More Than Half of Taiwanese Enterprises Concerned About Data Leakage in Cloud AI, Over 70% Seek On-Premises AI Yating FedGPT Sovereign AI Platform Enables Secure and Controllable Enterprise AI
June 30, 2026 — AI technology is advancing at an unprecedented pace, driving widespread adoption of personal AI applications. However, enterprise AI adoption has yet to deliver the productivity gains many organizations expected. Concerns over data privacy in public cloud AI services, limited control over user permissions, and unpredictable model updates remain major barriers to enterprise deployment.
To examine the current state of enterprise AI adoption, its challenges, and potential solutions, Yating Intelligence and Taiwan AI Labs jointly hosted the Sovereign AI Summit today (June 30), where they unveiled the 2026 Taiwan Enterprise AI Transformation Insights Report.
The survey collected 562 valid responses from organizations across more than ten industries, including education, media, healthcare, government, manufacturing, and finance.
Yating Intelligence Chairman Cheen Liao announced four key findings:
First, while personal AI adoption has become increasingly widespread, enterprise AI implementation remains largely confined to pilot projects. Only 15% of organizations have scaled AI across multiple departments, while the remaining 85% are still in the stages of small-scale experimentation, evaluation, or have yet to adopt AI, indicating that most enterprises have not established a governable AI operating framework.
Second, 51% of enterprises are concerned about data leakage. At the same time, the AI applications they most want to implement include repetitive administrative process automation (56%), data analytics and decision support (44%), and internal knowledge search and document question answering (42%). These use cases all rely heavily on proprietary enterprise data, making them among the highest-risk scenarios for confidential information exposure.
Third, existing public cloud AI tools remain difficult to integrate deeply into enterprise operations. 34% of respondents said cloud AI cannot adapt its reasoning to their business requirements; 39% believe AI lacks sufficient understanding of industry-specific terminology; 24% worry that cloud AI services may be discontinued, disrupting existing workflows; and 19% are concerned that future model updates could negatively affect existing performance.
Fourth, demand for on-premises AI deployment is rising significantly. 77% of respondents believe current public cloud AI services still impose limitations on enterprise use, while 72% expressed a clear need for on-premises AI deployment.
Five Pillars of Sovereign AI Build Trusted Enterprise AI
Addressing enterprises’ concerns over AI adoption, Ethan Tu, Founder of Taiwan AI Labs, emphasized that when core business processes rely on external cloud AI services, organizations face operational continuity and competitiveness risks if those services are discontinued, pricing changes, or model capabilities evolve.
He explained that the essence of Sovereign AI is autonomy.
While Taiwan may not possess absolute advantages in data resources, capital, or energy compared with other countries, the current wave of AI transformation presents a new opportunity. Taiwan’s highly digitalized, decentralized, self-governing, and trust-based society provides fertile ground for developing federated AI.
Through a federated architecture, organizations can ensure that “data stays where it is, while models move instead of the data.” Institutions can collaborate while maintaining ownership of their own data and preserving privacy. This approach aligns with national sovereignty while improving enterprise competitiveness, security, and operational efficiency.
Enterprise Sovereign AI is built upon five pillars:
- Data Sovereignty — AI governance platforms that keep data within enterprises, institutions, and organizations.
- Model Sovereignty — Support for local AI models and domestic AI ecosystems without dependence on specific multinational vendors.
- Compute Sovereignty — Transparent and democratically governed public AI computing resources that avoid concentration of computing power and protect private-sector innovation.
- System Sovereignty — Building independent AI frameworks and ecosystems rather than focusing solely on hardware procurement.
- Governance Sovereignty — Aligning with international AI governance standards to establish verifiable, auditable, and trustworthy AI ethics and regulatory frameworks.
Tu stressed, “Every AI action inside an enterprise must have a clearly defined authorization process and accountability. Humans are responsible. AI can never replace human responsibility.”
Taiwan Positions Sovereign AI as a National Strategy
During the summit keynote, Minister of Digital Affairs Yi-Jing Lin stated that Sovereign AI is not merely a technology initiative but a strategic foundation for national competitiveness and cultural autonomy.
The Ministry is advancing Taiwan’s Sovereign AI ecosystem through five policy pillars: computing infrastructure, data, talent, international promotion, and investment.
As part of its AI infrastructure strategy, the Ministry has announced the AI Computing Center BOO Project, incorporating national AI computing facilities into major public infrastructure projects to attract private investment. The initiative is expected to exceed NT$100 billion in investment and provide more than 20,000 GPUs, with a portion of the computing capacity reserved for government agencies and academic institutions at free or preferential rates.
Lin noted that Taiwan’s objective is not only to strengthen domestic AI capabilities, but also to develop AI models that genuinely understand Taiwan—its Traditional Chinese language, social and cultural context, and democratic, diverse, and open values.
Looking ahead, the Ministry will continue promoting Taiwanese AI services and solutions globally, positioning Taiwan as both a leader in Sovereign AI development and an important international partner.
Yating FedGPT Keeps Enterprise Knowledge Internal While Building an AI Brain for Organizations
Benson Tu, General Manager of Enterprise Solutions at Yating Intelligence, said that FedGPT was developed specifically to address enterprise concerns over public cloud AI.
FedGPT is a fully on-premises Sovereign AI platform that integrates with existing enterprise systems while ensuring all data remains inside the organization. It automates repetitive cross-departmental workflows and enables enterprises to build AI systems that are fully under their own control.
The AI models powering FedGPT are also developed by Taiwanese teams. According to evaluation results, they demonstrate outstanding capabilities in understanding Taiwanese knowledge, language context, and enterprise tasks, performing on par with many leading international cloud AI models.
Du explained that enterprises generate enormous volumes of meeting records, emails, and system logs every day, yet this information is often fragmented across multiple systems.
Serving as a centralized enterprise knowledge hub, FedGPT enables managers to gain clear visibility into decision-making processes and project progress, while allowing employees to quickly retrieve organizational knowledge and improve productivity.
During the summit, Du demonstrated multiple real-world enterprise applications.
For example, the Meeting Assistant AI automatically records meetings and enables users to retrieve previous discussions instantly through voice or text.

