As we prepare for a pivotal 2026, we invited CEO Bert van der Zwan to reflect on the most defining lessons from the past year — and what they signal for transformation leaders navigating AI, modernization, and operating-model change.
This conversation distills the themes shaping boardroom agendas worldwide: the shift from experimentation to execution, the rise of AI-native operating models, and the expanding role of enterprise architecture in connecting strategy to outcomes.
We’re sharing this perspective with the Bizzdesign community to offer perspective on the trends that will define next year’s transformation agenda.
One of the biggest lessons is that experimentation alone doesn’t guarantee outcomes. The last two years brought a wave of pilot projects — from operating model redesigns to modernization efforts, cloud migrations, and yes, AI initiatives — but most organizations remain pilot-heavy and deployment-light, so the business impact hasn’t materialized. Without foundational readiness, even sizable investments delivered limited returns.
Enterprise leaders are entering 2026 with no shortage of ambition, but far less tolerance for drift. After several years of sustained investment in AI, cloud, data, and security, boards and executive teams are no longer debating whether transformation is possible. They are asking a more demanding question: can it deliver consistent, measurable value at scale?
In many organizations, that pressure is most visible in one area: AI. Pilots and proofs of concept are no longer sufficient to demonstrate progress. Leaders now expect evidence that experimentation can translate into scalable operational outcomes, and that the organization itself is designed to absorb innovation at the pace the business requires.
The questions leaders ask are no longer, “Can AI work?” or “Should we modernize?”
It’s now, “How do we make this deliver measurable value, and how do we do it without losing control?”
The shifts shaping 2026 reflect this reality. They mark a new moment for enterprise transformation — one where long-standing architectural, governance, and portfolio disciplines are no longer optional, but central to delivering outcomes at scale.
A clear divide is emerging between organizations that add AI onto existing ways of working and those that design AI into how the business actually runs.
FAQs
In 2026, enterprise architecture becomes a central enabler of transformation rather than a supporting function. As AI, distributed systems, and regulatory pressure increase complexity, the challenge for leaders is ensuring the organization can scale change without fragmenting or losing control. Enterprise architecture provides the coherence needed to align strategy, execution, data, and risk across the enterprise, enabling faster decision-making with confidence. Its role shifts from documentation to orchestration, helping organizations turn transformation from a series of initiatives into a repeatable, enterprise-wide capability.
Successful AI adoption depends less on deploying new tools and more on how AI is embedded into the enterprise. Enterprise architecture enables organizations to treat AI as an architectural design choice rather than a standalone solution by providing visibility into where AI creates value, how it interacts with existing systems and processes, and what dependencies or risks must be managed. By modeling AI alongside applications, data flows, and controls, enterprise architecture helps organizations avoid fragmented pilots and scale AI in a way that delivers measurable outcomes while remaining aligned with enterprise priorities.
To deliver consistent business value, AI must be designed into the architecture of the enterprise from the outset, embedded into workflows, systems, and governance structures. This means embedding AI into core workflows, modeling how intelligent agents interact with systems and data, and ensuring governance, security, and accountability are built in from the start. Enterprise architecture plays a critical role in making this possible, providing the visibility and structure needed to scale AI safely across functions and processes. In 2026, the organizations that succeed with AI will be those that architect it with coherence, not just speed.
In 2026, enterprise architecture evolves from a primarily descriptive discipline into an operational one, driven by the demands AI places on the enterprise. As AI introduces greater autonomy, speed, and interdependence across systems, leaders need real-time visibility into how decisions, data, and risks propagate through the organization. Enterprise architecture responds by becoming more dynamic and contextual, modeling AI agents, intelligent workflows, and their dependencies alongside traditional systems and processes. This shift allows organizations to embed governance, security, and accountability into design choices from the outset, enabling AI to scale safely while keeping strategy, execution, and risk aligned.
In 2026, regulations such as the EU AI Act will increasingly shape how AI systems are designed, extending governance into architectural and operational decisions from the start. Requirements around risk classification, transparency, and accountability mean that compliance can no longer be treated as a downstream activity. Organizations will need to embed governance, traceability, and oversight directly into their architectures and operating models. When this is done well, regulation becomes a catalyst for maturity, giving leaders the confidence to scale AI responsibly rather than slowing innovation.
In 2026, executives should prioritize the foundations that make transformation scalable and sustainable, including enterprise-wide design choices that determine how technology delivers value. That means investing in real-time visibility, governed data, embedded security, and a shared understanding of how value flows through the organization. By designing operating models that support autonomy without losing control, embedding AI and security into architectural design choices, and treating data quality as a strategic asset, leaders can ensure that innovation flows through the enterprise in a consistent, governed way. When strategy, execution, and governance are aligned, transformation moves faster — with greater confidence and impact.
When it comes to digital transformation, progress is still a steep climb for many. Recent studies show that 88% of transformation fall short of their ambitions while only a quarter of organizations qualify their efforts as truly successful. [1]
But after decades of investment, why is real impact still so rare? The answer lies in a persistent gap between strategy and execution. McKinsey research indicates that even high-performing companies deliver around 30% less value than their strategies promise. [2]
When there's a disconnect between strategy and execution, it often stems from lacking a unified view of the organization, leading to fragmented decisions and lost value.
Bizzdesign, a leading enterprise transformation SaaS company, today announced that it has been named a Leader in the 2025 Gartner® Magic Quadrant™ for Enterprise Architecture Tools. This is the eighteenth consecutive year that Bizzdesign has been placed in the Leaders quadrant.
About Bizzdesign
Bizzdesign is a global enterprise transformation SaaS company. Through the merger of three industry leaders, Bizzdesign, MEGA International, and Alfabet, the company offers a comprehensive enterprise transformation suite that helps organizations navigate the complexity of digital business. With a data-driven and AI-powered approach, it accelerates transformation, from vision to value, by empowering teams to collaboratively plan, design, and govern change.
