What examples are there of AI‑enabled proactivity in Europe?

Germany’s BG Bau uses AI to identify companies with heightened accident risks, enabling more targeted inspections and preventive interventions. Sweden and the UK are deploying AI to forecast rehabilitation needs and injury risks, supporting more individualized support pathways

What is the tell-it-once principle?

This is about enabling citizens to submit their information a single time and have it securely reused across unemployment services, healthcare, family support, housing authorities, and private training provider.

What is the European Health Data Space?

The EHDS is the first common EU data space dedicated to a specific sector – one of several created by the European Commission to collectively create a data sovereign, interoperable and trustworthy data sharing environment. The objective of the EHDS is to foster a health-specific data environment that supports a single market for digital health services and products across Europe.

Trends in 2026 for welfare – How is digitalization accelerating service improvements?

Capgemini

Mar 18, 2026

Welfare agencies are entering a decisive stage in their digitalization journey. Across the public sector, 64% of organizations worldwide are already exploring or actively developing GenAI initiatives, and welfare agencies are increasingly drawing on these capabilities to modernize services. At the same time, new risks must be navigated, including the potential for biased or unethical outcomes if AI systems are deployed without sufficient oversight, transparency, or accountability, and increasing concerns around digital sovereignty in Europe.

In summary

Welfare programs are becoming more focused, data‑driven, and responsive to people’s real needs
Only with transparent and responsible design will welfare organizations fully realize the promise of AI
Interoperability has rapidly shifted from a technical ambition to a strategic necessity in welfare systems
Hybrid sovereignty strategies balance hyperscaler capabilities with strong local control over sensitive data
Legacy modernization has become an imperative in the transformation of welfare systems
Welfare systems must be resilient, trusted, and fit for the social and economic realities of the years ahead

Social protection systems have never been more digital. Evidence from the Organization for Economic Co-operation and Development (OECD) shows that AI is now widely used across global welfare. It can be seen supporting citizens, automating processes, detecting fraud, and enabling early‑warning analytics that make systems more proactive and responsive to risk.

This technological acceleration coincides with rising expectations for interoperable services, particularly within the EU, as post‑pandemic mobility reshapes citizen needs. Yet despite this momentum, growing geopolitical tensions have heightened concerns about reliance on foreign technologies. This is adding to other societal pressures, such as aging populations, and creating an increasingly complex modernization landscape for welfare agencies worldwide.

Drawing on our global footprint, Capgemini has supported welfare organizations in navigating this evolving environment. This has enabled us to identify the major trends shaping welfare delivery this year, most notably the rise of more mature AI adoption and the intensifying focus on digital sovereignty.

How welfare agencies can balance capability and security with hybrid sovereignty

Sovereignty is now a key driver prompting welfare agencies to reshape their cloud strategies. Indeed, it has become increasingly critical to the success and integrity of welfare programs as digital transformation deepens.

Despite advances in European cloud offerings, many Welfare systems operate on hyperscaler infrastructure, which for certain workload classes creates residual extraterritorial risk exposure under legislation such as the US CLOUD Act, a dependency that agencies should assess and manage, not necessarily eliminate.

This has led to uneven cloud adoption across Europe, from comprehensive strategies in the UK, Denmark, and Norway to strong resistance in Sweden, Germany, and France. This latter resistance is driven by compliance concerns related to regulatory requirements (GDPR, DORA, NIS2), and EU court rulings such as Schrems I and II.

As geopolitical tensions intensify and US–EU relations grow more complex, agencies must navigate an increasingly difficult balance between using advanced cloud capabilities and maintaining compliance, security, and control over sensitive citizen data. Given that full-stack sovereignty across all technology layers remains an aspiration rather than a near-term reality for any welfare agency, a “hybrid sovereignty” model is emerging as a pragmatic approach for welfare agencies in 2026.

What does hybrid sovereignty look like?

This involves diversifying providers, increasing local control, and selectively allocating hyperscaler services to workloads whose sovereignty risk profile is consistent with those tiers, while routing the most sensitive citizen data to national sovereign environments or on-premise systems. At the same time, highly sensitive data is kept within EU‑owned environments or on‑premise systems.

