At ATxSG, Tara Neal spoke with Dave Rizzo, President & CEO of TP Asia Pacific about the technologies driving the next phase of enterprise AI deployment. Dave highlighted the importance of agentic AI, multimodal models and human-in-the-loop governance, emphasizing that scalable AI success depends on trusted infrastructure, strong operational execution and collaborative ecosystems. He also underscored the growing need for regionally aligned compliance strategies as enterprises scale AI across global markets.
Tara: By 2026, enterprises are demanding real-world AI outcomes rather than experimentation — what technologies will define the next phase of scalable AI deployment globally?
Dave: As enterprises move beyond proof-of-concept initiatives, the next phase of AI deployment will be defined by technologies that enable operational scale, measurable business outcomes, and trusted governance. We expect to see accelerated adoption of multimodal and domain-specific AI models, agentic AI systems capable of autonomous task orchestration, and human-in-the-loop and human-on-the-loop frameworks that improve accuracy, compliance, and accountability in enterprise environments.
From TP’s perspective, the organisations that succeed will be those that combine advanced AI capabilities with strong operational execution, governance, and human expertise to drive sustainable business impact. Through TP.ai Data Services, TP enables enterprises to operationalize AI at scale with end-to-end support spanning data collection, annotation, model evaluation, and human-in-the-loop and human-on-the-loop governance for trusted, real-world deployment.
Tara: How are cloud, AI, edge, and telecom infrastructure converging, and what new ecosystem partnerships will become critical over the next five years?
Dave: The convergence of cloud, AI, edge computing, and telecom infrastructure is fundamentally reshaping how digital services are delivered and consumed. As AI workloads become increasingly data-intensive and latency-sensitive, enterprises are looking to process and analyse information closer to the source — whether in connected factories, smart cities, autonomous systems, or customer engagement environments. This is driving tighter integration between hyperscale cloud providers, telecommunications operators, AI platform companies, and digital services partners.
TP is seeing increasing demand for integrated ecosystems that combine AI technology with operational delivery, multilingual capabilities, trust and safety services, and human expertise. The future will belong to collaborative ecosystems that can help enterprises deploy AI responsibly while maintaining agility, resilience, and customer trust across global markets.
Tara: As AI regulation and digital sovereignty frameworks expand worldwide, how should technology providers adapt their solution architecture, product strategies and go-to-market models?
Dave: As regulatory frameworks evolve globally, technology providers must embed trust, transparency, and compliance into every stage of the AI lifecycle. This means moving beyond a “deploy first, govern later” mindset toward AI architectures that are secure, explainable, auditable, and adaptable to local regulatory requirements.
We expect organisations to increasingly adopt regionally aligned infrastructure strategies, including sovereign cloud models, localized data governance frameworks, and market-specific compliance capabilities. Providers will also need stronger human oversight mechanisms particularly in areas involving sensitive data, customer interactions, and high-impact decision-making.
TP believes human-in-the-loop and human-on-the-loop governance, multilingual operational expertise, and locally informed delivery models will become increasingly important as organizations navigate a more fragmented and regulated digital landscape. Many organizations still lack the operational backbone and data services expertise required to run AI effectively at scale; particularly when issues arise in real-time, across markets, languages, and regulatory environments. That is the gap TP fills through its end-to-end AI and TP.ai Data Services capabilities.
Tara: 4. Looking ahead, which emerging technologies — from agentic AI to quantum, spatial computing, or autonomous infrastructure — are most likely to reshape industries at scale?
Dave: Several emerging technologies have the potential to significantly reshape industries over the coming decade, but their impact will depend on how effectively organisations can operationalise them at scale. Quantum and spatial computing will play important but more contained roles, concentrated in specific domains and over longer time horizons. In the near term, agentic AI is likely to drive the most immediate transformation by enabling systems that can automate workflows, coordinate tasks, and augment human decision-making across customer operations, IT management, cybersecurity, and enterprise productivity.
Ultimately, the organisations that realise the greatest value from these technologies will be those that balance innovation with governance, operational readiness, and human expertise. TP believes the future of technology transformation will continue to be driven by the combination of AI and human intelligence working together to create more resilient and customer-centric businesses.