Enterprise Architecture in 2026: From a Vision to Resilient Operations

Enterprise architecture does not often make headlines. But it should. Over the past months, we talked to enterprise architects, CIOs and technology leaders across Europe – the companies they represent ranging from financial services to Government, Energy to Consumer – to understand how they are navigating one of the most complex transformation periods in IT history.

What emerged in the Enterprise Architecture study was not a surprise. It was a validation of what works and a clear signal about where the real leverage points are.

“We’ve had the privilege of working directly with the architects who are in the trenches. These were not theoretical discussions as we talked to practitioners who’ve lived through failed modernisations, budget constraints and the pressure to deliver faster. Their insights are gold” Ville Laitinen, Manager at Deloitte says.

The study, conducted across 14 European countries, reveals a landscape where transformation is no longer optional. It is about getting and staying change ready. The path forward is clearer than many organisations realise.

The ERP paradox: Simplicity as a competitive advantage

What proved least surprising, yet most consequential, was that ERP transformation sits at the core of every major initiative. Seventy-two per cent of the studies organisations have listed application modernisation or ERP transformation as a top priority. But therein lies the fundamental issue and where most organisations stumble. Companies have experience of complex, multi-system ERP setups. They have learned, often painfully, that complexity does not equal capability. The organisations winning today are those simplifying their ERP landscapes while maintaining business agility.

The data tells a consistent story across sectors. Organisations that have moved to modern, streamlined ERP architectures – whether SAP S/4HANA, or Microsoft Dynamics – are outpacing their peers. But the journey is not about rip and replace. It’s about sequenced, phased simplification,” Timo Salo, Senior Specialist Lead at Deloitte Nordic, explains.

This is where real value emerges. Rather than treating ERP as a technology project, leading organisations are treating it as a business transformation lever – one that simultaneously addresses

• Risk and compliance (the #1 driver across all sectors)

• Cost optimisation (structural OpEx reduction, not just headcount cuts)

• Operational agility (the ability to respond to regulatory shifts and market changes)

• Data and AI readiness (ERP as the backbone for governed data and intelligent operations)
  
  

The implication for organisations planning major initiatives in the next 1–3 years is clear: ERP transformation is not a checkbox. It is the foundation. Getting it right, with the right partner who understands both the technical and business dimensions, determines whether your other transformation bets (AI, data, cloud bets) succeed or stall.

AI governance: The difference between pilots and scale

Here is a statistic that deserves attention: 42% of the studied companies are already using ERP AI capabilities. This figure reflects not experimental deployment but established mainstream practice. It signals something critical: the AI race is now an efficiency competition.

However, the study reveals the core challenge. While AI adoption is accelerating, governance is lagging. Organisations are deploying AI in pockets, in ERP systems, in analytics, in customer-facing applications, but without the centralised governance, risk frameworks and lifecycle management that are needed to scale.

“AI and GenAI are moving centre stage, but they must be industrialised and governed. With the highest priority overall, AI and GenAI are expected to change how decisions, interactions and operations work, but only if governance, risk, compliance and life cycle are addressed,” Laitinen says.

The survey data backs this up:

• 77% of studied organisations list AI and GenAI in their Top 4 priorities

• Only 37% of the studied financial services organisations expect to reach standardisation and compliance with regulations in three years

• 83% respondents prefer internal training as their primary way to build AI expertise, yet most lack the structured programmes to do this at scale

Organisations that move first on AI governance – establishing clear ownership, risk frameworks and life cycle management – will pull ahead. Those that continue deploying AI in isolated projects will face escalating technical debt, compliance risk and wasted investment.

Data: The non-negotiable foundation

If ERP is the backbone and AI is the competitive edge, data is the nervous system.It can be argued that, in most organisations, the data is broken.

“Data Management is a Top 3 priority because AI, reporting, compliance, CX optimisation all depend on reliable, shared and governed data across functions and entities. Yet most organisations are still managing data in silos,” Salo notes.

The study shows the following:

• The consumer sector allocates 33% of IT budget with equal emphasis on ERP (17%) and AI and data management (16%)
• The energy, resources and industrial sector 80% of respondents identifies internal training as the primary method for acquiring data expertise

• Over 60% of organisations plan to increase their use of modern data platforms (Snowflake, Databricks, Power BI)

• In three years, the respondents aim for higher coverage across all data governance dimensions, especially data quality control

The mandate is explicit: data governance admits no deferral. Organisations that treat data governance as supplementary to AI and modernisation initiatives will be fundamentally unable to

• meet regulatory requirements (GDPR, the AI Act, sector-specific mandates)

• leverage AI effectively (garbage in, garbage out)

• optimise customer experience (no single view of the customer)

• respond to market changes (no real-time visibility of operations).
  
  

The organisations we spoke with understand this. They are not treating data as a separate workstream. They are embracing data as the connective tissue embedding data governance into every transformation initiative: ERP, AI, cloud and modernisation initiatives.

The transformation imperative: It is not optional

What unites these three elements is a critical reality: transformation has transitioned from being discretionary to being mandatory. The imperative is to ensure the organisation remains positioned to respond to dynamic business demands. This does not refer to "modernisation for modernisation’s sake" programmes, but how organisations stay resilient in the face of:

• regulatory shifts (AI Act, ESG mandates, sector-specific compliance)

• market shocks (economic downturns, competitive disruption, talent scarcity)

• new business models (digital-first customer engagement, platform ecosystems, data monetisation).
  
  

The organisations that will thrive in the next three years are those that:

• simplify their ERP landscape while maintaining business agility, treating it as a business transformation, not a technology project
• establish AI governance before scaling AI adoption, moving from pilots to industrialised, compliant operations
• invest in data foundations as the prerequisite for everything else, not as an afterthought.