly.
52. The UNHCR has used AI technologies extensively for logistical and aid distribution purposes. As noted by Professor A. Beduschi, this includes the Biometric Identity Management System (BIMS), CashAssist and the Global Distribution Tool (GDT) for managing both cash and in-kind assistance in refugee camps. These tools streamline service delivery and improve co-ordination during crises. They also have potential to enhance access to public services and reduce administrative delays. 
			(50) 
			Beduschi,
A., International migration management
in the age of artificial intelligence in Migration Studies,
Volume 9, Issue 3, September 2021, Pages 576–596, <a href='https://academic.oup.com/migration/article/9/3/576/5732839'>https://academic.oup.com/migration/article/9/3/576/5732839</a>.
53. However, Ms Emilie Wiinblad Mathez clarified to the committee on 11 March 2025 that UNHCR does not use AI to determine or review refugee status decisions. Instead, it is exploring the use of generative AI for tasks such as transcribing protection interviews and conducting country-of-origin information research, ensuring all outputs comply with standards of reliability, accuracy, and transparency. 
			(51) 
			Evangelos Kanoulas,
“Unlocking Artificial Intelligence’s Potential in COI Research”,
Research Paper No. 44, UN High Commissioner for Refugees (UNHCR),
February 2025, <a href='https://www.refworld.org/reference/lpprs/unhcr/2025/en/149514'>www.refworld.org/reference/lpprs/unhcr/2025/en/149514</a>. UNHCR is also assessing how AI can help counter disinformation, stressing the need for embedded privacy and safety from design to deployment.
54. AI tools may also contribute to reducing fraudulent or ineligible applications. The ACME chatbot, for instance, supports asylum seekers by cross-referencing their circumstances with legal databases, identifying possible protection statuses and flagging inconsistencies – such as mismatched employment histories – while respecting the transparency requirements of the EU AI Act. 
			(52) 
			<a href='https://arxiv.org/html/2407.09197v1'>https://arxiv.org/html/2407.09197v1</a>.
55. Finally, in both asylum and alien policing contexts, AI systems are increasingly used to conduct risk assessments. These determine whether a person may face harm upon return and whether the principle of non-refoulement applies – even in cases where the individual has not applied for asylum. Such evaluations are ethically and legally critical, but verifying identity and origin remains a persistent challenge, necessitating the use of reliable and accountable AI-supported credibility assessments.

3.4. Stay period

56. Following admission to a host country, migrants, refugees or asylum seekers are generally granted temporary residence that allows them to stay in the country, although some States may offer pathways to permanent settlement. They are expected to comply with the legal requirements of their stay – such as employment, education, or family reunification conditions – while States remain obligated to uphold fundamental rights, including the principle of non-refoulement, which prohibits returning individuals to situations of serious harm. In exceptional circumstances, such as conflict, natural disasters, or human trafficking, States may grant temporary protection to ensure safety and delay removal.

3.4.1. Inclusive integration through AI

57. The integration phase is pivotal for achieving social cohesion and sustainable development. Assembly Resolution 2502 (2023) “Integration of migrants and refugees: benefits for all parties involved” provides a framework for inclusive strategies that promote mutual benefit for both migrants, refugees and asylum seekers and host communities. AI can be leveraged to streamline administrative processes, support employment matching, enhance access to services and empower them through tailored solutions.
58. Ms Mariam Tartousy (Norway) speaking before the committee on behalf of the Advisory Council on Youth, highlighted both the promise and the risks of AI in this context. AI can improve the efficiency of asylum systems and integration services, yet challenges persist around algorithmic transparency, digital literacy and accessibility. She called for enhanced accountability, inclusive design and user-oriented systems to ensure that migrants, refugees and asylum seekers are not excluded or disadvantaged by digital tools.