FedGPT enables enterprises to build automated workflows such as employee onboarding, account provisioning, and attendance approval. Shown here is the Universal Secretary handling domestic business travel reimbursement.
The Universal Secretary AI helps employees search internal policies such as expense reimbursement, leave requests, business travel, and office supply applications, while automatically completing workflow submissions.
The AI agents and automated workflows can also integrate with APIs from different enterprise systems to support industry-specific applications.
For healthcare organizations, FedGPT can connect with hospital information systems to generate clinical summaries, answer patient education questions, and prepare monthly reports for medical staff.
When integrated with facial recognition access control systems, HR teams can instantly check employee attendance and manage meeting reservations.

FedGPT can integrate with various enterprise information systems to expand AI use cases. When connected with hospital systems, it can support intelligent patient navigation, waiting status updates, and post-operative care guidance.
Yating Intelligence Partners with Industry Leaders to Build Taiwan’s Sovereign AI Ecosystem
At the Summit, Jon Wang, Managing Director, Taiwan & Hong Kong, HPE, said, “HPE is committed to helping build secure, scalable AI infrastructure that supports on-prem and hybrid AI deployments. Through collaboration with ecosystem partners, HPE enables customers to accelerate enterprise AI adoption while maintaining security, governance, and operational flexibility.”
The summit also showcased solutions developed by several FedGPT strategic partners and independent software vendors (ISVs), including Maxnion AI ,truley.AI , WiziGo Corporation, and Awespire .
For enterprises requiring industry-specific or customized on-premises AI applications, FedGPT provides the technology platform while ecosystem partners develop specialized solutions, jointly building an AI environment that Taiwanese enterprises can fully control.
For the media and entertainment industry, Maxnion AI Technology demonstrated AI agents capable of organizing massive multimedia libraries and transforming video content into searchable enterprise knowledge assets.
Awespire showcased AI-powered Expressive Digital Humans capable of turning static photographs into animated, speaking avatars using FedGPT.
In education, WiziGo ‘s ePeer Learning Platform integrates with FedGPT to analyze student learning records and provide personalized capability assessments and development recommendations.
For general enterprise applications, truley.AI demonstrated AI-powered meeting transcription, enterprise knowledge management, and workflow automation that support both cloud and on-premises AI deployment.
Liao concluded that while open-source models and AI applications have rapidly accelerated personal AI adoption in recent years, enterprise leaders place greater importance on process traceability, access control, and corporate governance when deploying AI into mission-critical operations.
By collaborating with hardware providers, independent software vendors, and system integration partners, Yating Intelligence is building a Sovereign AI ecosystem tailored for Taiwanese enterprises—helping organizations deploy AI securely while creating greater value across Taiwan’s industries.










的發展有4個層次。-1030x687.jpg)
應用程式-1030x687.jpg)









與東華大學校長徐輝明(右)合影。-1030x551.jpg)
