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Data and AI sovereignty: A universal business imperative grounded in two unifying rules

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More than 10,000 of the world’s 34,500 large enterprises—nearly 30%—have already committed to becoming their own data and AI platforms. And within just three years, over 95% of global enterprises say they want to do the same, regardless of where they operate—from Japan and India to the US, EMEA, and MEA. This isn’t just a regional trend. It’s a global imperative. And it’s accelerating.

While the first three waves of digital transformation took a decade or more to reshape industries, the agentic revolution may unfold in less than three years. That’s not just speculation—it’s the view of 2,050 executive leaders across 13 economies surveyed in our 2025 global study. Their consensus is clear: the time to act is now.

This is a tale of two futures. For the 13% of enterprises already getting it right, the advantages are profound. They report five times the ROI of their peers and are deploying agentic and generative AI capabilities at twice the scale. Perhaps more tellingly, these leaders are 250% more confident in their ability to remain at the forefront of their industries over the next three years. Their platform choices are not just strategic—they’re producing measurable economic outcomes.

Meanwhile, the other 87% aren’t necessarily struggling—but they are behind. Their return on AI investment is, at best, a fraction of what the leaders are generating. At worst, they’re five times less productive, still reliant on legacy infrastructure, and unable to meet the rising expectations of customers, regulators, and shareholders.

The conviction to move toward sovereign data and AI infrastructure is shared across the globe. Leading enterprises in Scandinavia, the United States, Saudi Arabia, the UAE, and Japan are rapidly building their own platforms. And among the 13% of high performers, the highest concentration of success stories is emerging in Germany, Saudi Arabia, the UAE, and the US. These regions are showing us what’s working—and why.

Rule one: Mission-critical sovereignty enables scalable agentic AI

What distinguishes the 13% is not just what they do, but how they think. Nearly 90% of these organizations share one defining mindset: they see sovereignty over their AI and data as mission-critical. They believe that all their data—structured and unstructured—must be accessible in real time, regardless of where it’s stored. They prioritize eliminating silos, enforcing compliance, and creating an environment where data and AI can work together seamlessly.

This belief isn’t theoretical—it’s validated. In our research, across more than 15,000 simulations that combined 15 agentic and GenAI capabilities with seven economic metrics and 35 data infrastructure variables, the organizations that focused on real-time sovereign access and control consistently outperformed. Statistically, this pattern of success showed an exceptionally high predictive score (CHAID and regression: 0.982), confirming that this mindset isn’t just useful—it’s essential.

These leaders aren’t treating AI and data as separate disciplines—they’ve fused them into a single, sovereign engine that fuels operations across more than a dozen business areas. They’ve built platforms that don’t care where the data lives because the design ensures access, security, compliance, and scale. And as a result, they’re moving faster, innovating more, and outpacing competitors.

Every day, an average of 58 new enterprises begin this transition. That’s the scale of change we’re witnessing. The question for those not yet moving is simple: do you have the infrastructure—and the mindset—to thrive?

Rule two: Compliance, observability, security, and agility must be designed in

Sovereignty isn’t just about ownership. It’s about architecture. The most successful organizations don’t just talk about sovereignty—they’ve engineered it across four interdependent layers: compliance, observability, security, and agility.

They’ve built environments where AI can interact with the real world without compromising data integrity or breaching regulatory obligations. Financial forecasting agents, for example, need to pull from CRM, customer experience, sales funnel, ledger data, and external benchmarks. Edge agents may need to ingest signals from vehicles, sensors, or telecom infrastructure. Sovereign AI requires the infrastructure to support all of this in a unified, compliant way.

Among the deeply committed, over 40% operate on a truly hybrid infrastructure—one that supports full observability across environments, from cloud to on-prem, and delivers centralized control through a single pane of glass. This allows them to respond to competitive threats, regulatory changes, and customer demands simultaneously. They’ve reduced reliance on global infrastructure providers, built flexibility into their architectures, and are realizing more than double the innovation and efficiency gains of their peers.

These are not abstract advantages. These are measurable business outcomes that compound over time—what many refer to as the sovereignty flywheel. When you have unified control, innovation becomes faster. When compliance is built in, agility increases. When observability is complete, optimization becomes constant. And when security is inherent, trust becomes an asset.

This is why the sovereignty movement is growing so quickly. It’s not just the right thing to do. It’s the profitable thing to do.

Redefining success in the agentic and gen AI era

What’s happening is a global migration—not just to AI—but to sovereign AI. More than ever, enterprises are realizing that just “having” AI isn’t enough. Real success comes from owning the infrastructure, the data, and the intelligence end-to-end.

Open source platforms like PostgreSQL are powering this shift. Flexible, hybrid, and battle-tested, Postgres is enabling enterprises to unify AI and data across environments, accelerate their sovereignty strategies, and build resilient systems that scale.

Because at the end of the day, just anything isn’t data and AI sovereignty. Building the right architecture, with the right mindset and the right principles—that’s the definition of success in a world where AI is no longer optional.

The race is on. The winners are emerging. And the rules are now clear.