3.4.2. Bridging the digital divide

59. Many migrants or refugees face digital exclusion, which undermines their ability to access AI-driven services. The UNHCR “Digital Transformation Strategy” recommends that AI tools – such as the AILEM app, co-designed with refugees for language learning – be made available in multiple languages and formats. 
			(53) 
			<a href='https://globalcompactrefugees.org/good-practices/ailem-app'>https://globalcompactrefugees.org/good-practices/ailem-app</a>; <a href='https://ai4good.org/eureka/'>https://ai4good.org/eureka/</a>. Public service chatbots should include offline access, voice-based interfaces and content co-created with migrants or refugees, legal aid providers and community mediators. 
			(54) 
			<a href='https://www.weforum.org/stories/2023/01/ai-in-migration-is-fuelling-global-inequality-how-can-we-bridge-gap/'>www.weforum.org/stories/2023/01/ai-in-migration-is-fuelling-global-inequality-how-can-we-bridge-gap/</a>; 
			(54) 
			<a href='https://globalcompactrefugees.org/good-practices/geomatch-connecting-people-places-using-artificial-intelligence'>https://globalcompactrefugees.org/good-practices/geomatch-connecting-people-places-using-artificial-intelligence</a>. An example is the Aurora chatbot, developed in Latin America, which improves access to information by incorporating migrant or refugee feedback into its design. 
			(55) 
			<a href='https://www.migrationdataportal.org/did-profile/aurora-chatbot-empowering-transit-migrants-reliable-information-and-humanitarian-aid'>www.migrationdataportal.org/did-profile/aurora-chatbot-empowering-transit-migrants-reliable-information-and-humanitarian-aid</a>.
60. Speaking before the committee on 11 March 2025, Ms Emilie Wiinblad Mathez noted the growing use of Large Language Models (LLMs) such as ChatGPT, Gemini and CoPilot, as well as less visible AI systems across the public and private sectors. She stressed that such tools must be evaluated for trustworthiness and contextual relevance, particularly where refugee protection is concerned. Refugees have distinct international protection needs that must guide any AI applications developed in this space.

3.4.3. Ethical labour market matching

61. AI tools like GeoMatch and Annie MOORE are designed to optimise refugee resettlement by considering both individual characteristics – such as education and language proficiency – and local factors like labour market demand and community infrastructure. 
			(56) 
			<a href='https://globalcompactrefugees.org/good-practices/geomatch-connecting-people-places-using-artificial-intelligence'>https://globalcompactrefugees.org/good-practices/geomatch-connecting-people-places-using-artificial-intelligence;</a> 
			(56) 
			<a href='https://www.economics.ox.ac.uk/annie-moore-increasing-employment-of-resettled-refugees-using-matching-machine-learning-and-integer'>www.economics.ox.ac.uk/annie-moore-increasing-employment-of-resettled-refugees-using-matching-machine-learning-and-integer</a>. These tools must prioritise family unity, cultural compatibility and gender sensitivity to avoid reinforcing labour segregation (e.g. directing women disproportionately into low-paid sectors). Feedback loops should be built in to identify and correct placement mismatches. 
			(57) 
			<a href='https://www.economics.ox.ac.uk/annie-moore-increasing-employment-of-resettled-refugees-using-matching-machine-learning-and-integer'>www.economics.ox.ac.uk/annie-moore-increasing-employment-of-resettled-refugees-using-matching-machine-learning-and-integer</a>.
62. Dr William Jones, in a presentation on 3 October 2024, introduced Annie MOORE, which uses United States immigration data to support more accurate job placements. The software reportedly improves employment outcomes by 25-30%. He also presented Annie 2.0, which predicts refugee arrivals and optimises placement even before arrival dates are confirmed, helping authorities anticipate resettlement needs. Finally, Ruth, another tool developed under this initiative, integrates refugee preferences into resettlement decisions and has been used for Ukrainian arrivals in the United States, demonstrating improved speed and responsiveness.

