RESEARCH REPORT
Sovereign AI: Own your AI future
From managing risk to accelerating growth – Why CEOs and government leaders must own the next phase of AI
5-MINUTE READ
November 3, 2025
Why sovereign AI, why now?
Artificial intelligence is no longer just a shiny new technology—it’s the backbone of national competitiveness and business survival. But today, the foundation of AI—its compute, data and models—is concentrated in very few hands. This creates dependencies that raise questions about national security, competitiveness and innovation. Current geopolitical tensions are bringing these risks into sharp focus.
The good news is that the path to risk mitigation and resilience also reveals a major opportunity.
Sovereign AI, done right, lets you tap global technology alongside local innovation while building in safeguards from the start. It’s a range of solutions designed to boost resilience while accelerating local value.
Who’s leading? Sovereign AI maturity by industry and market
As industries and governments move to own their AI future, understanding where sovereignty maturity stands is critical to identifying opportunities, gaps and growth potential.
To benchmark this readiness, we developed the Sovereign Maturity Index, which measures an organization’s overall digital and AI sovereignty on a scale of 0–100.
DATA
61%
of organizations surveyed say geopolitical tensions make them more likely to seek sovereign technology.
Top companies in sovereign AI are moving fast and boldly, playing both offense and defense.
Our research reveals four key imperatives that set leaders apart.
4 imperatives for making sovereign AI your strategic advantage
01
CEO ownership: Make sovereign AI leadership’s new power play
Why it matters
AI sovereignty is being negotiated on the global stage, yet only 15% of organizations have made it a CEO or board-level priority. Without top-level ownership, sovereign AI becomes a compliance checkbox—leaving organizations vulnerable to geopolitical risks and strategic trade-offs. Elevating sovereignty to the CEO and board isn’t just a governance move; it’s a power play that unlocks trust, accelerates growth and positions organizations to shape the rules of AI, rather than just inherit them.
Here's how CEOs can act now to shape the future of AI:
Take action
- Pick suppliers based on geopolitical risk, supply chain resilience and long-term cost.
- Establish governance frameworks that align legal, financial and tech priorities with national and corporate strategies.
- Engage policymakers to secure alliances and negotiate access to critical markets and technologies.
- Governments: Create roles such as an AI Sovereignty Officer in the public sector to signal the importance of executive ownership.
Who owns sovereignty?
15%
CEO or Board
19%
IT/Cloud Infrastructure team
29%
Chief Compliance or Risk Officer
37%
Chief Data or AI Officer
02
Reframe sovereignty: From risk management to value creation
Why it matters
Sovereignty is inseparable from competitiveness: Those who lead will shape markets; those who lag risk being locked out. Treating sovereign AI as a mere risk-management exercise traps organizations in a defensive posture, stifling growth and collaboration. The real opportunity lies in building AI that speaks your market’s language—literally and figuratively—creating customer trust, fueling local innovation and unlocking new revenue streams.
Take action
- Companies: Shift from risk mitigation to value creation by embedding sovereignty in your business strategy.
- Governments: Embed sovereignty in national, digital and industrial strategies. Fund local infrastructure, subsidize trusted providers and open public datasets. Partner with academia to build a pipeline of next-gen talent, local models and innovation.
- Providers: Act as ecosystem anchors, enabling smaller players to participate and thrive.
- Energy companies: Apply locally governed AI to grids to strengthen resilience and lower national cost.
Sovereignty drivers are still defensive:
46%
compliance
28%
control over critical data
27%
security needs
13%
monetization or tailoring AI to local value
03
Expand your ecosystem: Navigate the sovereignty continuum
Why it matters
AI infrastructure is fragmenting fast: Choice is now the only way to meet multi-faceted needs across providers, architectures, models and services. Seeing sovereignty as an all-or-nothing concept can force expensive system changes, create reliance on dominant global players, and leave organizations exposed when international rules shift. The smarter move? Orchestrating a flexible ecosystem that blends global scale with local trust—unlocking speed, resilience and a decisive competitive edge.
Take action
- Build hybrid strategies that combine the best of the four provider types in this growing sovereign ecosystem, as needed:
- Choose global cloud providers for scale and innovation.
- Choose frontliners for trust and industry-led solutions.
- Choose neoclouds for agility, performance and local governance.
- Choose federated consortia to tap the power of shared capabilities along with trust and interoperability.
Companies prefer hybrid solutions:
55%
are considering both local and global sovereign providers
27%
are focused solely on local sovereign providers
19%
are relying on global sovereign options only
04
Redefine architecture: Sovereignty for intelligence, not just infrastructure
Why it matters
Generative and agent-based AI are reshaping workflows, regulations are tightening and static compliance is no longer enough. That’s why now is the time to redesign your architecture for intelligence, not just infrastructure. With the right insights and controls across all layers of the AI stack—from infrastructure through models and apps—organizations can scale innovation while embedding trust, resilience and agility.
Take action
- Architect for multi-cloud, multi-model, and multi-agent collaboration to ensure flexibility and compliance at scale.
- Conduct sovereignty audits for each critical use case to determine the right level of sovereignty.
- Benchmark infrastructure, data residency and provider dependencies to identify gaps and prioritize modernization.
- Embed dynamic controls and governance across the AI stack to anticipate risks and adapt to evolving regulations.
Sovereignty gaps: Where companies apply controls across the AI stack
60%
data
46%
infrastructure
32%
applications
22%
AI models