84% of Organizations Report Operational Challenges with AI Adoption.
Industry leaders explore how healthcare providers can move beyond AI pilots to secure, measurable, and sustainable hospital-wide deployment.
TAIPEI, Taiwan, October 12, 2026 — As healthcare providers expand their use of artificial intelligence, integrating AI into hospital-wide operations remains a challenge. A global KPMG survey found that 72% of organizations reported efficiency gains from AI, while only 39% reported financial benefits and 84% faced operational challenges.
Against this backdrop, global AI company iKala hosted the "Healthcare AI: From Point Solutions to Hospital-Wide Intelligent Operations" forum on October 12, bringing together experts from Google Cloud and KPMG in Taiwan to discuss how healthcare institutions can move AI from proof of concept (PoC) to production.
Sega Cheng, Co-Founder & Chairman of iKala, emphasized that AI adoption requires changes to workflows and collaboration across clinical and technology teams. Citing iKala's work with Tzu Chi on IT, cloud and AI infrastructure for dialysis centers in eastern Taiwan, Cheng said technology must be designed around healthcare professionals' needs.
KPMG: AI Efficiency Gains Outpace Financial Returns
Jarret Su, Co-Head of Healthcare and Life Science Medical Doctor at KPMG in Taiwan, noted that 86% of organizations surveyed see AI as a competitive advantage, although financial returns remain less widespread than efficiency improvements.
Su outlined a three-stage strategy—Enable, Embed and Evolve—covering infrastructure and team readiness, integration into clinical and administrative workflows, and expansion into community, home-based and long-term care. He recommended prioritizing use cases with measurable benefits before scaling investment.
iKala Introduces AI Ready Architecture for Hospital-Wide Integration
"Traditional information systems were designed to solve specific problems. Today, people expect AI to carry out tasks on their behalf," said Gary Yang, Deputy General Manager, AI Service Division at iKala.
Yang introduced iKala's AI Ready architecture, built on three layers: Infrastructure Ready, providing secure on-premises, cloud or hybrid environments; Data Ready, connecting hospital information systems, electronic medical records and medical imaging systems with appropriate access controls; and AI / Agent Ready, integrating AI models and agents into existing workflows.
The architecture is designed to help healthcare institutions connect fragmented systems and establish the technical foundation for broader AI deployment.
Google Cloud Highlights Security and Human Oversight in AI Agent Deployment
Jason Peng, AI Sales Specialist at Google Cloud, warned of risks associated with unauthorized AI tools, citing research indicating that approximately 78% of surveyed employees had used personal AI tools without employer approval. He also referenced IBM's Cost of a Data Breach Report 2025, which put the average cost of a healthcare data breach at US$7.42 million.
Peng demonstrated how Google Cloud's Gemini models and centralized AI agent management capabilities can support secure deployment through access controls, data isolation, source traceability and audit logs.
A clinical handover demonstration illustrated how AI agents could retrieve authorized patient information and generate reports for professional review. Peng stressed that healthcare professionals must retain oversight and final authority over clinical decisions, with AI serving as a tool to support, rather than replace, clinical judgment.
iKala's Framework Bridges the Gap Between AI Pilots and Production
Paggie Chen, Solution Architect, AI Service Division at iKala, cited research from The Health Management Academy indicating that 83% of respondents anticipated significant value from agentic AI, while 43% had begun PoC projects or testing and only 3% had deployed AI agents in production.
To bridge the gap, Chen introduced iKala's SCOPE Framework—Select for Scale, Commit to Production, Openness, Platform and Evidence—which focuses on scalable use cases, production readiness, transparency, reusable platforms and measurable outcomes.
Chen emphasized that moving AI into production requires reliable systems, strong data governance and clearly defined human oversight, particularly in clinical settings.
Together, iKala's AI Ready architecture and SCOPE Framework provide a structured approach to moving healthcare AI beyond isolated pilots toward broader operational deployment, while maintaining security, accountability and clinical oversight.
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iKala helps enterprises make better, faster decisions by embedding AI and data at the core of their business. We support AI transformation by helping organizations move from data to decisions, delivering full AI solutions that combine their first-party data with iKala's intelligence built on billions of global social signals.
Headquartered in Taiwan with a global footprint, iKala serves over 1,000 enterprises and 50,000 brands across more than 190 countries, including Fortune 500 companies.
iKala Official Website: https://ikala.ai
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