Stop Innovating, Start Building Sustainably: Why Foundations Matter More Than Additions

Organisations love to talk about innovation. In education, healthcare, and the public sector, new initiatives are often framed as the next big step forward: a new program, a new tool, a new “floor” added to the existing building. The logic seems simple: if one floor is good, more floors must be better.
But buildings are not infinite. If the foundation is fragile, adding another floor will not make the structure stronger. It will expose the cracks and place the entire building at risk. The same applies to organisations. When institutions embrace new initiatives without strengthening their core, they risk amplifying weaknesses rather than building resilience.
Artificial intelligence (AI) provides a current illustration of this dynamic. Institutions are eager to add AI tools and systems, sometimes with great urgency. But if the foundation of an institution is not solid, AI will not enrich. It will destabilise. AI is not the problem here; it is simply the latest example of how innovation, when treated as addition rather than transformation, can undermine rather than strengthen.
What if instead of innovating by adding more, institutions would focus on sustainable change: reinforcing the foundation, deepening what works, and only then enrich this with new elements such as AI or any other novel development.

The pitfall of innovation-as-addition

“Innovation” has become one of the most overused words in organisational life. We innovate in education, innovate in healthcare, innovate in the way we govern and manage. Innovation is almost always framed as something new, something that adds to what already exists.
The problem with this mindset is that it often skips over the hard work of alignment. Adding something new can make an institution look modern or forward-thinking on the surface, but without re-examining whether the new element fits the foundation, the result is fragile.
History gives us many examples. In education, the early 2010s saw the introduction of tablets and digital platforms. They were often added with the promise of transformation. Yet teachers were unprepared, pedagogical visions were underdeveloped, and practices were not adapted. The technology became a burden rather than a support.
AI today is repeating the pattern. Institutions are rushing to install chatbots, predictive analytics, and automated grading. But if the fundamental questions like: What do we see as learning? How do we define equity? What role should human relationships play? remain unanswered, AI will not solve problems. It will magnify them. The lesson is clear: innovation understood as mere addition can destabilise. We need another way.

Foundations first: the questions we neglect

If we are to stop innovating superficially, we must start with the foundation. For institutions, this means returning to first principles:

What is our purpose?
What values do we want to enact?
What kind of relationships do we want to cultivate (with students, patients, or citizens)?

These may sound like abstract questions, but in practice they are deeply concrete. A school that defines learning as relational and formative will approach new tools very differently from a school that defines learning as measurable outcomes. A healthcare institution that values holistic well-being will interpret technology differently from one that values throughput and efficiency above all else.
If institutions neglect these questions, every new innovation is built on sand. The foundation will not carry the weight.

The three layers of sustainable change

To think differently about change, I propose a model of three interconnected layers: Base, Deepen, and Enrich.

The base layer (foundation)
The base layer defines the identity of the organisation. It is where institutions articulate their “view on the world”: what they stand for, why they exist, and what commitments guide their daily work. In a school, this may involve clarifying what learning means and what role teachers and students should play. In healthcare, it might mean redefining health not just as treatment, but as well-being. Without a shared and enacted foundation, every new initiative risks becoming cosmetic.
The deepening layer (strengthening what works)
Once the base is secure, institutions can focus on strengthening and improving what already exists. This layer is about quality and coherence. In schools, this could involve investing in professional development, fostering collaboration among teachers, or aligning curricula. In healthcare, it might mean improving continuity of care or reducing bureaucratic burdens.
Deepening ensures that the foundation is not only strong but alive, responsive, and resilient.
The enrichment layer (adding new elements)
Only when the base and deepening are in place does it make sense to add enrichment: new tools, methods, or perspectives. This is where innovations such as AI belong. At this stage, enrichment can genuinely extend and amplify what is already strong because it fits seamlessly with the base and the deepening.
Enrichment is not the first step. It is the last.

Illustration: AI as a test case

Artificial intelligence is a useful case to illustrate the three layers. Especially because AI does not always belong to the enrichment layer, while in the experience of many it is being treated like this. In some organisations, AI may indeed function as enrichment: a supportive tool that amplifies what is already strong. For others, engaging with AI exposes the cracks in the foundation of the organisation and reveals the need to revisit the foundation itself.
If a university concludes that preparing students for a world shaped by AI is part of its very mission, and wants them to make use of AI as a supportive tool, then this becomes a foundational element. It shapes not only what students learn but also how the institution defines its role in society. Similarly, a healthcare institution might decide that responsible use of AI is part of its ethical base, woven into its definition of good care.
In yet other cases, AI belongs to the deepening layer, helping to strengthen existing practices: say, by reducing administrative tasks so that professionals can focus on their core work.
The key insight is that AI (or any new development) does not have a fixed place in the model. Its position depends entirely on how it relates to the foundation. What matters is not whether an institution uses AI, but whether its use fits coherently within base, deepening, and enrichment.

Beyond AI: other lessons from innovation

Although AI is today’s most visible case, the principle extends far beyond. Consider other “innovations”:

Blended learning in education: when aligned with a clear pedagogical vision, it can deepen learning; when added superficially, it can create confusion.
Lean management in healthcare: when grounded in a culture of collaboration, it can reduce waste and improve patient experience; when imposed without trust, it can reduce care to metrics.
Community engagement in local government: when connected to genuine values of participation, it can strengthen democracy; when treated as a checkbox, it erodes trust.
In each case, the question is not whether the innovation is promising, but whether the foundation is ready.

To illustrate, consider two schools facing a decision about new technology.
School A introduced AI-based tools rapidly, hoping to save teachers time and modernise. No shared understanding existed of what learning meant for them. Teachers worried about plagiarism, students were confused, parents distrusted the process. Innovation increased fragility.

School B began with dialogue. Teachers, students, and parents reflected together: What do we believe learning is? What skills and values do we want our students to embody? From this base, they strengthened practices of feedback and assessment. Only then did they explore AI tools that aligned with their vision. The result was trust, coherence, and real enrichment.
The lesson is not about AI alone. It is about the order of change: base, deepen, enrich.

Rethinking institutional change

What, then, should institutions do when confronted with the pressure to innovate? A few guiding principles emerge:

Foundations before additions: Ask first what values and commitments define the organisation.
Deepening before novelty: Strengthen what works with proven methods before experimenting.
Enrichment only when ready: Adopt new elements such as AI only when they fit seamlessly with the foundation and deepening.

This reframing shifts the conversation. Instead of “How can we innovate with AI?” the question becomes: “How can AI serve our values once our foundation and practices are strong?” Or perhaps: “Does AI belong in our very foundation?”

Institutions are under pressure to innovate. But if innovation means adding new floors to fragile buildings, we risk collapse rather than progress. The real task is not innovation as addition, but change as sustainability. By first reinforcing the foundation, then deepening what works, and only then enriching with new elements, organisations can ensure that novelties such as AI do not destabilise but truly add value.
The building metaphor reminds us: a structure on sand cannot carry skyscrapers. But with strong foundations, the possibilities are limitless.
It is time to stop innovating for innovation’s sake and start building sustainably.

Written for OEB 2025 by Frank van den Ende.

Join Frank for his Presentation “Stop Innovating, Start Working on Meaningful Change” at OEB25.

Join Frank at #OEB2025!