Enterprise Artificial Intelligence: Building Trusted AI in the Sovereign Cloud
The decade of responsible intelligence has begun — are you ready?
Enterprise AI is hitting a wall: Public models aren’t trained on your business data, but you can’t hand over your organization's proprietary information to a public system. The definitive roadmap for this new reality is Enterprise Artificial Intelligence: Building Trusted AI in the Sovereign Cloud, a new book written by OpenText leaders. Listen now to learn why this book is a must for organizations looking to move from isolated AI experiments to enterprise-grade deployments.
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Enterprise Artificial Intelligence: Building Trusted AI in the Sovereign Cloud
Foreword
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The foreword to Enterprise Artificial Intelligence: Building Trusted AI in the Sovereign Cloud, written by OpenText leaders, was authored by James Arroyo OBE, former Director for Data at the British Foreign and Commonwealth Office and Director of The Ditchley Foundation.
Enterprise Artificial Intelligence Building Trusted AI in the Sovereign Cloud by Shannon Bell, David Frasier, and Tom Jenkins. First publication, November 2025. Published by Open Text Corporation. Forward James Arroyo, OBE, former Director for Data, British Foreign and Commonwealth Office, and Director of the Ditchley Foundation. James Arroyo's views do not necessarily represent those of the Ditchley Foundation. We stand at a pivotal juncture in history, a time when the world's technological systems are converging, raising questions of power, trust, sovereignty, and governance. Artificial intelligence is redefining how decisions are made, how organizations operate, and how societies function. Yet progress in AI cannot be measured solely by technical capability. We must combine advances with policy clarity, ethical discipline, and a renewed understanding of what sovereignty means in the digital age. This book, Enterprise Artificial Intelligence, Building a Trusted AI in the Sovereign Cloud, addresses both the challenge and opportunity presented by AI. It recognizes that the next decade will not only be defined by who builds the largest models, but by who governs and uses data most effectively. Data is both the fuel and the foundation of modern intelligence systems. Much like energy or currency, it requires regulation, stewardship, and above all, trust. The future of AI depends on how we manage the privacy, provenance, and sovereignty of that data. This will become critical as individuals, institutions, and enterprises move to add their own personal proprietary and sovereign data to AI systems. When I served as Director for Data at the UK's Foreign and Commonwealth Office, our task was not simply to digitize the institution and define the policies that would make digital transformation sustainable for decades to come. We had to ask difficult questions. Who owns the data we rely on? Where does it reside? How is it shared, stored, and secured? How long should it be retained? Those same questions now confront every enterprise, every government, and every citizen as AI systems become more autonomous and pervasive. AI's powers of inference mean that every atom of data can potentially bring insights in aggregate combination, and that is game-changing. In conversation with leaders from technology, government, and civil society, it is becoming clear that sovereign data policy is not a technical debate. It is a question of national and economic security. In a world where the majority of data is locked behind organizational and governmental firewalls, sovereignty extends beyond mere compliance. It is about control, accountability, and the ability to act with confidence in a world of algorithmic decision making. This book makes a compelling case for that philosophy. It argues that trusted data and responsible AI are two sides of the same coin, and that to build AI that is fair, explainable, and safe, we must ensure the data it learns from is well governed, contextual, and sovereign. Without privacy and data stewardship, AI risks undermining the very institutions it seeks to empower. Without innovation, governance risks becoming a hindrance that hinders progress. The task before us is to align trust and innovation so that one strengthens the other. As you read, you'll see how the landscape of enterprise computing is being rebuilt from the inside out. Hyperscale infrastructure, sovereign clouds, and AI driven systems are forming the backbone of the digital economy's industrial grid. But real advantage will belong to those who treat data not as a neutral commodity, but as a constitutional principle, something to be protected, respected, and deployed responsibly. The book's call to action is one I can warmly endorse to move fast but to govern faster, to innovate boldly but with purpose, to ensure that every digital advance strengthens public trust rather than erodes it. That is the essence of leadership in this new era of AI. In the years ahead, the nations and enterprises that will win by embedding AI in society and encouraging widespread and deep adoption will be those that understand a simple but profound truth. AI without trusted, sovereign, and well governed data is power without responsibility and perhaps legitimacy. But when innovation and governance move in step, when privacy, accountability, and ethics are embedded in design, we can create not just intelligent systems, but intelligent societies. The cognitive computing era is here. A time where trust is the foundation and innovation is the engine. Its success will depend not on machines alone, but on our shared ability to define the principles that govern them. Enterprise Artificial Intelligence, building trusted AI in the sovereign cloud, offers a roadmap for that journey and an invitation to shape the future responsibly together.