From business decisions to customer communications, artificial intelligence (AI) initiatives, and everything in between – data is critical. Whether this is first, second, third or even fourth party data, the public sector is constantly handling oceans of information and utilising it to inform and drive multiple initiatives.
However, the sheer volume of information being handled – which is often siloed across and within different departments – poses a significant challenge to data integrity. That is, how trustworthy the insights, and therefore decisions, are. Without robust strategies and dedicated leadership, data can become stale, unstandardised, full of duplicates or incomplete, making it unreliable for meaningful, strategic insights.
This demonstrates the growing need for a comprehensive data integrity strategy, spearheaded by a chief data officer (CDO). The CDO’s role is to thoroughly manage how data is collected, governed and used, ensuring its optimal value is extracted and its quality maintained throughout the organisation.
Despite the benefits, the UK public sector has historically been slow to adopt this critical role and to develop robust and sustainable data initiatives. Alarmingly, 45 percent of public sector organisations lack a formal data strategy altogether.
This lack of direction is particularly concerning given how many critical decisions impacting millions of citizens rely on public sector data. With organisations striving to implement and innovate with AI, those without sound data strategies are being left behind, or are fuelling their AI models with untrustworthy inputs. This has significant consequences in public services.
AI readiness in the public sector
When it comes to AI adoption, organisations are too keen to run before they can walk. Despite heavy investment into AI, the fundamental importance of data integrity is often overlooked. In fact, research reveals that only 12 percent of organisations believe their data is truly AI-ready, and 85 percent of AI projects fail due to poor data quality, weak governance, or misalignment between business and IT.
For the private sector, this translates as poor return on investment for AI. However, for the public sector, the consequences of faulty AI are potentially life-altering. There are already significant real-world impacts of this, ranging from impaired facial recognition software that inaccurately identifies women and people of colour, to inequities in healthcare provision.
In fact, recent findings indicate that AI bias – the production of incorrect outputs due to incomplete, unreliable, and inaccurate data – is causing pulse oximeter devices to less accurately detect dangerous falls in oxygen levels for people with darker skin tones.
Without a dedicated role to regulate the data flowing into, out of and throughout an organisation, these biases will continue to emerge.
Fuelling the AI machine
The UK public sector is increasingly embracing data-hungry initiatives, including generative AI, to drive transformation. In fact, the UK Government has recently announced plans to implement OpenAI software across the public sector to boost productivity. The demand for high-integrity data has never been greater.
AI – while offering unprecedented potential to streamline processes and enhance operational performance – is fundamentally dependent on the integrity of its inputs. For example, if AI were represented as a sophisticated machine in a factory, data would be the raw materials. If those inputs are faulty, cheap, or incorrect, the machine will not produce the desired end product and could even malfunction.
This is where CDOs and the strategy they implement are invaluable. The CDO is the human oversight, ensuring a constant supply of accurate, consistent, and contextual data flows into every aspect of the AI “machine”.
Additionally, a proactive CDO identifies potential data pain points, explores superior data sources, and implements efficient collection methods, preventing issues before they arise. To support this, the CDO builds a data-driven culture throughout the organisation. Consequently, organisations can trust the AI-driven insights and they can safely use AI to drive efficiency.
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The role of data integrity in AI
Indeed, robust data management programmes based on high-integrity data are vital to ensuring the trustworthiness of AI. A strong culture – comprising data integration, governance, quality and enrichment – ensures data at all levels of the company is standardised, stored correctly and interrogated for anomalies before reaching the AI models.
Indeed, many organisations rely on multiple, and usually disjointed, applications to manage their different types of data, storing them in siloes and varying internal systems. This leaves data inconsistent, stale, duplicated, and incomplete, which undermines the reliability of AI outcomes.
To improve the reliability and trustworthiness of AI outcomes, public sector organisations must start by breaking down these data silos and integrating critical data across cloud, on-premises, and hybrid environments as well as across different departments. Building a holistic view of the data ultimately provides AI models with a more comprehensive understanding of patterns and trends stored in the data, creating reliable and well-informed results.
However, the CDO’s job isn’t finished here – a robust approach to data governance and quality is also critical. At its core, a comprehensive data governance programme aims to provide a fuller understanding of the data’s source, use, meaning, ownership, and quality. It establishes confidence in an organisation’s data by ensuring that AI models have access to all necessary information, and that the data is being used ethically and responsibly.
To achieve this, organisations need a solution that automates governance and stewardship tasks, and proactively ensures the quality, value, and trustworthiness of their data before it can cause any issues downstream. Trusted high-quality datasets are essential to powering AI systems that deliver accurate, equitable outcomes – particularly in public services where getting the right information to the right citizens is critical.
Accuracy and completeness are vital, but context is just as important. Without it, even high-quality data is vulnerable to misinterpretation. The public sector overcomes this by enriching first-party data with curated third-party sources – such as points of interest, demographic profiles, precise address data, and environmental risk indicators. By layering in this external context, patterns and insights emerge that would otherwise remain hidden, enabling smarter, more informed decisions.
Ultimately, by fostering a data integrity culture – built on integration, governance, quality, and enrichment – the CDO ensures every initiative, including AI use, is supported by a clean, contextualised, and trustworthy data foundation. What’s more, the CDO spearheads a consistent, sustainable framework for innovation, which ensures public trust. This approach empowers the organisation to act with greater confidence, agility, and impact.
The value of data
In our personal and professional lives, data holds as much value as financial capital. In the context of the UK public sector, every initiative, strategy, and communication are not only underpinned, but driven by data – so the room for error is wafer thin.
With vast quantities of data constantly flowing, attempting to manually catch every inconsistency is unmanageable. When faulty data slips through, the implications are far-reaching and potentially catastrophic.
Establishing a strong foundation of data integrity, spearheaded by a CDO, is therefore essential for generating meaningful insights, on which important decisions can be made, in the UK public sector. Without this, the full potential of AI cannot be realised. In fact, the growing use of AI is increasing the urgency of establishing sound data integrity strategies.
Indeed, just as the internet’s emergence led to new roles and industries, the growing prevalence and influence of AI means that organisational structures must evolve. Increasingly, public sector organisations will need to appoint more strategic roles, such as the CDO, to ensure trusted data flows throughout the organisation and AI is implemented successfully and ethically.