3.4.4. Language learning and cultural adaptation

63. AI supports integration through tailored language and cultural orientation tools. The AILEM app uses culturally relevant scenarios and features like AILEMmap, which geolocates language support services, and AILEMexchange, which connects learners with native speakers. 
			(58) 
			<a href='https://globalcompactrefugees.org/good-practices/ailem-app'>https://globalcompactrefugees.org/good-practices/ailem-app</a>. Similarly, Eureka offers multilingual guides to local customs, including practical information such as recycling procedures in Amsterdam. 
			(59) 
			<a href='https://communicity-project.eu/2025/04/11/an-ai-tool-to-support-immigrants-and-refugees-with-administrative-tasks/'>https://communicity-project.eu/2025/04/11/an-ai-tool-to-support-immigrants-and-refugees-with-administrative-tasks/</a>.
64. AI-powered real-time translation tools such as the MigrantSocial voice-to-text translator support over 100 languages, enabling migrants, refugees and asylum seekers to communicate with landlords, healthcare providers and educators. 
			(60) 
			<a href='https://migrantsocial.org/page/about-migrantsocial'>https://migrantsocial.org/page/about-migrantsocial</a>. These tools have been shown to reduce municipal administrative costs by 23% and improve cross-cultural trust. Enhanced language acquisition also correlates with a 31% reduction in social service use and improved social cohesion. 
			(61) 
			<a href='https://globalcompactrefugees.org/good-practices/ailem-app'>https://globalcompactrefugees.org/good-practices/ailem-app</a>.

3.4.5. Legal, social and economic inclusion

65. AI is also enhancing legal and social support. The Réfugiés.info app in France provides multilingual guidance on healthcare, housing and rights. 
			(62) 
			<a href='https://refugies.info/en'>The public information service
for refugees – Réfugiés.info.</a> The Skendy chatbot, operational in Amsterdam and Prague, helps manage administrative documents, visa renewals and even guides refugees through business registration and grant applications. 
			(63) 
			<a href='https://communicity-project.eu/2025/04/11/an-ai-tool-to-support-immigrants-and-refugees-with-administrative-tasks/'>https://communicity-project.eu/2025/04/11/an-ai-tool-to-support-immigrants-and-refugees-with-administrative-tasks/</a>. In Amsterdam, 68% of refugee-led startups using Skendy secured seed funding within six months. 
			(64) 
			<a href='https://communicity-project.eu/2025/04/11/an-ai-tool-to-support-immigrants-and-refugees-with-administrative-tasks/'>Ibid</a>. Notably, migrant entrepreneurs were found to generate 3.2 times more jobs per capita than native-born citizens, significantly contributing to local economic revitalisation. 
			(65) 
			<a href='https://www.caf.com/en/blog/artificial-intelligence-ai-at-the-service-of-financial-inclusion/'>https://www.caf.com/en/blog/artificial-intelligence-ai-at-the-service-of-financial-inclusion/</a>; 
			(65) 
			<a href='https://rbcdsai.iitm.ac.in/blogs/can-ai-facilitate-the-digital-financial-inclusion-of-migrant-workers/'>https://rbcdsai.iitm.ac.in/blogs/can-ai-facilitate-the-digital-financial-inclusion-of-migrant-workers/</a>.

3.4.6. Governance, oversight, and predictive tools

66. AI is increasingly being applied in long-term stay and Schengen area integration decisions. Authorities may use AI to track legal compliance, monitor residency conditions, or assist with fraud prevention. Yet, concerns over privacy, due process and non-discrimination require robust legal safeguards and independent audits. As outlined in the “Principles for the Ethical Use of Artificial Intelligence in the United Nations System”, States should conduct annual risk assessments to detect discriminatory practices, such as algorithmic redlining in housing allocations. 
			(66) 
			<a href='https://www.un.org/digital-emerging-technologies/sites/www.un.org.techenvoy/files/GDC-submission_UNHCR.pdf'>www.un.org/digital-emerging-technologies/sites/www.un.org.techenvoy/files/GDC-submission_UNHCR.pdf</a>; 
			(66) 
			<a href='https://ai4good.org/eureka/'>https://ai4good.org/eureka/</a>.
67. AI systems can also support geographical allocation by matching asylum seekers to regions where they are most likely to succeed, based on skill compatibility, community networks and service availability. Predictive tools are already in use for urban planning, such as in Utrecht, where AI-informed housing strategies reduced ethnic segregation by 19% and increased innovation and social cohesion. 
			(67) 
			<a href='https://www.living-in.eu/news/digital-solutions-migration-management'>https://www.living-in.eu/news/digital-solutions-migration-management;</a> 
			(67) 
			<a href='https://ijrpr.com/uploads/V6ISSUE1/IJRPR37902.pdf'>https://ijrpr.com/uploads/V6ISSUE1/IJRPR37902.pdf</a>.
68. AI integration strategies yield a dual dividend: they accelerate self-sufficiency while enhancing the economic and social resilience of host communities. To realise this potential, member States must scale solutions like GeoMatch, invest in inclusive language technologies like AILEM and uphold ethical standards under the Council of Europe Framework Convention on AI.
69. Finally, as shown in research by Bansak et al., AI-assisted refugee placement based on personal and regional data (e.g. language, education, local employment markets) can lead to significantly improved integration outcomes. This form of data-driven decision making enables policymakers to customise allocations and improve long-term prospects.

