AI-as-a-Service is emerging as a new enterprise operating model, signaling a structural shift beyond traditional SaaS. As organizations across Asia-Pacific scale AI adoption, leaders are moving from application access toward intelligence-driven outcomes.
Kenneth Lai, Vice President, ASEAN at Cloudflare, explains that AI-as-a-Service represents more than an extension of SaaS. Instead of paying for software seats and user access, enterprises increasingly pay for real-time decisions, automation, and measurable outcomes delivered by AI agents.
Traditional SaaS models assume humans remain primary operators. AI-as-a-Service changes that assumption. Autonomous agents now execute workflows, streamline administrative tasks, and support real-time decision-making. Spending shifts toward inference, orchestration, and embedded intelligence rather than application licenses.
This transformation elevates the network into mission-critical infrastructure. AI agents require low-latency performance and consistent policy enforcement across regions and cloud environments. According to Lai, AI applications lose value when latency rises or when governance controls are fragmented. Embedding compute, security, and trust directly into network architecture becomes essential.
AI-as-a-Service also introduces new cybersecurity demands. Enterprises must secure autonomous systems operating at machine speed rather than protect static applications alone. Security must evaluate intent dynamically, enforce data boundaries, and provide auditability from deployment onward. As third-party and open models expand, governance gaps may increase systemic risk.
Budget priorities are expected to evolve accordingly. Cloud spending may increasingly favor AI orchestration layers and network-delivered intelligence over conventional SaaS licensing. However, procurement decisions will vary by industry. Regulated sectors prioritize trust and auditability, while consumer-facing use cases emphasize latency and cost efficiency.
AI-as-a-Service remains in an early phase, but the direction is clear. Enterprise success will depend on embedding intelligence, security, and resilient network architecture into core operations rather than layering AI on top of legacy systems.
Source:
https://www.itnews.asia/news/ai-as-a-service-emerges-as-a-new-operating-model-for-enterprises-623803
