From IT’s perspective, enabling the workplace means ending the chaos of disjointed apps and siloed technologies and work environments. This workplace complexity breeds fragmentation spikes where teams juggle chat, docs, and tickets while workflows stall.
One of the CIO’s critical missions in 2026 should be to restore flow: a unified system where conversations trigger actions, not more tabs. We need platforms that reduce IT firefighting by embedding knowledge, automation, and follow-through into collaboration itself.
When work moves seamlessly from talk to completion, only then can we finally stop maintaining tools and start enabling outcomes.
This is the Resolution Economy – an economic model that focuses on guaranteed outcomes, reduced fragmentation and systemic resolution beyond experience. For the IT department, the resolution economy means fewer alerts, smoother integrations, and a digital workplace that works as one.
Yet for most organisations across Southeast Asia, this vision remains stubbornly out of reach. The culprit? What Carlos Quaderi, head of Asia at Zoom, calls the “digital transformation paradox”.
The digital transformation paradox
“Despite having more technology, work is not necessarily becoming easier,” Quaderi explains. “In many cases, it has actually become more complex and led to more fragmentation and channels.”
For IT teams across the region, this fragmentation is a daily operational reality: conversations in one application, notes in another, tasks in a third, and follow-ups scattered across an ever-expanding digital estate.
The cost is not merely inconvenience. It is operational friction. Employees now spend increasing amounts of time searching, switching between contexts, and reconstructing information instead of moving work forward. This is the hidden tax of the modern distributed enterprise.
Quaderi argues that the Resolution Economy demands a fundamental shift in how we measure success. Historically, organisations measured collaboration ROI through activity metrics such as meeting counts, message volumes, and response times. But as he notes, “activity doesn’t necessarily mean productivity or progress.”
The real cost today is operational friction. In distributed environments, meaningful indicators are increasingly tied to resolution and execution: time between decision and execution, reduced workflow bottlenecks, fewer manual follow-ups, and faster movement from meetings to completed actions.
For IT leaders justifying platform investments to CFOs in 2026, this shift from activity metrics to “completion velocity” represents a far more compelling value proposition.
The ASEAN data sovereignty challenge
No conversation about workplace collaboration in Asia is complete without addressing the region’s complex data governance landscape. Governments across ASEAN increasingly view data as a core national asset. Indonesia, Singapore, Thailand, the Philippines, and Vietnam each maintain distinct regulatory frameworks, creating a defining challenge for regional CIOs, as Quaderi calls it.
“Governments are increasingly asserting control over data produced by their citizens, businesses, and public bodies,” he observes. “Geopolitical uncertainty, rapid AI adoption, and concerns around foreign technology dependence are driving stronger localisation and sovereignty requirements.”
According to recent research on China-ASEAN data flows, the region faces significant variation across six dimensions: data classification, localisation requirements, cross-border transfer mechanisms, contractual structures, privacy protection, and exceptions provisions. For CIOs operating across multiple ASEAN markets, compliance is not a single checkbox but a matrix of constantly shifting requirements.
Quaderi makes a crucial distinction: the conversation must evolve beyond simply where a service is hosted. “The more important question is increasingly becoming who controls access to the data, how it is protected, what AI is authorised to do with it, and what level of human oversight actually exists.”
He cites a sobering example:
Carlos Quaderi
“Last year, a fire at one of the South Korean data centres reportedly knocked hundreds of government services offline, partly because there was no external redundancy. The policy designed to protect the data effectively created a single point of failure.” Carlos Quaderi
This underscores a critical insight for Asian CIOs: blanket localisation can undermine resilience. The path forward requires what he describes as “technical guarantees rather than geographic restrictions alone”—strong encryption, customer-managed keys, and internationally recognised certifications such as FedRAMP and DoD IL-4.
AI governance in the agentic era
By 2026, AI agents will have become deeply embedded in workplace workflows. Gartner’s strategic predictions for the year point toward autonomous multi-agent systems reshaping customer operations and strategic execution. Yet for IT departments, the governance question looms large.