To learn more about EDB, visit here.



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Major artificial intelligence (AI) service companies such as Google, OpenAI, and Dipsyck are raising..

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Major artificial intelligence (AI) service companies such as Google, OpenAI, and Dipsyck are raising prices one after another for B2B users. This is a different result from the previous prediction that AI service prices will fall as AI use becomes more common and competition among companies intensifies.

In addition to the assessment that concerns that AI companies can raise prices after securing the market have become a reality, there are also growing calls for Korea to secure “Sovereign AI” (self-AI model) to prevent domestic companies from putting pressure on AI costs.

According to the information technology (IT) industry on the 2nd, China’s DeepSeek announced in a recent announcement that it will abolish the night discount system for corporate customers and adjust input/output unit prices from the 5th.

The current input is $0.07 per million token and the output is $1.10, but the output will go up to $1.68. The input remains at $0.07 if the same data is repeatedly used, but when new data is imported, $0.56 is added. Discounts that were only applied during the night hours will also disappear.

It is the first additional increase in half a year following a five-fold increase in fares in February. At the time, inputs were up from 0.014 to 0.07, and outputs were up from $0.28 to $1.10. The industry is concerned that the end of the night discount could increase the output rate by up to three times.

An IT industry official said, “As companies are feeling the effectiveness of AI, demand will remain even if rates are raised,” adding, “AI companies will try to take advantage of this to cover enormous development costs and infrastructure investment and maintenance costs.”

A similar trend is also seen in other global AI companies. OpenAI unveiled GPT-5 in August, changing its enterprise ChatGPT pricing plan from a flat-rate to a usage-based system.

In the past, all functions could be used for a certain amount of money on a monthly basis, but in the future, credit will be purchased and used as much as necessary. If you choose an advanced function, you will be charged additional costs, and the specific unit price will vary depending on the terms of the contract, so it was not disclosed. Only team pricing plan for small organizations will have a flat rate of $25 to $30 per month per user.

Google also raised Gemini rates in June. Input for the 2.5 Flash model increased by $0.15 to $0.30 per million token and output by $0.60 to $2.50, respectively, by nearly doubling and quadrupling. The system of differential application of rates by performance has disappeared and a single pricing system has been introduced. Instead, the flashlight model is newly established to provide relatively low-cost options of $0.10 input and $0.40 output, but from the perspective of companies, the overall unit price has risen, increasing the cost burden.

Anthropic also introduced weekly usage restrictions in July to prevent some subscribers from using Claude’s coding tools indefinitely, and the latest model Sonet 4 has a new rate system.

Sonet 4 supports a super-large context function that can process up to 1 million tokens, but from inputs exceeding 200,000 tokens, you will be charged $6 in input and $22.50 in output per 1 million token.

Some point out that even if some AI models lower unit prices, the burden on companies is increasing.

According to the Wall Street Journal (WSJ), companies that have introduced AI, such as chatbots, document summaries, and code writing, have seen their token unit prices fall, but their actual bills are increasing. The information also said, “The price of advanced AI models has not fallen in the past six months.”

In particular, the spread of agent-type AI applications has led to a surge in token usage, and the amount of computation has increased in the process of repeatedly executing the same query several times or driving its own calculation program.

Big tech such as Google, Meta, and OpenAI can afford these costs based on their enormous financial power, but startups and small and medium-sized companies are struggling with unexpected spending.

An industry official said, “In a situation where the use of AI is essential, the cost burden can hinder innovation,” adding, “In the end, there is a high risk that viable companies will be concentrated on large companies with capital power.”

[Reporter Kim Kyu-sik/ Silicon Valley correspondent Wonho-seop]



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From bugs to bypasses: adapting vulnerability disclosure for AI safeguards – National Cyber Security Centre

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From bugs to bypasses: adapting vulnerability disclosure for AI safeguards  National Cyber Security Centre



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The AI Con — unpacking the artificial intelligence hype machine

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Is the world really in the midst of an AI revolution, or is it all just clever marketing, powered by immense amounts of money, capital and hype? This episode arms you to spot AI hype in all its guises, expose the exploitation and power-grabs it aims to hide, and push back against it at work and daily life.

The conversation with Emily M Bender was recorded at RMIT University in partnership with Readings books on 1 July 2025.

The panel discussion Reboot the Narrative was recorded at the Rose Scott Women Writers Festival on 27 June.

Speakers

Emily M Bender 
Professor of Linguistics and Adjunct Professor in the School of Computer Science and the Information School at the University of Washington
Co-author (with Alex Hanna), The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want
Co-host, Mystery AI Hype Theater 3000 podcast

Kobi Leins (host) 
Digital ethics and human rights lawyer
Author, New War Technologies and International Law: The Legal Limits to Weaponising Nanomaterials

Tracey Spicer 
Journalist and broadcaster, author of Man-Made: How the bias of the past is being built into the future

Paula Bray 
Chief Digital officer at the State Library of Victoria

Lucy Hayward 
Chief Executive Officer of the Australian Society of Authors

Ally Burnham (host) 
Screen writer and novelist, author, Swallow



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