Pre-migration: Access to informa­tion, selection, and application

Even before migration takes place, digital and, in some cases, algorithmic systems shape key decision points in the migration process. States use them to standardise and expedite procedures to align them more closely with political objectives, in particu­lar through upstream selection, ranking, and screening mechanisms.

A well-known example is Canada’s Ex­press Entry system. Prospective migrants create digital profiles that are automatically evaluated and ranked based on defined criteria such as qualifications, professional experience, or language proficiency. Migra­tion is thus structured even before a formal application is submitted, with political objec­tives translated into data fields, point systems, and algorithmic selection mecha­nisms that determine whose profile is ad­mitted for further review.

This form of digital advanced screening is also gaining importance at the European level. With the European Travel Informa­tion and Authorisation System (ETIAS), which is scheduled to go into operation in the last quarter of 2026 after previous delays, personal data from online applications, such as nationality and employment status, will be automatically cross-checked against existing EU databases. Rule-based and algorithmic procedures are used to assess security and migration-policy risks in advance and to categorise travellers even before they cross the border. Migration-policy control is thus increasingly shifting to upstream decision-making spaces.

In addition, many OECD countries use automated document and plausibility checks in digital visa procedures. Proof of identity, education, or employment is recorded digi­tally and checked for consistency and anomalies using automated systems, often before a formal official assessment.

These government instruments are com­plemented by digital offerings from non-governmental sources. Job placement plat­forms such as Upwork and freely accessible online self-assessment tools for estimating one’s immigration prospects (such as point calculators for programmes such as Cana­da’s) already influence migration decisions at an early stage by managing expectations and encouraging self-selection.

Information gathering, application sub­mission, and pre-screening are therefore increasingly taking place online and in a semi-automated manner. This facilitates access to procedures and can speed up pro­cesses, but it also increases the importance of standardised personal, qualification, and procedural data, of criteria catalogues, and of technical assessment systems. Biased datasets, selective selection criteria, and limited opportunities for correction can systematically disadvantage certain regions of origin, education paths, or employment histories, for example if training or refer­ence data primarily reflect certain profiles and classify others as “high-risk”. In this way, existing inequalities are reproduced at an early stage of the migration process.

During migration: Infrastructure, management, and protection

During migration, digital and data-driven systems are primarily used to record, link, and manage mobility operationally, while also supporting and protecting migrants.

In the EU, large IT infrastructures form the backbone of the so-called smart border approach. These include databases such as Eurodac, which stores biometric data on asylum seekers and irregular migrants, and the planned Entry/Exit System (EES), which is scheduled for progressive rollout from 2025/26. These instruments aim to system­atically record the movements of third-country nationals and link them via inter­operable systems. The objective is to attri­bute identities more clearly, trace travel and stay histories, and identify security and migration-policy risks earlier.

Aggregated data on border crossings, registrations, or movement patterns will be used to identify changing migration routes, regional hotspots, or seasonal shifts, and to derive operational situational assessments. Building on this, data-driven analytical methods support the prioritisation of per­sonnel, screening capacities, and control measures. In this way, such systems influ­ence where authorities focus their efforts and which developments or cases are moni­tored more closely.

Beyond the analysis of existing movement patterns, predictive approaches are also gaining importance. Researchers, inter­national organisations, and security agen­cies are increasingly experimenting with data-intensive models and machine learn­ing to anticipate refugee and migration movements, for example in connection with conflicts, climate risks, or economic shocks. Such predictive models promise earlier planning and prevention, but they are methodologically highly controversial and heavily dependent on data availability and model assumptions. They also raise questions about responsibility, perverse in­centives, and the political use of forecasts.

Digital and semi-automated procedures are also used in the asylum context, for ex­ample in registration, biometric identification, and the prioritisation of procedures. Country-of-origin analyses, security checks, and plausibility checks are in part supported by data-driven methods. This can speed up procedures, but it also increases reliance on data quality, assessment logics, and tech­nical standards in a particularly sensitive protection context.

These developments are also being ad­dressed politically at the EU level: The Com­mission plans to establish a “Forum for AI on Migration” in 2026 to systematically re­view and structure the use of AI in asylum, migration, and border management.