3.4.7. AI in education and future preparedness

70. AI can also transform educational access for migrant or refugee children and adults. Personalised language learning tools offer real-time feedback on pronunciation, fluency and comprehension, adapting to individual progress. These innovations can play a vital role in helping migrants, refugees and asylum seekers, especially youth, to adapt more quickly and confidently to their host societies.

3.5. Circular migration and return stages

71. Circular migration refers to the repeated movement of individuals between countries, such as seasonal workers or permanent residents maintaining ties with their countries of origin. When voluntary, it can benefit both home and host countries economically and socially. Migrants may return voluntarily for personal or professional reasons, though some returns are involuntary due to loss of legal status. In such cases, assisted voluntary return and reintegration programmes offer a more dignified alternative to forced deportation.
72. States must ensure return processes are safe, voluntary and informed. AI-powered tools – such as chatbots for return assistance – can improve access to reintegration support but must not pressure migrants into return. These systems should follow the OECD Guidelines on AI Fairness. 
			(68) 
			<a href='https://www.oecd.org/migration/mig/EMN-OECD-INFORM-FEB-2022-The-use-of-Digitalisation-and-AI-in-Migration-Management.pdf'>www.oecd.org/migration/mig/EMN-OECD-INFORM-FEB-2022-The-use-of-Digitalisation-and-AI-in-Migration-Management.pdf</a>; 
			(68) 
			<a href='https://www.weforum.org/stories/2023/01/ai-in-migration-is-fuelling-global-inequality-how-can-we-bridge-gap/'>www.weforum.org/stories/2023/01/ai-in-migration-is-fuelling-global-inequality-how-can-we-bridge-gap/</a>.
73. AI platforms managing circular migration, such as the EU Blue Card Network must uphold data protection standards, allowing migrants to delete or transfer personal data, and prohibiting biometric data sharing with countries of origin, particularly where risks of persecution exist. 
			(69) 
			<a href='https://www.oecd.org/migration/mig/EMN-OECD-INFORM-FEB-2022-The-use-of-Digitalisation-and-AI-in-Migration-Management.pdf'>www.oecd.org/migration/mig/EMN-OECD-INFORM-FEB-2022-The-use-of-Digitalisation-and-AI-in-Migration-Management.pdf</a>; 
			(69) 
			<a href='https://www.vfsglobal.com/en/individuals/insights/enhancing-border-management-systems-using-artificial-intelligence.html'>www.vfsglobal.com/en/individuals/insights/enhancing-border-management-systems-using-artificial-intelligence.html</a>. The UNHCR 2022 “General Policy on Personal Data Protection and Privacy” mandates strict encryption, limited access, and data deletion post-decision. 
			(70) 
			<a href='https://www.un.org/digital-emerging-technologies/sites/www.un.org.techenvoy/files/GDC-submission_UNHCR.pdf'>www.un.org/digital-emerging-technologies/sites/www.un.org.techenvoy/files/GDC-submission_UNHCR.pdf</a>.
74. AI can also support environmental risk assessments for return destinations using satellite imagery and predictive analytics. States can use AI to assess environmental conditions in regions of return. For example, satellite imagery analysed via machine learning could verify whether drought conditions in Somalia have sufficiently abated for safe repatriation. AI analyses satellite imagery to verify safe conditions in regions of return. Chatbots may notify returnees of these assessments while encrypting biometric data. 
			(71) 
			<a href='https://naturenews.africa/iom-microsoft-use-ai-to-combat-climate-driven-migration/'>https://naturenews.africa/iom-microsoft-use-ai-to-combat-climate-driven-migration/</a>; 
			(71) 
			<a href='https://phys.org/news/2024-10-ai-climate-driven-migration.html'>https://phys.org/news/2024-10-ai-climate-driven-migration.html</a>.

