From Trusted Platforms to Exceptional Outcomes - Rethinking Data and AI at Scale
Mathematician Clive Humby said in 2006 that "Data is the new oil". Twenty years on, he has been proven right in ways he could never have anticipated. The increasing integration of physical and digital systems, followed by the rapid rise of Artificial Intelligence (AI), means that data is now very much a national resource - one that's not only driving growth across both the public and private sectors, but also transforming the way critical services are delivered, enhancing our collective wellbeing and quality of life.
However, in the rush to achieve all the outcomes promised in AI's earliest days, too many organisations find themselves limited by the foundational infrastructure. Legacy systems were simply not designed with such sophisticated, resource-intensive applications in mind, and so find themselves held back by inconsistent capacity and availability, disparate systems delivered by multiple suppliers (who may not share the same security and compliance standards), and inconsistent pricing and visibility caused by over-reliance on public platforms.
In our current period of mounting geopolitical turbulence, data sovereignty is a particular concern. While technology providers may be able to guarantee the location of certain data centre environments, the nature of modern SaaS platforms, Cloud infrastructure, and AI-powered workflows means that there is no guarantee that users' data will remain within their sovereign region, potentially leaving it vulnerable to national legislation like the US' Cloud Act, which allow governments to demand access to the data stored by Cloud providers.
This not only presents a grave risk in terms of users' privacy and security, but also means the data that powers mission-critical services like healthcare, defence, finance, and Critical National Infrastructure (CNI) may be left vulnerable to international bad actors.
Questions of data sovereignty therefore naturally lead into considerations around how we design, deploy, and scale the physical and digital foundations of emerging AI platforms that numerous organisations are exploring - the 'horsepower' that allows them to consistently deliver the desired outcomes at scale.
When infrastructure is designed with the next generation of AI workflows, and the new level of sovereignty they demand - inherent in the design, rather than retrofitted onto legacy infrastructure, the possibilities are tremendous and will drive a shift in our thinking around AI from a technology-focused approach, to an outcome-focused one.
However, while the concept is ostensibly simple, putting it into practice often proves prohibitively complex and costly, requiring the support of a trusted partner who can not only demonstrate deep knowledge of AI's ongoing evolution, but also the multiple physical and digital layers that provide the all-important horsepower, engaging with the appropriate providers to ensure their secure, seamless integration whenever necessary.
This will prove a crucial step in unleashing AI's full potential for organisations across the entire UK - from mission-critical public services that citizens depend on, to everyday interactions between businesses and their customers.
We explore this journey in greater depth in our latest report, Sovereign AI Horsepower - A British Model of Resilience, Competitiveness, and Trust. Inside, our experts consider the challenges and opportunities presented by the new generation of AI platforms and posit a new approach for bringing them to the enterprise in a way that delivers the desired outcomes with zero compromises in terms of compliance, security, or cost control. The report is free to read here for a limited time.
Frequently Asked Questions
What is sovereign AI?
Sovereign AI refers to Artificial Intelligence platforms and infrastructure designed to ensure that data, workloads and governance remain under the control of the organisation or nation that owns them. This helps maintain compliance, improve security and reduce exposure to foreign jurisdictional risks.
Why is data sovereignty important for AI?
Data sovereignty ensures sensitive information remains protected under local laws and regulations, reducing compliance risks and supporting secure AI adoption.
What are the risks of using public AI platforms?
Public AI platforms can create concerns around data residency, regulatory compliance, visibility, security and exposure to foreign legislation.
How does sovereign AI improve security?
Sovereign AI provides greater control over data location, access management, infrastructure security and governance frameworks.
What infrastructure is needed for enterprise AI?
Enterprise AI requires resilient connectivity, secure Cloud platforms, scalable compute resources, robust governance and integrated cyber security capabilities.
How does AI affect Critical National Infrastructure?
AI can improve operational efficiency and decision-making within Critical National Infrastructure, but requires strong security, compliance and sovereignty controls to protect critical services.
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