Early implementations of this approach are already visible, such as France’s Cloud de Confiance label and the Bleu solution developed by Capgemini and Orange, designed for French and EU jurisdictional control with operational separation from US legal reach. Alongside frameworks like the EU Cybersecurity Certification Scheme (EUCS), these initiatives reflect a broader shift toward reconciling competitiveness with security.

As reliance on foreign technology continues to pose risks, welfare agencies will increasingly need to chart their own hybrid pathways to safeguard sovereignty. At the same time, they must focus on ensuring modern, resilient, and effective service delivery.

Why is modernizing the legacy IT backbone an urgent imperative in welfare?

Replacing legacy systems remains one of the most persistent challenges for welfare organizations worldwide. Many agencies were early adopters of IT in the 1970s and 1980s, but the systems they built, often monolithic and written in aging languages such as COBOL, have become increasingly fragile, costly, and complex to maintain.

Across Europe, outdated welfare payment systems alone are estimated to cost governments up to 1.5% of GDP each year due to delays, administrative inefficiencies, and operational burdens. Despite efforts to modernize, these legacy platforms are still embedded deep within essential welfare processes, often remaining in place even when new digital services are introduced.

Welfare agencies are confronting demographic pressures such as Europe’s rapidly aging population, now representing 20.3% of the EU’s residents and expected to rise steadily over the coming decades. These pressures mean that the ability to modernize legacy systems becomes central to sustaining reliable, adaptive, and equitable welfare services in 2026.

How are legacy systems constraining digital transformation in welfare – and how can AI help?

This urgency is further amplified as long‑recognized “smoldering platforms,” such as skill shortages in legacy programming and limited vendor support, escalate into genuine operational risks. A recent cross‑government analysis in Europe published by the Government Transformation Magazine found that legacy systems now consume such a substantial share of public‑sector IT resources that they are seen as the key barrier to digital transformation, constraining both innovation and service integration efforts.

Agencies increasingly recognize that incremental updates are no longer sufficient. They need modern, modular architecture capable of supporting interoperability, new policy demands, and advanced analytics. In this context, AI‑supported software engineering has become a critical accelerator.

While AI cannot automatically replace entire systems, it can dramatically speed up the analysis of decades‑old codebases and embedded logic, reducing modernization timelines and lowering risks. Combined with more strategic transformation planning, these capabilities provide welfare agencies with a realistic, forward‑looking pathway to replace aging systems without recreating the next generation of technical debt.

How is AI moving beyond the hype to create proactive welfare service delivery?

AI is no longer an experimental layer in welfare; it now underpins core processes across social protection systems. OECD and ISSA analyses show that AI is widely used for customer‑facing services, internal automation, fraud detection, and risk management. This reflects its move into mission‑critical workflows and aligns with broader public‑sector trends.

According to a report on Data and Government by the Capgemini Research Institute, 91% of public organizations are exploring, piloting, or have already integrated GenAI into their customer service operations. With predictive analytics, agencies can anticipate citizen needs before they escalate and provide more personalized, efficient services.

As welfare systems replicate successful early use cases, they are beginning to tap into the wider potential of emerging technologies such as Agentic AI. In 2026, this shift is expected to accelerate as agencies refine existing systems and explore new AI‑driven capabilities that enhance both operational precision and citizen outcomes.

What’s being done to build trust in these new AI-based services?

This growing incorporation of AI into welfare services means that explainability and accountability are no longer optional. Thus, we are seeing the following:

Welfare agencies are increasingly adopting Explainable AI (XAI) techniques to make algorithmic decisions transparent, auditable, and understandable to both caseworkers and citizens.
In parallel, Human‑in‑the‑Loop (HITL) mechanisms ensure that automated outputs support, rather than replace, professional judgment, particularly in high‑impact decisions such as eligibility, sanctions, or benefit adjustments.

Together, XAI and HITL approaches help agencies preserve trust, comply with legal obligations, and retain clear lines of responsibility while still benefiting from automation and predictive analytics at scale.