3.6. Sustainable integration and reintegration stages

75. Integration involves the mutual adaptation of migrants, refugees and asylum seekers and host societies, enabling them to actively participate in all aspects of life – social, economic, cultural and political. It is a two-way process built on shared responsibility and focused on inclusion and social cohesion.
76. Reintegration, on the other hand, supports returning migrants in re-establishing their lives in their country of origin. It emphasises economic, social and psychosocial well-being, aiming to make future migration a matter of choice, not necessity.
77. To support sustainable integration and reintegration, States should implement long-term monitoring systems and community-based impact assessments, use AI tools like IOM’s livelihood matching algorithms and the EU Digital Services Act reporting tools to track outcomes such as employment retention and social cohesion, and promote digital literacy and provide offline-accessible AI assistants (e.g. Eureka) for tasks like healthcare enrolment or language learning. 
			(72) 
			<a href='https://publications.iom.int/system/files/pdf/pub2024-033-l-return-reintegration-2023-highlights_1.pdf'>https://publications.iom.int/system/files/pdf/pub2024-033-l-return-reintegration-2023-highlights_1.pdf</a>; 
			(72) 
			<a href='https://migrationletters.com/index.php/ml/article/view/7575'>https://migrationletters.com/index.php/ml/article/view/7575</a>.
78. For anti-discrimination, natural language processing (NLP) can be used to detect hate speech online. Tools like Sol.ai offer offline digital service tutorials, while NLP systems monitor xenophobic rhetoric. The Council of Europe Committee on Artificial Intelligence (CAI) stresses the importance of combining AI with human oversight to ensure contextual accuracy and prevent over-censorship. 
			(73) 
			<a href='https://glowaction.org/a-comprehensive-guide-to-sol-ai-glows-innovative-chatbot-dedicated-to-enhancing-language-learning-for-refugees/'>https://glowaction.org/a-comprehensive-guide-to-sol-ai-glows-innovative-chatbot-dedicated-to-enhancing-language-learning-for-refugees/</a>.

