Andrew Abraham, Managing Director of Experian Data Quality
Businesses have faced significant challenges in recent years from economic uncertainty to rapid digital transformation. As we head into 2026, one theme is clear: data quality and governance are becoming critical foundations for resilience and growth.
The reality is that poor data quality remains one of the most persistent barriers to progress. It can lead to compliance breaches, inefficiencies, and reputational damage. Experian’s recent Data Quality Report reinforces this, with over half of organisations highlighting inconsistent or incomplete data as a significant challenge to achieving their data goals.
And as organisations scale their use of AI, the consequences become even greater. Recent IDC research shows that 88% of AI proofs of concept fail to launch, largely due to poor data quality. When data is inaccurate or incomplete, models suffer, bias creeps in, and ROI stalls. And without robust governance frameworks, these issues escalate, leading to flawed and inefficient AI implementation.
So how can organisations overcome these challenges and build the resilience needed for growth? Here are five trends that will define the data quality and governance agenda in 2026.
1. Automation of data quality will accelerate
Manual checks can’t keep pace with the volume and complexity of today’s data. Automated validation, cleansing, and exception handling are becoming essential for improving efficiency and reducing error rates. The report shows that improving data quality and consistency is the top priority for investment over the next two years which is a clear signal that organisations are turning to automation to support scale and operational resilience.
2. Platform usability will remain a top barrier
Even the most powerful data platforms fall short when they are difficult to navigate. When business users struggle to find the right data, run checks, or interpret results, adoption slows and value is constrained. Research also highlights that many organisations still lack true self-service access to data, limiting the ability for teams to act quickly and independently. In 2026, organisations will expect intuitive, self-service tools that integrate naturally with existing workflows and support faster, more confident decision-making.
3. The rise of the Chief Data Officer
Data governance has become a board-level priority. With only one in four organisations reporting clarity on data ownership, the need for dedicated leadership is clear. The findings show that 43% of organisations already have a CDO or CIO, with a further 19% planning to hire one within a year. As data becomes ever more critical across the business, these roles will be crucial in aligning data strategy with commercial objectives and regulatory requirements.
4. Trust and integrity as differentiators
Scrutiny from consumers and regulators is increasing, particularly around how data and AI are used. Compliance with data legislation also remains a major challenge for many organisations. Those that can demonstrate transparency, fairness, and responsible practices will strengthen trust and stand out competitively. This means that in 2026, the ability to evidence integrity in data and AI processes will become an essential hallmark of market leadership.
5. Investment will shift to strengthen data foundations
Before accelerating into advanced analytics or AI, organisations must reinforce the fundamentals: governance, stewardship, quality controls, and clear ownership. Improving data quality and consistency is the number one priority for investment, ahead of compliance and migration programmes. Those that invest early will unlock faster ROI and be better positioned to innovate. The differentiator in 2026 will be the willingness to start, learn, and evolve.
Strengthen your business foundation
Organisations are already recognising that data quality and governance underpins every stage of transformation. As we look ahead to 2026, the focus will shift from experimentation to measurable outcomes. More importantly, organisations that prioritise strong data foundations today will be better placed to scale responsibly, meet regulatory expectations, and unlock their full innovation potential in the years to come.
