In her latest column, Charlotte McEleny looks at the APAC market, and why data accumulation is all for nothing if it’s not backed by sophisticated strategy…

Nearly two-thirds of APAC enterprises say they are prioritising data strategies to prepare for AI, according to research from Digital Realty’s The State of Data and AI in Asia Pacific report. The problem, according to practitioners working across the region, is that most businesses mistake more data for a plan.

“Most companies mistake data accumulation for data strategy,” says Terrence Quah, general manager of Dentsu X Singapore & Merkle Singapore.

It is a diagnosis that cuts across sectors and markets, and one that Isabella Spragg, independent advisor on data, retail media and AI strategy, echoes from a different angle. In her view, the failure begins before a single data point is collected. “Many companies approach first-party data as a technology project rather than a business strategy,” she says. “Significant investment is often made in platforms, warehouses and customer data technologies without first defining the business outcomes they are trying to achieve.”

The result, in both cases, is the same: a sophisticated infrastructure that cannot deliver for marketers.

The identity problem

For Quah, the most critical missing piece is unified identity resolution. Without it, even large volumes of customer data remain inert.

“Instead of building a centralised data foundation, businesses deploy disjointed, platform-specific tools,” he says. “This creates disconnected data silos, leaving organisations with vast amounts of information that cannot be activated for real-time personalisation.”

“If your data foundation is broken, your expensive AI stack becomes completely inert, killing your return on technology investment,”

The consequences extend beyond missed personalisation opportunities. As AI planning and automation tools demand clean, unified, real-time data inputs to function, poorly connected data foundations directly constrain technology ROI. 

“If your data foundation is broken, your expensive AI stack becomes completely inert, killing your return on technology investment,” Quah adds.

Sector maturity varies significantly across the region. Banking, financial services and insurance have led on infrastructure readiness, driven by regulatory pressure and high-volume customer touchpoints, while CPG and traditional retail, by contrast, remain fragmented, still trying to bridge legacy offline data with digital engagement platforms.

The governance gap

Spragg locates a second, equally damaging failure in governance. Businesses that have invested heavily in data infrastructure frequently find that poor data quality, unclear ownership, and inconsistent consent management limit what they can actually do with it.

“First-party data foundations are only as strong as the discipline behind them,” she says. “Without clear governance and accountability, even the most advanced technology stack will struggle to deliver consistent value.”

She also points to a maturing attitude toward regulation that, while encouraging, remains uneven. Larger enterprises in financial services and telecoms tend to have stronger compliance frameworks and dedicated resources. Many mid-market and smaller businesses are still finding their footing as requirements continue to change. The more significant development, Spragg argues, is a reframing of privacy from legal obligation to commercial asset.

“Brands are certainly recognising that customer trust is becoming a competitive advantage,” she says. “The businesses that are future-proofing are certainly those continuing to embed privacy, consent and governance into their operating models rather than treating them as standalone legal or compliance requirements.”

Where to start

Both Quah and Spragg converge on the same starting point: define the outcome before you touch the technology.

“Map your data collection directly to clear business outcomes,” Quah says. “Before buying another shiny activation tool, audit your existing stack and focus on making your data unified, accessible, and scalable.”

Spragg goes further, placing people alongside process as a reset priority. “Make sure your people understand how to use the data, its source, who is accountable for changes and upgrades,” she says. “Make your people central to the reset.”

With 72% of APAC businesses now aligning their data strategies with AI plans, according to the same Digital Realty report, the pressure to get foundations right is only increasing. The businesses that invested in clean, connected, governed data before AI became the priority are already seeing the returns.

As Spragg puts it: “Strong foundations may not be the most exciting part of the journey, but they are almost always what separates successful data strategies from expensive experiments.”

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