4. Cross-cutting aspects

79. To ensure that AI serves migrants, refugees and asylum seekers without compromising human dignity or justice, member States must ground AI governance in human rights frameworks and implement safeguards across all stages of the migration process. Binding legal structures, including the Council of Europe Framework Convention on AI, should be adopted through signature and ratification. 
			(74) 
			<a href='https://www.coe.int/en/web/artificial-intelligence/work-in-progress'>www.coe.int/en/web/artificial-intelligence/work-in-progress</a>; 
			(74) 
			<a href='https://edoc.coe.int/en/artificial-intelligence/11926-council-of-europe-framework-convention-on-artificial-intelligence-and-human-rights-democracy-and-the-rule-of-law.html'>https://edoc.coe.int/en/artificial-intelligence/11926-council-of-europe-framework-convention-on-artificial-intelligence-and-human-rights-democracy-and-the-rule-of-law.html</a>. Participatory design, such as refugee involvement in AI development (e.g. the Eureka model), can help ensure systems address real needs and avoid reinforcing institutional bias. 
			(75) 
			<a href='https://ai4good.org/eureka/'>https://ai4good.org/eureka/</a>.
80. Capacity building is essential. EU Digital Europe Programme funds may support training for migration officers in AI ethics, 
			(76) 
			<a href='https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai'>https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai</a>. while NGOs involved in border surveillance audits must also receive resources and training. Caseworkers and asylum officers should be trained to critically assess AI outputs, especially when discrepancies arise between automated summaries and original testimony. 
			(77) 
			<a href='https://inkstickmedia.com/for-migrants-artificial-intelligence-becomes-a-roadblock-to-europe/'>https://inkstickmedia.com/for-migrants-artificial-intelligence-becomes-a-roadblock-to-europe/</a>. As highlighted in the UNHCR “Digital Transformation Strategy”, staff must be able to recognise algorithmic bias and understand the limitations of AI – such as difficulties in interpreting trauma-induced speech patterns. 
			(78) 
			<a href='https://www.gov.uk/government/publications/evaluation-of-ai-trials-in-the-asylum-decision-making-process'>www.gov.uk/government/publications/evaluation-of-ai-trials-in-the-asylum-decision-making-process</a>; 
			(78) 
			<a href='https://www.helenbamber.org/sites/default/files/2024-02/memon-et-al-2024-artificial-intelligence-(ai)-in-the-asylum-system.pdf'>www.helenbamber.org/sites/default/files/2024-02/memon-et-al-2024-artificial-intelligence-(ai)-in-the-asylum-system.pdf</a>. It emphasises the need to train staff to recognise algorithmic biases and contextualise AI outputs. 
			(79) 
			<a href='https://www.un.org/digital-emerging-technologies/sites/www.un.org.techenvoy/files/GDC-submission_UNHCR.pdf'>www.un.org/digital-emerging-technologies/sites/www.un.org.techenvoy/files/GDC-submission_UNHCR.pdf</a>; <a href='https://www.helenbamber.org/resources/research/artificial-intelligence-ai-asylum-system'>www.helenbamber.org/resources/research/artificial-intelligence-ai-asylum-system</a>.
81. A broader effort is needed to improve the AI-related competences of all actors in migration and asylum governance. According to the European Commission report “Opportunities and challenges for the use of artificial intelligence in border control, migration and security”, effective implementation requires a multidisciplinary mix of skills spanning policy, law, ethics, data science, AI engineering and systems design. AI Centres of Excellence will play a central role in advancing this capacity. 
			(80) 
			Opportunities
and challenges for the use of artificial intelligence in border
control, migration and security, op.cit.
82. Finally, data protection remains a critical concern. The work of eu-LISA underscores the need to ensure the security of personal data, linking human rights protections directly to secure and ethical AI deployment in migration systems.

5. Conclusion

83. Artificial intelligence is increasingly shaping migration and asylum procedures, affecting migrants, refugees and asylum seekers and host societies alike. While technological innovation presents opportunities to improve efficiency and service delivery, its use must be firmly grounded in the principles of human rights, democracy and the rule of law. A critical challenge lies in balancing humanitarian protection with border security and public safety.
84. Europe must actively shape its own AI governance model rather than relying on regulatory approaches from other regions. This requires integrating European values into the design and use of AI, particularly in sensitive areas such as migration. AI is already being used extensively at the pre-departure and arrival stages of migration for identity verification, risk assessment, surveillance and asylum case processing. However, its use in return procedures remains limited.
85. To ensure safe and ethical deployment of AI, member States must implement stage-specific safeguards aligned with the Refugee Convention and Council of Europe standards. These include ensuring that asylum decisions remain human-led, involving migrants, refugees and asylum seekers in the co-design of integration tools and establishing protocols for data governance, auditing and redress. AI impact assessments must be carried out systematically to evaluate the potential consequences on rights and freedoms.
86. The Council of Europe HUDERIA methodology provides a structured approach to assessing human rights risks. High-risk AI applications should be prohibited and strong oversight mechanisms, including independent review boards, should be established. These bodies must include civil society, legal and technical experts to ensure accountability and compliance with international protection standards.
87. Redress mechanisms must be readily available and accessible. Asylum seekers should have the right to challenge AI-generated evidence, such as flawed interview summaries or biased analyses, through fast-track judicial review processes. Legal aid should be expanded to support such challenges, and reparations must be available where harm results from algorithmic errors. States party to the Council of Europe Framework Convention on AI must guarantee effective remedies for rights violations.
88. Ethical AI-powered tools, such as chatbots, can increase access to information and reduce vulnerability if implemented with proper safeguards. Their design should be participatory and future developments must prioritise interoperability and offline functionality to support digitally excluded migrant populations.