International organisations also use digi­tal systems. The International Organization for Migration (IOM) deploys digital data-capture and analytical tools through MIDAS (Migration Information and Data Analysis System) to register border crossings and evalu­ate migration data, in particular in countries of origin and transit. The United Nations High Commissioner for Refugees (UNHCR) operates PRIMES (Population Regis­tration and Identity Management EcoSystem), a global digital identity and registration system for refugees. This sys­tem combines biometric and biographic data to enable access to protection and assistance and to prevent multiple regis­trations.

Private technology companies are involved in the technical implementation of many of these systems. Consulting and IT service providers such as Accenture, and data-analytics companies such as Palantir, provide software for the integration, visu­alisation, and analysis of large volumes of data, thereby shaping the operational design of migration-policy management. Alongside state and international authorities, civil society and humanitarian actors also play an important role with their digi­tal offerings. Apps and platforms such as RefAid support orientation, access to infor­mation, and networking with local support services.

This phase in particular highlights how closely administration, control, and protec­tion are intertwined in digital migration systems – the same infrastructures that enable access to assistance also structure the monitoring, categorisation, and priori­tisation of mobility.

After migration: Integration, remittances, and return

After arrival in the destination country, digital and algorithm-based systems pri­marily shape how integration is organised, how access to the labour market is facili­tated, and how conditions of stay are man­aged. A key area is the recognition of quali­fications and access to the labour market. In Germany, for example, the relevant pro­cedures are increasingly being handled digi­tally, for example via online portals such as “Anerkennung in Deutschland” (Recog­nition in Germany), which consolidates competent authorities, required documen­tation, and procedural steps. This speeds up processes, but it also shifts organisational responsibility onto migrants, who must pro­vide documents digitally and actively man­age procedures.

Building on this, algorithmic matching and recommendation systems are being deployed. Public employment services and private platforms use digital profiles, auto­mated skills matching, and ranking logics to assign migrants to occupational fields or support measures. Private employers are not only users of these procedures but also indirectly involved in their design, for ex­am­ple through requirement profiles, selec­tion practices, and the choice of platforms and systems. In countries such as Canada, administrative data are systematically evaluated to align integration programmes more closely with labour-market needs and to prioritise measures.

Digital identities now also play an increasingly central role. In countries with well-developed e-government structures, such as Estonia, they serve as a central point of access to administrative services, the labour market, health care, and bank­ing services. Digital identity is thus effec­tively becoming a prerequisite for social participation.

In some countries, digital systems are also used for residence administration and compliance management. In the United Kingdom, for example, fully digital eVisas replace physical residence permits; migrants’ rights and obligations are verified and checked via online systems. The legal secu­rity of residence status is thus increasingly dependent on reliable digital infrastructures.

Another key area for such applications is the financial sector. Digital service pro­viders such as WorldRemit and Sendwave enable fast and inexpensive money transfers to countries of origin. This makes remit­tances more accessible, while at the same time generating detailed data on income, transfer behaviour, and transnational net­works, which creates new dependencies on private payment platforms.

In the context of return and reintegration, international organisations such as the IOM – in Bangladesh, for example – also use digital databases to record support needs and plan interventions, among other things. Depending on the context, information from previous residence or asylum procedures may also be included. Such data integration can make reintegration pro­grammes more targeted, but it also raises ques­tions about purpose limitation, in­formed consent, and the handling of sensi­tive personal data.

Digital systems thus have a less visible but more structural impact after migration. They shape integration trajectories, access to work and services, and the conditions for legal security. They can facilitate access and speed up procedures, but at the same time create dependencies on platforms, data infra­structures, and algorithmic logics.

A shared pattern emerges across all phases of migration: Digital systems not only trans­form migration management through effi­ciency gains, but also embed it within up­stream infrastructures, data models, and prioritisation logics. Unlike in largely ana­logue processes, selection, categorisation, and risk assessment are increasingly stand­ardised, scaled, and technically pre-struc­tured. This accelerates procedures, but it also determines whose mobility becomes possible, visible, or administratively action­able, and it shifts political decisions in part into technical preliminary decisions.

Digital labour mobility: From physical to virtual migration

Digital technologies are changing inter­national migration by enabling new forms of transnational employment that, in some segments, can partially replace physical migration or restructure it. Digital platforms, cloud infrastructures, and algorithmic matching systems are making it increas­ingly possible to work, irrespective of loca­tion. In certain segments, activities that previously required physical mobility can now be offshored digitally – a process often described as “virtual migration”.