Across Europe, practical examples of AI‑enabled proactivity are already emerging – see FAQs, below. These advancements also contribute to broader institutional transformation, including helping governments map and modernize legacy systems.

Yet one major obstacle remains: public trust. Among OECD countries’ citizens, approximately only 40% view AI-supported application processing as positive for users, highlighting persistent concerns about fairness, transparency, and data use.

To overcome this trust barrier, welfare agencies must focus not only on scaling AI but on doing so responsibly. How? By improving explainability, ensuring data quality, using chatbots only when they add demonstrable value, and embedding strong governance frameworks. Building trust through transparency and responsible design will be essential for welfare organizations to fully realize AI’s promise of more proactive, personalized, and equitable services.

Why is interoperability part of digital transformation in welfare?

Interoperability has rapidly shifted from a technical ambition to a strategic necessity in welfare systems. This comes as societies become more mobile, labor markets more fluid, and citizen needs more complex.

The European Commission’s first Annual Report on Interoperability in the European Union shows the EU has made “steady advances toward more connected, efficient, and citizen‑centered digital public services across borders”. This has been driven by the Interoperable Europe Act and the establishment of the Interoperable Europe Board and Portal.

By 2026, a major milestone will be the integration of core interoperability components, such as the European Search Portal (ESP) and the Common Identity Repository (CIR), as part of the EU’s broader interoperability roadmap, with full architectural operationalization expected by 2028. This shift underpins the “tell‑us‑once” principle – see FAQs, below. As shared data architectures improve, agencies gain the ability to build a 360° overview of beneficiaries, reducing administrative duplication, accelerating entitlements, and strengthening fraud detection across borders.

The European Union is driving this transformation through its Interoperability Roadmap, which targets integration of major components like the European Search Portal and Common Identity Repository by mid‑2026, with full architecture operational by 2028. These milestones are pushing welfare agencies to:

Harmonize data formats
Adopt open standards
Expand shared information into new areas, such as disability, care pathways, and professional mobility.

However, achieving these goals requires overcoming significant challenges, including some already mentioned in this article: modernizing legacy systems, ensuring data quality, and complying with strict legal frameworks for sensitive personal information (sovereignty). Organizations that combine gradual system upgrades with robust privacy controls, staff training, and ongoing audits will be best positioned to deliver faster, more coordinated services and reduce administrative burdens.

Data sharing is becoming a strategic lever for efficiency, continuity of rights, and fraud prevention. By cross‑referencing entitlements and household composition, agencies can reduce inconsistencies and detect undue payments, while mechanisms like the Nominative Social Declaration automate contribution checks and flag anomalies.

At the European level, interconnected systems enable monitoring of common indicators such as compliance rates, processing times, and fraud detection, shortening verification cycles and optimizing public resources. For citizens, this means simpler, fairer services and guaranteed continuity of rights during life transitions; for agencies, it lowers costs and strengthens sustainability through proactive fraud control and streamlined processes.

From a beneficiary perspective, these changes translate into more continuity and less friction. A worker moving across borders, for example, no longer needs to repeatedly resubmit the same employment or family information to multiple authorities. Instead, entitlements follow the individual, enabling faster access to unemployment support, healthcare, or family benefits during life transitions, reducing stress at moments when support matters most.

Achieving this vision requires welfare agencies to address persistent obstacles, including legacy system modernization, data quality, and compliance with strict data‑protection frameworks. The 2026 Interoperable Europe Agenda emphasizes the need to harmonize data formats, adopt open standards, and scale reusable interoperability solutions, such as core vocabularies and common semantic frameworks, across Member States.

At the same time, EU initiatives like MyHealth@EU and the European Health Data Space (see FAQs, below) illustrate how interoperability can advance security, pseudonymization, catalog compatibility, and cross‑border health data exchange, helping build trust and resilience in sensitive domains. As geopolitical tensions and cyber threats grow, resilience measures, including business continuity, encryption, authentication, and active monitoring, become essential.

In 2026, interoperability is expected not only to enhance technical integration but to reinforce GDPR compliance, digital sovereignty, and citizen trust. This will position welfare systems to deliver more efficient, equitable, and sustainable social protection across Europe.

