Governance just got cool again (and we’re into it)

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This week we’re quoting…

Dr. Kathrin Kind-Trueller (Data Scientist and AI expert)

What Kind-Trueller said: 

“As we stand on the shoulders of giants, looking into the future, the challenge lies not just in harnessing this power but in guiding it with wisdom, ensuring it serves not just the few but the many.” 

Weaving wisdom into governance 

These words come from our interview with Kind-Trueller a couple of years back, when she shared her excitement about the vast potential of generative AI. And we remembered them this week when we read KPMG’s new report on tech in Saudi Arabia – specifically, the parts of the report that talked about governance. 

Because governance has had an image problem for a while now – it tends to be treated as the least interesting part of technology. Innovation gets the headlines and founders become celebrities, while governance sits in the corner with a clipboard asking everyone to please just slow down a little bit. 

Now though, AI is beginning to change how people feel about it. As AI moves deeper into the foundations of organisations, governance is starting to feel more current and relevant; maybe even kind of cool. It’s becoming one of the defining conversations in enterprise technology.

Moving fast with governance 

That is partly what makes the new KPMG Saudi Arabia Tech Report 2026 so interesting. Beneath the big AI numbers and investment figures, the report points toward a structural change: the organisations moving fastest are often the ones building the strongest operational discipline underneath the surface.

• 93% of organisations surveyed said they centralise decisions around new technologies.
• 99% follow formal processes for evaluating emerging tools.
• 69% report optimised cybersecurity maturity (that’s significantly above global averages).
• 76% expect AI to be delivering ROI at scale within the next 12 months.

When you put them all together, these numbers challenge the idea that governance and speed inevitably work against each other. 

Instead, they can start enabling each other. 

Why scaling AI is harder than experimenting with it

Around the world, organisations are discovering that AI is relatively easy to experiment with but much harder to operationalise. Pilots are everywhere – but scaled deployment is not.

The obstacle here is whether organisations can integrate AI into complex systems without creating fragmentation, security risks, duplicated tools, compliance problems or internal confusion. The really difficult part is the coordination that has to happen around the tech. 

This is happening far beyond Saudi Arabia alone. McKinsey’s latest State of AI research found that organisations seeing the greatest impact from AI are more likely to redesign workflows and establish governance oversight from the beginning.

Governance becomes infrastructure

And governance is rapidly moving from an internal enterprise concern into a global operating reality: 

• The EU AI Act, which entered into force in 2024, is helping establish new international expectations around transparency, accountability and responsible AI deployment.
• Structures like the NIST AI risk management framework are gaining influence because they approach governance more as resilience than restriction. 

When systems become more interconnected, governance stops being about paperwork. It starts to offer real clarity over who owns decisions, how models are evaluated, how risks are monitored, how data moves through organisations, and how people maintain confidence in increasingly automated systems.

The KPMG report reflects that shift clearly. Saudi organisations report a high willingness to take bold technology risks (51%, well above the global average), but those risks are being taken inside highly structured operating models.

So as a global tech industry, we need to stop framing governance as something imposed externally by regulators and legal departments, and embrace it as a practice that’s native to innovation itself. 

The more powerful the systems become, the more valuable coordination becomes alongside creativity.

The next phase of AI

Maybe that’s why the report’s concerns aren’t primarily about whether AI works. Organisations are already looking further ahead, toward geopolitical tensions, governance gaps, biased data, resource scarcity and operational resilience – as AI scales deeper into enterprise life.

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