Democratising data with AI: In conversation with Amperity’s Billy Loizou

Even the great fictional detective Sherlock Holmes understands the importance of data, stating, “It is a capital mistake to theorise before one has data.”

In the world of AI agents enabling stronger data stitching and identity resolution, why is data democratisation across organisations still lagging?

At the 2025 CDAO conference in Sydney, Billy Loizou, Area Vice President, APAC at Amperity and a recognised thought leader in the marketing and technology space, shared powerful insights on how brands can truly democratise data by harnessing AI, without losing the magic of human thinking.

Not all teams require all data, yet accessibility issues remain

Data is currency as some would say, but for many organisations, it remains frustratingly out of reach for the people who need it most.

“The biggest challenge is that business users often don’t have access to the data,” addresses Loizou. 

“And even when they do, data literacy within departments can be low.” 

The problem isn’t only about data availability, it’s about usability. Teams need information in a format that’s both accessible and easy to understand for effective decision-making. 

To solve this, companies like Amperity are thinking beyond centralised dashboards and moving towards hyper-tailored data environments. 

“We don’t just build a view of the customer,” says Loizou. “We build it specifically for each team.” 

In practice, that means marketing teams receive a different set of data points than customer service teams. While marketing may focus on personalisation attributes – browsing behaviour or category interests – customer service teams might need last purchase dates, satisfaction scores or case histories to resolve issues faster.

This approach supports real-time, role-specific decision-making while also mitigating risk. 

“Not everyone needs access to all the PII…just the relevant attributes that help them do their jobs better.”

AI as the great enabler of data democratisation

When it comes to customer data, AI can really take the painful and tedious work out of data engineering. For Amperity, AI is deeply embedded into how users interact with data, regardless of technical skill level.

There are two main ways this plays out.

First, for more technical users: “If I’m writing SQL, we have an AI assistant that helps generate that code,” Loizou says.

“It’s simple, helpful and really speeds up the value track.”

But where things get really interesting is for the non-technical users like the marketers, CX leads or analysts who aren’t fluent in SQL. 

“We’ve built a capability that understands your data’s relationships and allows you to ask natural language questions,” he says. 

It’s as intuitive as asking, “How many customers purchased in the last 30 days?” or “Which of them are high value, and how do they compare to others?”

Behind the scenes, AI interprets these questions, runs the necessary queries, visualises the data, and enables segmentation all in one flow. 

“It removes the data literacy barrier, which is still a real issue in ANZ,” says Loizou. 

And for customers, this capability unlocks the kind of deeply personalised experiences that make them feel recognised and understood.

Let's not give AI all the credit

With all the power AI offers, there’s a growing temptation to rely on it for everything. But Loizou cautions against over-automation, especially in areas that require emotional intelligence or lateral thinking.

“I’ve been playing with AI for years,” he says, “and the more I engage with it, the more human it starts to feel. But it still doesn’t think laterally the way a human does.”

In other words, AI is a phenomenal enabler of operational efficiency, but it’s not a replacement for human insight. 

“The expression, the creativity, the execution of what you identify, that still needs a human,” Loizou explains. 

While AI can analyse and surface patterns, humans are capable at contextualising meaning, understanding nuance and aligning data with broader brand narratives.

Loizou also raises important considerations around AI governance, especially when AI does hiccup on the odd occasion. Without human oversight, the risks to brand reputation and customer trust become significant. 

“We’re seeing things like bias and hallucinations emerge more often in enterprise environments,” he warns. 

“Companies need to be careful how much control they give AI.”

True customer centricity is humans and AI working in tandem

The organisations that will thrive in the AI era are those that strike the right balance between empowering teams with access to data, simplifying the user experience with AI and preserving the creative intuition only humans can bring.

Loizou’s perspective reflects a maturing industry mindset; one where personalisation doesn’t just come from data or algorithms, but from understanding people at a deeper level. 

“Hopefully all of this translates into more personalised experiences where customers feel genuinely known by the brand,” he says.

That’s the future of customer experience. Not one ruled entirely by automation, but one enhanced by it and anchored in human insight, powered by intelligent tools, and accessible to every team across the business.

Authored by Jessica Phillips, Senior Social Media and Communications Specialist at AZK Media.

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