Beyond the 'Department of No': Why Data Governance Is Becoming AI's Greatest Enabler

Corinium's Kashmira George spoke with Melecio Valerio, Head of Data Governance and Group Technology at Maya, to uncover why governance is no longer a barrier to innovation but the key to unlocking trusted AI and lasting business value.

Speaking ahead of his session at CDAO Philippines (27th October 2026), Valerio emphasises that governance should no longer be viewed as a compliance function or an obstacle to innovation.

Instead, it should become the foundation that allows organisations to innovate faster, scale responsibly and realise measurable business value.

What purpose has data governance taken in 2026?

Historically, data governance has been associated with policies, compliance and risk mitigation. It existed to ensure organisations stayed within the rules. That purpose has changed.

As organisations increasingly rely on AI, governance is becoming less about preventing mistakes and more about creating confidence.

"The shift is really moving from governed data because we need control to governed data because we want to unlock value," Valerio explains.

Without trusted, well-managed data, even the most sophisticated AI models struggle to deliver meaningful outcomes. In that sense, governance has become an innovation strategy rather than simply a compliance exercise.

It's time to retire the 'Department of No'

One of the biggest misconceptions surrounding governance is that it slows projects down.

For years, governance teams have earned the reputation of being the final checkpoint that delays deployment and introduces additional bureaucracy. Valerio believes that mindset must disappear.

Instead, he believes that good governance creates confidence in compliance.

Rather than sitting outside projects as an approval gate, governance should be embedded directly into how organisations build, manage and consume data.

When governance is integrated into workflows through automated data quality checks, metadata management, lineage tracking and responsible AI assessments, innovation becomes both safer and faster.

Governance by design, not governance at the end.

Embedding governance early is one of the strongest themes emerging from today's AI landscape.

Traditional governance often happens at the end of a project, just before deployment. By then, identifying issues becomes expensive and delays become inevitable.

Valerio advocates a different approach.

"Governance becomes a catalyst when it is embedded into how organisations build and consume data and AI rather than being a separate approval layer."

This "governance by design" philosophy allows organisations to build guardrails directly into AI development rather than adding them afterwards.

The result is fewer bottlenecks, greater transparency and significantly more confidence when AI systems move into production.

Culture matters more than technology.

Technology alone cannot create a data-driven organisation. While companies often focus on governance platforms and frameworks, Valerio believes the real differentiator is organisational culture.

"You may have the best tools, the best frameworks and policies, but if people do not see data as a shared responsibility, governance will always remain theoretical."

Creating a culture where data is treated as a shared enterprise asset requires leadership commitment.

As Valerio notes:

"Data governance is not just a data initiative. It should always be treated as an organisational transformation."

Business leaders play a critical role by setting expectations that strategic decisions should be based on trusted data while encouraging accountability across every department.

One of the most practical messages from the discussion is that governance initiatives should never exist in isolation. Too often, organisations launch governance programmes because regulations require them or because governance is viewed as a standalone objective.

If governance cannot demonstrate measurable business outcomes, organisations will struggle to gain executive support or sustained adoption. Instead, governance should directly enable faster decision-making, trusted AI, operational efficiency and better customer experiences.

Building an AI-ready governance framework.

As AI adoption accelerates, organisations need governance models designed specifically for intelligent systems.

According to Valerio, every AI-ready governance framework should begin with a strong data foundation because:

"AI quality is directly influenced by data quality."

From there, organisations should establish the following:

• Clear ownership and accountability
• Trusted and governed data assets
• Strong data quality and lineage
• AI risk classification
• Responsible AI principles such as fairness, explainability and accountability
• Continuous monitoring throughout the AI lifecycle

Importantly, these controls should not introduce unnecessary bureaucracy.

"AI governance definitely should not become another layer of bureaucracy. It should enable teams to innovate responsibly and ethically."

Trust will define the next generation of AI.

Looking ahead, Valerio believes governance will become increasingly automated and embedded directly into enterprise platforms.

Rather than relying on manual reviews, organisations will use AI itself to improve governance through automated monitoring, quality tracking and risk detection.

More importantly, governance will evolve into a competitive advantage.

"The future of governance will not only be about controlling risk. It will be about creating the trust foundation that allows organisations to confidently scale AI."

For organisations operating in highly regulated industries, particularly financial services in the Philippines, this evolution is already underway. Many businesses are implementing governance frameworks even before regulations are finalised, recognising that responsible AI adoption cannot wait for legislation.

Governance and innovation are no longer opposites.

If there is one takeaway from the conversation, it is that governance and innovation should never be viewed as competing priorities.

Valerio believes the organisations that will lead the next wave of AI adoption are those that recognise governance as the very thing that enables innovation to flourish.

"The future is not about choosing between governance and innovation. The organisations that win will be the ones that use governance as the foundation to allow innovation at scale."

As AI continues to reshape industries, organisations face a choice. They can treat governance as a barrier that slows progress, or they can embrace it as the framework that builds trust, unlocks value and enables AI to scale with confidence.

For today's data leaders, that distinction may prove to be the difference between simply adopting AI and truly transforming the business.

If you are interested in speaking at our CDAO and CDAIO series in ASEAN, reach out to Kashmira George for more information. 

Ready to build an AI-ready organisation? Join us at CDAO Philippines on 27 October 2026 to hear from Melecio Valerio and an exceptional lineup of data leaders as they explore the governance, leadership and innovation strategies driving the future of enterprise AI.