Knowledge-intensive and standardisable activities, for example in the fields of IT, design, data processing, and digital services, are particularly suitable for virtualisation. For countries of origin, this can create new income opportunities without incurring the social and financial costs of physical migra­tion. Countries such as India, the Philippines, and increasingly African countries have specifically built up digital service sec­tors that are integrated into global value chains, and they are benefiting from the growing demand for digital labour.

At the same time, this development can indirectly influence migration policy in destination countries. If labour for certain activities is available digitally, this can reduce political pressure to expand physical immigration pathways in certain segments, depending on the labour market and regu­latory framework. Virtual labour mobility thus acts in part as a functional substitute for migration. However, this applies only where tasks can genuinely be virtualised and where companies, labour laws, and infrastructure enable this form of work.

However, a large proportion of economically relevant work remains location-bound. Jobs in health care, construction, agriculture, logistics, and personal services require physical presence and are heavily dependent on migrant workers in many destination countries. While knowledge-intensive activities can increasingly be delivered digi­tally, physical migration therefore concentrates more on non-virtualisable, often low- or medium-skilled activities, which are often associated with precarious working conditions and limited legal protection.

Virtual and physical migration are thus not developing in parallel but diverge along lines of work and skills profiles. Digital labour mobility shifts employment oppor­tunities into the virtual space, while physi­cal mobility remains indispensable in key sectors. This dynamic is changing migration patterns, exacerbating inequalities between different groups of workers, and raising questions about regulation, social protection, and fair participation.

New power asymmetries

Furthermore, the increased use of data-driven and automated systems in migration management is changing power relations and dependencies. Digital procedures struc­ture access, priorities, and decision work­flows and therefore do not operate neutrally but can affect different groups unequally, depending on their design.

For migrants, asymmetries vis-à-vis state authorities are intensifying. Decisions on mobility, residence, or access to services are increasingly based on complex data-process­ing and assessment systems whose func­tion­ing is often difficult to understand for those affected. Opportunities to review, correct, or challenge such assessments effec­tively often remain limited, especially in transnational procedural phases and where transparency and justification requirements are weak.

At the same time, new dependencies on digital services are emerging. Platforms, apps, and automated systems are becoming central interfaces for information, procedures, and support services. Those who do not have access to these systems, or who lack sufficient digital skills, are structurally disadvantaged, regardless of their formal legal status.

Power relations between states are also shifting. Countries with well-developed data infrastructures and analytical capac­ities can capture, prioritise, and manage migration in a more targeted manner. States with limited resources, by contrast, tend to be more dependent on external sys­tems, international organisations, or private technology providers, and they have less influence on technical standards, data use, and system design.

Lastly, dependence on private technology companies is increasing. External software solutions, data platforms, and analytical tools shape the operational design of migra­tion-policy management, thereby influencing how selection, prioritisation, and assess­ment processes are technically implemented. This creates new, long-term lock-ins to indi­vidual providers because core infrastructures, data formats, and workflows are tai­lored to their systems. Switching can then be associated with high costs, risks, and loss of functionality. These actors thus exert in­fluence over key instruments of migration governance without themselves being po­litically accountable – with consequences for transparency, accountability, and the state’s capacity to exercise control.

Migration in the global data economy

With the ongoing digitalisation of migration processes, data itself is becoming a key resource for both political control and eco­nomic value creation. Information about identity, mobility, qualifications, or resi­dence histories forms the basis of digital migration systems and is therefore syste­matically collected, linked, and evaluated. Migration is thus increasingly embedded in networked data infrastructures that extend beyond individual procedures.

In this logic, migration is shifting from a primarily administrative policy area to a data-driven domain of control. Countries and organisations that can capture, link, and evaluate large volumes of data gain structural influence over how mobility is shaped. Analytical capacities, technical stand­ards, and interoperable systems become strategic resources that help deter­mine political room for manoeuvre.

This data economy is organised trans­nationally. Migration-related data circulate across national borders and are used by states, international organisations, and pri­vate actors. Control over infrastructures and analytical capacities is concentrated in the hands of a few actors, while countries of origin and transit, in particular, often have only limited influence on usage, onward processing, and standard-setting.

For migrants, being embedded in this global data economy means increased vis­ibility. Data can facilitate access to mobility, work, or services, but they also structure how people are categorised, assessed, and slotted into administrative templates. Ques­tions of data sovereignty, purpose limitation, rights safeguards, and international accountability often remain largely un­resolved and can only be regulated to a limited extent within national legal frame­works.