As customer demands for personalisation grow, marketers face mounting pressure to deliver, yet siloed data and privacy concerns are stalling progress. Now, brands are investing in smarter data strategies to unlock AI’s full potential and drive meaningful engagement at scale.
In a study by Adobe today released its 2025 AI and Digital Trends Australia and New Zealand (ANZ) snapshot, revealing ANZ brands have accelerated AI adoption at the fastest rate in Asia Pacific (APAC) this year. The study found the number of brands formally deploying and evaluating generative AI solutions increased from 14% in 2024 , less than half the APAC average to 29% in 2025. “As AI is rapidly adopted and marketing teams are expected to acquire new skills and supervise higher volumes of content, it can feel overwhelming.
This makes agentic AI appealing, given its potential to automate customer engagement and lighten internal workloads. However, new agentic AI applications won’t be effective unless they’re built on connected data,” Egan said.
“These tools, coupled with cross-team collaboration, will ensure businesses can overcome their most significant challenges and continue to unlock AI’s full power to achieve personalisation at scale and more importantly, business growth.”
It also found a further 12% of executives have working generative AI solutions that are already delivering consistent, measurable return on investment (ROI) – in line with the global average. Others are earlier on their AI journey, with pilot projects in motion (24%).
Senior leaders reported significant improvements from AI-driven personalisation, including improved customer engagement (45%). “Local brands have significantly advanced their AI initiatives in the past year, building on a responsible foundation of AI guardrails and data governance essential for scaling,” said Duncan Egan, Vice President of Enterprise Marketing, Adobe APAC and Japan. “With two in three brands planning to invest in data integration and real-time insights over the next couple of years, it’s clear the focus is shifting towards connecting data to help deliver timely, consistent, and relevant customer experiences.”
Brands also recognise the potential for personalisation to drive broader business growth, nominating it is the top priority for 2025. That’s followed by unifying data, and leveraging AI. Still, there is a significant gap to close when it comes to meeting customer demands. Currently, only 35% of consumers say they receive personalised recommendations and offers, while 62% want to receive them.
Understanding your data
Understanding data governance is essential for any business. Think of your data as a treasure chest: without proper care, it can be lost, damaged, or stolen. Data governance acts like a treasure map, guiding you to keep your data safe, accurate, and fully usable. It means knowing who is responsible for different types of data, such as having the finance manager oversee financial records, ensuring consistency across systems so customer names are always spelled the same, and controlling access to protect sensitive information. Beyond organization, good data governance also helps your business comply with important laws like the Privacy and Personal Information Protection Act, protecting customer privacy and avoiding costly fines or security breaches. By treating data as a valuable asset, setting clear policies, assigning roles, and following legal requirements, your business can make smarter decisions, build trust, and operate more efficiently.
How to create a good plan
To create a strong data governance plan, start by setting clear and achievable goals. First, take time to reflect on the data your business handles every day, such as customer information, sales figures, financial records, and employee details. Then, consider who needs access to this data. For example, sales teams may require customer records while HR should access employee files. It is also important to think about how you will keep this data accurate and secure, preventing errors and protecting against cyber threats. Mapping out the who, what, when, where, and why of your data will help you understand your landscape.
Once you have a clear picture, set specific, measurable goals like reducing customer record errors by 20 percent or achieving full compliance with privacy laws within the year. These goals give your team direction and benchmarks to track progress.
Next, designate data owners who will take charge of specific data sets. Even if your business doesn’t have a Chief Data Officer, someone needs to be responsible for managing data. For instance, the sales manager might own customer data, while the finance team oversees financial information. These owners set rules for how their data should be handled, keep it up to date, and approve any changes.
This creates accountability and prevents confusion about who is responsible for what. Alongside data owners, data champions or stewards manage daily data tasks and are familiar with how information flows through the business. Together, they form a data governance committee that reviews processes, defines policies, and monitors progress towards your data goals. Quarterly or biannual meetings are usually enough to keep everyone aligned.
Define the scope of your data
It is important to define the scope of your data, focusing on the core information that drives your business, like customer records and financial data. Not all data is equally critical. Peripheral data such as marketing analytics can be managed later. Prioritizing core data helps your business save time and reduce complexity. As you do this, set rules around data security, compliance with privacy laws, and how data should be used. This ensures your most valuable data receives the attention it deserves.
Finally, work with your IT team or outsource to data experts to build a solid governance framework. If your business uses several systems for customer data, for example a CRM and email marketing software, IT can help create a master data management system that consolidates all records into one reliable source. This reduces errors and improves accuracy. The team can also help with data quality by ensuring consistency across systems, track data lineage so you know where data comes from and how it moves, use metadata to clearly describe your data, and fill gaps by gathering missing information. With these systems in place, your data governance will be effective and scalable as your business grows.
Read NSW Data Governance Toolkit here
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