Conclusion and recommendations – 2026: a year of precision

Welfare agencies are moving from the rapid, crisis‑driven changes of the pandemic years to a more thoughtful approach to digital transformation. Governments now face aging populations, tight budgets, and greater global uncertainty. This is pushing them to design welfare programs that are more focused, data‑driven, and responsive to people’s real needs.

This shift is supported by four major trends: using cloud services more carefully and securely, replacing outdated legacy systems, applying AI in a responsible and transparent way, and improving data sharing between institutions. Together, these changes allow welfare agencies to work more proactively, offer more personal support, and react faster when people need help.

Even though each country starts from a different place, many are moving in the same direction towards welfare systems that are more digital, better connected, and better prepared to support citizens fairly and effectively.

Five recommendations for welfare agencies in 2026

To turn these trends into measurable impact, we recommend that welfare agencies focus on a small set of concrete priorities:

Adopt hybrid sovereignty strategies, balancing hyperscaler capabilities with strong local control over sensitive data
Accelerate legacy modernization, using modular architectures and AI‑supported engineering to reduce risk and cost
Scale AI responsibly, embedding explainability, human‑in‑the‑loop controls, and strong governance from the start
Invest in interoperability, adopting open standards and reusable components to support mobility and continuity of rights
Design around citizens, using data sharing and proactivity to simplify services and deliver support earlier and more fairly.

Agencies that act decisively on these priorities will be best positioned to deliver welfare systems that are resilient, trusted, and fit for the social and economic realities of the years ahead.

Authors

Gustaf has many years of experience selling, delivering, and leading business process and customer engagement solutions in a variety of industries, including banking and insurance Gustaf currently leads Pega globally and is the Augmented Services leader for Financial Services.

“I am privileged to support and guide public organizations in their pursuit of becoming exemplary citizen-centric service providers. By sharing and leveraging global developments and innovations, tailored to local and regional cultures and policies, I aim to enhance the citizen experience. In a world where data privacy, legislation, sovereignty, and trust are paramount, I am driven to identify actionable solutions and inspire our clients to drive positive CX transformations. My motivation lies in discovering new waves of innovation and applying them to end-to-end citizen journeys that truly matter, ultimately improving the interaction between citizens and government during significant life events.”

We envision a society where people can realize their potential, where equal opportunities prevail, and social security is easily accessible to everyone. By modernizing their applications and services, welfare organizations can improve citizens’ lives every day, and we are proud to contribute to that with our deep technology expertise and international experience of optimizing social security systems.

“As a Delivery Executive, I support social security organizations facing structural cost increases driven by longer life expectancy and the evolution of medical treatments. My focus is on a critical challenge: improving the efficiency of software application development and maintenance. I optimize information systems by promoting mutualization, experience sharing, and capitalization across organizations. I advocate for user-centric approaches, grounded in real usage and operational impact. Within this transformation, I continuously pursue a pragmatic path to leverage sovereign AI as a driver of efficiency, delivering tangible, measurable, and sustainable gains.”

“By aligning strategy, innovation, and operational transformation, we at Capgemini Invent enable organizations to modernize their practices and reinforce their resilience. Through the modernization of their applications and services, welfare organizations are able to enhance the citizen journey on a daily basis. Our ambition is to contribute — with rigor, expertise, and a clear sense of purpose — to sustainable transformations that deliver measurable improvements in the performance and overall experience of social security systems.”

“Welfare systems are being pushed to adapt faster than ever. Demographic shifts increased and more dynamic population movements and shifting labor markets are placing growing pressure on social security networks worldwide. While each country faces its own unique challenges, we believe looking at shared trends across borders and exchanging solutions can help Welfare Organizations strengthen their services, and ultimately better support the citizens who rely on them.”

“Senior Sales professional at Capgemini Spain, focused on designing and coordinating value‑driven proposals for Welfare Public Sector organizations, including Social Services, Housing, Employment and citizen‑centric programs. Along these years, I’ve gathered deep understanding of public‑sector processes with extensive experience managing strategic opportunities, aligning multidisciplinary teams, and ensuring the technical quality and robustness of solutions for both public- and private-sector clients.”