What are the priorities for Enterprise architects in Europe in 2026?

In Summary

Legacy is now a structural risk and a cost issue, not just a “technology debt.” The high scores on Application Modernisation and ERP transformations show that ageing cores are perceived as a business continuity, risk and cost issue, and not just as an IT concern. They become a visible brake on the resilience, security and agility of the business. 

Data is the foundation of all other transformations. Data management is a top 3 priority because AI, reporting, regulatory compliance, customer experience, and operations optimisation depend on data that is trusted, shared, and governed across functions and entities. Without a solid data foundation, AI, modernisation and transformation programmes remain limited in their impact. 

AI and generative AI are coming to the forefront but need to be industrialised and governed. With the highest level of priority, AI and GenAI are set to transform decision-making, interactions, and operations. This value creation will only be possible if organisations fully address the challenges of governance, risk management, compliance and control of the life cycle of models and uses. 

The cloud is the “execution fabric” of transformations. Cloud Adoption plays a cross-functional role by supporting ERP, data, AI transformations and modernisation programmes, providing scalability, resilience and standard services. Hybrid and sovereign models make it possible to manage the issues of sovereignty, data protection and regulatory compliance. 

ERP remains the backbone of process and financial control. The strong focus on ERP transformations, especially in the energy sector, confirms that organisations continue to rely on modern ERP cores for process standardisation, compliance and cost control, whilst surrounding them with platforms, APIs and AI capabilities. 

The real goal is simplification, speed and resilience. Across all themes, the main drivers of transformation are reducing IT complexity, improving efficiency and agility, lowering operational and IT costs, strengthening resilience and cybersecurity, and reducing time-to-market. 

Transformation is no longer optional: it aims to make business “change-ready”. These programmes are no longer part of a modernisation “for the sake of modernisation”; they are the way for organisations to stay ready for regulatory changes, market shocks and new business models. The ability to absorb and take advantage of change becomes a central competitive advantage. 

The study focuses on several key dimensions, including key technology trends and transformation challenges, current or upcoming IT/IS transformation programmes, the value they aim to generate, as well as the expected evolution of information systems landscapes over the next three years. 

The study highlights a cross-cutting vision of the priorities that now structure roadmaps: AI and GenAI, Data Management, ERP, Cloud, Modernisation, Platforms, Microservices/APIs and Agility. 

The primary goal is to understand how architecture and technology functions are organised, governed, and equipped with the capabilities to meet the demands of an increasingly complex and ever-changing environment. This includes integrating architecture into strategic decision-making processes, adopting modern delivery models and practices, and aligning technology investments with business outcomes and objectives.

Enterprise Architecture in 2026: Simplifying, Securing and Accelerating Business 

Regardless of the sector of activity, five priorities keep coming up. These are not five separate programmes, but five structural levers that make it possible to meet the same requirement: to do more, faster, with fewer risks and fewer inherited burdens. 

Organisations respond to a limited number of recurring drivers of transformation. The challenge is not to activate all the levers, but to align each investment with the need it best meets: 

✔ Application and ERP modernisation to control operational costs, simplify the IS and reduce risks. 

✔ Artificial intelligence, generative AI and data for efficiency, agility, innovation and resilience; 

✔ The cloud for scalability, flexibility, resiliency, and reduced complexity; 

Discover the specificities of each industry: 
 

• Financial services: how to manage the explosive cocktail of legacy, regulation and high intensity of internal development? 

• Energy and Industrial: How to Modernise ERP, Data, and Applications Without Destabilising Critical Operations 

• Public sector: how to reconcile security, budgetary constraints and digitalisation of services? 

• Consumption: how to make data, platforms and AI the engine of omnichannel? 

What you need to remember 

Use application modernisation to sustainably reduce operational costs and IT complexity. 

Application modernisation is one of the most effective levers for reducing IT complexity and operational expenses. Chief Architects’ efforts should prioritise applications that generate complex integration issues and high operating costs. It is recommended that you use standardised approaches such as rehost, replatform, refactor, or replace, rather than application-specific policies. 

Make ERP the main lever for risk control, compliance and business cost control. 

ERP programmes make a significant contribution to reducing regulatory and operational risks, building resilience, and optimising costs. They should be used to harmonise financial, logistical, and operational processes, streamline local variants, and embed control mechanisms directly within processes, where regulators and auditors focus their attention. 

Design new business processes as integrated initiatives combining AI, Data, and ERP. 

AI, Data, and ERP all score high when it comes to creating new business processes. When redesigning a process (claims management, collections, maintenance, onboarding, etc.), it is essential to simultaneously design business processes, data flows, ERP evolutions, and analytical or AI capabilities, rather than letting each team work independently. 

Entrust scalability to platforms and the cloud rather than over-provisioning ERP or AI solutions. 

Given the central role of the Cloud in managing scalability and flexibility, it is important to avoid overly complicating ERP or AI architectures to meet scalability needs. Cloud platforms, API-driven architectures, developer platforms, and managed services should be the scaling layer, whilst ERP and AI remain focused on business processes and business intelligence. 

Deploy AI and generative AI where they allow for a change in scale, not just incremental gains. 

AI is the lever most strongly associated with improving efficiency and agility. It should be prioritised on areas that rely heavily on manual decisions (risk management, operations, customer experience), where automation and decision support can significantly transform costs and lead times, rather than being limited to marginal optimisations. 

Position the cloud first as a lever for scalability and resilience, before making it a lever for cost reduction. 

The cloud is the primary driver of scalability and flexibility, whilst contributing to resilient and simplifying systems. Cloud migrations should prioritise workloads that require elasticity, global coverage, disaster recovery plans, and standardised services. Cost savings should be seen as a secondary, long-term benefit. 

Sequence investments: simplifying first, industrialising AI second. 

Application modernisation and ERP transformation programmes primarily reduce complexity and operational costs, whilst AI and the cloud drive efficiency and scale-up. Major initiatives must therefore be planned sequentially, with a focus on simplifying and streamlining the IS before the massive deployment of AI solutions, in order to avoid amplifying existing dysfunctions. 

Think of data management as the co-pilot of AI, not a separate work site. 

Data management is a major contributor to improving efficiency, reducing complexity, and creating new processes. Any major AI initiative should be conditional on the existence of a clear data governance plan covering sources, quality, responsibilities and management rules. Without this foundation, organisations risk multiplying Proofs of Concept (PoCs) without generating value at scale.