AI regulation is rapidly evolving globally. The EU, China, and South Korea have each established and implemented regulatory frameworks, while in the US, the American AI Action Plan aims to boost AI innovation by removing red tape.
Companies are having to navigate increased compliance complexity to realize all the benefits that AI tools can bring.
Roger Lee
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Area Vice President for Solutions Consulting at Appian.
The EU AI Act sets a precedent as the first comprehensive regulation of artificial intelligence by a major governing body.
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Coming into force: the EU AI Act
With the majority of its provisions to come into effect in August 2026, the Act establishes clear guidelines for how companies must utilize AI within the European Union.
Any organization deploying AI or otherwise using AI output inside the EU must adhere to the act’s risk-based framework, which assesses transparency, verification, and human oversight to determine operational risk levels.
Businesses failing to meet these requirements, especially in high-risk AI usage, face both financial and reputational consequences, as failures could pose major risks to personal data.
Understanding data sovereignty
Data sovereignty refers to the principle that data collected in a specific region is subject to the laws of that region. This concept is much more than a compliance checkbox; it is essential to thrive amid new and evolving regulations.
Maintaining control over data is vital for providing traceable evidence to regulators, as losing that control can result in operational limits or exclusion from global markets.
This is exactly why security and compliance are now top of the agenda for business leaders. According to a Gallagher survey, more than 2 in 5 business leaders have had to reassess their security measures surrounding AI to ensure compliance and reduce security risks.
Establishing true data sovereignty is the most effective way to tackle these risks. It ensures that sensitive data is not exposed to third parties, not used to train external AI models, and always remains within the compliance boundaries required by current and future regulations.
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Partnering with private AI vendors
Today, achieving true data sovereignty and meeting growing privacy expectations means going beyond generic public AI models.
While many AI governance principles – such as human oversight, transparency, and fairness – apply to AI regardless of deployment model, private AI provides an added layer of control that helps meet security, compliance and sovereignty requirements.
Partnering with a private AI vendor ensures your organization retains full control and oversight of sensitive information. Unlike public AI, private AI models are trained exclusively on your own data, ensuring your information is never shared externally or used to enhance third-party models.
This approach enhances data control and allows for customization to your business’s specific context and needs – essential for aligning with regulatory expectations.
Private AI platforms ensure your data never leaves your control, supporting compliance with regional data privacy laws such as the EU AI Act and GDPR. Features like robust encryption, customer-managed private keys and granular access controls make it easier to meet and demonstrate regulatory compliance.
By embedding AI within your own infrastructure or trusted private platforms, you retain full visibility into how data is processed. This reduces the risk of breaches or unintended exposure – all while maintaining compliance with regulatory requirements.
Non-compliance risks under the EU AI Act
The EU AI Act places strict requirements on how high-risk AI systems are managed, emphasizing data privacy, risk management and traceability. Private AI solutions support these demands by keeping your data and models confidential and under your control.
When properly implemented, they allow for auditability, updatability, and data erasure – all key for compliance with the EU AI Act. In contrast, public AI models often introduce ambiguity about how data is used and increase the risk of compliance gaps.
Maintaining human oversight
Even with advanced AI – whether public or private – human oversight is essential. Keeping people in the loop allows for intervention, error correction and accountability – critical components for responsible AI use and regulatory compliance.
Embedding AI into business processes with clear governance frameworks can strengthen stakeholder confidence while supporting sustainable, compliance growth. For organizations prioritizing data control, private AI platforms can further enhance oversight by offering visibility into model behavior, data usage, and decision pathways.
Security and traceability challenges in workplace AI
Relying on public AI solutions raises significant security and traceability concerns. Without clear boundaries, data may be repurposed or exposed, and tracking usage across multiple vendors can be challenging.
Private AI provides a solution with clearly defined governance models, enterprise-grade guardrails and seamless integration with existing workflows. This enables secure, adaptive infrastructure that can evolve as regulation and business needs change.
Cloud adoption for compliance and efficiency
Consider a Fortune 500 pharmaceutical firm facing efficiency challenges stemming from processes that require frequent handling of complex, time-sensitive documents. This presented a significant hurdle for regulatory compliance.
By integrating a private AI vendor directly into their workflow, the organization was able to streamline processes, delivering process certificates with 99% accuracy – all while maintaining compliance across the entirety of their business.
Laying strong foundations early enables companies to stay ahead of regulatory changes, making future transitions straightforward and transparent for both the organization and regulators. Early adoption of compliance frameworks also ensures a high level of stakeholder engagement and customer trust.
Preparing for the future of AI regulation
Robust data sovereignty and secure, scalable AI solutions help protect sensitive information and meet evolving regulatory requirements. Acting now simplifies compliance, reduces risk, and positions businesses to innovate confidently.
The EU AI Act is just the start. More rules are coming from industries, government agencies, and regional authorities. Addressing its core principles, reducing bias, enhancing transparency, and safeguarding data today will make future compliance far easier.
Embedding AI into core business processes – particularly through privacy-conscious, well-governed solutions – positions companies to stay ahead of evolving regulations, build trust, and drive innovation without compromising compliance.
Private AI offers a strategic path to achieving this, especially where data control and sovereignty are essential.
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