Scaling Innovation Requires Letting Go

Three months into my role as Chief Strategy Officer at CMBYND, I’ve had the privilege of speaking with decision-makers across banking, insurance, and asset management, leaders tasked with transforming how their institutions operate, deliver, and grow.

One thing is clear: the ambition is there. Institutions are looking to transform how they operate and deliver value, with artificial intelligence emerging as one of the most promising enablers. Whether it’s accelerating insight, anticipating risk, automating manual effort, or elevating both the client and employee experience, AI is becoming central to the next generation of transformation.

But alongside that ambition is a recurring barrier: legacy complexity continues to weigh down execution and the ability to scale.

Disconnected platforms, duplicated data, and fragmented processes, all layered on infrastructure that reflects decades of decisions, not today’s priorities. Many business units still rely on manual workarounds and compensating controls, not by choice, but by necessity.

Legacy complexity weighs down transformation execution.

A few hard truths:

• Maintaining legacy systems consumes 60–80% of IT budgets, leaving little headroom for innovation

• Adding new platforms without retiring legacy increases cost and complexity

• AI requires clean, accessible, and timely data, nearly impossible to provide in fragmented environments

• Many successful AI initiatives only scale after simplification

That’s why I believe the next wave of transformation won’t be driven by AI alone, it will be led by organizations that pursue simplification and innovation in parallel.

Simplification may not grab headlines, but it’s the necessary multiplier.

It’s not easy, but it’s vital: consolidating applications, standardising platforms, embedding reusable controls, simplifying workflows, and moving to cloud-native architectures. These actions unlock data, improve agility, reduce total cost of ownership, and, critically, create the operating leverage required to scale innovation.

The institutions making the greatest progress are those treating simplification and AI as two halves of the same strategy. Not either-or. Not sequential. But interdependent.

What makes this moment different is that the path forward is clearer than ever. The tools exist. The capabilities exist. And increasingly, so does the will to reimagine what’s possible.

For firms willing to rationalise what they have while innovating toward what they need, the return isn’t just operational efficiency.

It’s strategic empowerment.

And it starts with courageous decisions, about what to retire, what to invest in, and how to lead through both.

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