Here are seven key strategies I believe are essential for organisations navigating the evolving landscape of AI and data governance:
1. Drive accountability through business value
Assigning data stewards and governance roles is a good start but real traction comes when those roles are tied to business outcomes. At Experian, we’ve found that aligning governance with goals like reducing churn or improving customer experience drives deeper engagement and accountability.
2. Make governance part of business as usual
Governance shouldn’t be a bolt-on it needs to be embedded into everyday operations. One example that resonated at the Summit was integrating governance into the software development lifecycle. This mirrors our own approach at Experian, where governance is woven into how we build, deliver and evolve our solutions.
3. Evolve as a modern data governance leader
The role of governance leaders is shifting. Adaptability is key, especially with the rapid rise of AI and changing regulatory landscapes. Strategic communication and stakeholder engagement are central to how we ensure governance investments stay aligned with business priorities.
4. Focus on data quality for critical data elements (CDEs)
Data quality is non-negotiable. At Experian, we use scorecards and business-aligned metrics to ensure our critical data assets are trusted and validated. The Summit’s emphasis on managing CDEs reinforced the importance of this discipline.
5. Make data literacy meaningful
Data literacy isn’t just about training, it’s about culture. We’re focused on creating engaging, purpose-driven upskilling initiatives that make data learning fun and relevant. A key theme from the Summit was the need for data professionals to deepen their business knowledge to be truly effective, which strongly aligns with our own efforts.
6. Use technology to scale governance
Technology is a powerful enabler. We leverage tools for data cataloguing, lineage, stewardship and quality to scale our governance efforts. But tech alone isn’t enough, it must be paired with a strong framework and clear ownership to drive real impact.
7. Responsible AI – From hype to practice
AI is a strategic priority, and we approach it with a clear focus on solving real business problems. Our proof-of-concept initiatives start with well-defined problem statements, high-quality input data and early involvement from risk and compliance teams. Ethical AI is non-negotiable – we monitor for bias, ensure auditability and maintain data quality to build trust and sustainability.
Thanks again to DGX for hosting such a forward-thinking and collaborative event. It’s clear that the data governance community is ready to lead the way in responsible innovation and I’m proud to be part of that journey.
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Martin Soley is a seasoned leader with over 20 years of experience in data management across international and ANZ markets. He has successfully led data engineering, software development, product, and client-facing teams to deliver innovative solutions in data quality, insights, and governance. Martin’s strategic approach and cross-functional leadership has consistently driven value through scalable, high-impact data initiatives. |