A survey of over 4,000 ASEAN knowledge workers found that 75% have already interacted with or used agentic AI at work. Critically, adoption is being driven from the bottom up: 66% of workers report that personal AI use increases their trust in workplace AI tools.
This creates an urgent mandate for IT leadership. Workers are moving faster than governance frameworks can keep pace. Only 32% of ASEAN knowledge workers say their company is training them on AI agent usage, and just 26% report investment in peer-to-peer AI knowledge sharing.
Quaderi emphasises three priorities for responsible AI governance: clear visibility into how AI systems access and use data; human oversight with configurable guardrails around automated actions; and flexible deployment architectures to support regional compliance requirements.
“Trust should increasingly be earned through technical guarantees,” he argues. Zoom’s federated AI approach—integrating with models from OpenAI and Anthropic without using customer communications to train its own models—offers a way to balance innovation with control.
“We remain committed to responsible AI,” Quaderi states, “and do not use customer audio, video, chat, screen sharing, attachments, or any other kind of communications to train Zoom’s or third-party AI models.”
Open ecosystems and the lock-in dilemma
Perhaps the most pressing concern for CIOs in 2026 is vendor lock-in. As collaboration platforms evolve into operational systems that control both conversation and execution, the risk of replicating fragmented workflows inside a new dependency becomes real.
Quaderi is unequivocal: “The risk that organisations want to avoid is replicating fragmented workflows with a new form of dependency. This is why openness and interoperability will become increasingly important.”
Citing the over 3,000 integrations available through its APIs and SDKs, he believes Zoom has built an open ecosystem designed for mixed enterprise environments. He comments that the company is not just committed to an open ecosystem but depends on it.
The future competitive advantage for collaboration platforms, he suggests, may not come from owning every workflow but from reducing friction between them while preserving customer flexibility.
This aligns with broader industry trends. IBM’s 2026 advisory practice has begun emphasising “cross-cloud compatibility” as a hedge against AI vendor lock-in, enabling organisations to run models across AWS, Google Cloud, Azure, and open-source environments without being forced to “pick a side”.
For Asian CIOs managing heterogeneous environments that include multiple productivity suites and cloud platforms, this interoperability requirement is non-negotiable.
Balancing frontline and knowledge work
The workforce in 2026 is not monolithic. Across manufacturing, logistics, healthcare, and retail, frontline workers face challenges distinct from those of knowledge workers—yet both share the same core problem: fragmented work.
Deputy’s 2026 “Big Shift” report, analysing over 41 million shifts, found that nearly 75% of frontline shift workers say AI helps them leave on time, yet 80% report that employers do not clearly communicate how AI is being deployed around them. The technology is delivering efficiency gains, but trust lags.
Quaderi argues that effective platforms will not simply connect people—they will connect the work around them and adapt to how different employees operate day to day.
“The ultimate goal is not to force frontline and knowledge workers into the same experience,” he explains. “It is to create an operational environment where communication, workflows, and follow-through happen more seamlessly across the entire workforce.”
The new security frontier
When AI systems begin pulling data across previously siloed systems—connecting messages, meetings, documents, ticketing systems, and CRMs—the security conversation expands beyond traditional boundaries. “Organisations need new governance boundaries around access, permissions, accountability, and consent,” Quaderi states.
There is also a human dimension to trust that CIOs cannot ignore. “When every conversation is transcribed and summarised, people can start to change how they actually communicate.” Preserving the ability for candid, spontaneous communication—even with AI present—may prove as important as any technical control.
For Asia’s IT leaders navigating distributed workforces, fragmented toolchains, divergent regulatory regimes, and AI adoption pressures, the mandate is clear. The Resolution Economy waits for no one. The time to restore flow is now.
Click on the PodChats player to hear Quaderi’s thoughts on the questions below.
How do we measure ROI when collaboration platforms evolve from communication hubs to operational “systems of action”?
With AI agents joining workflows, how do we govern data privacy across ASEAN’s varying regulations?
Can our current stack reduce fragmentation without forcing yet another new tool on employees?
What metrics truly indicate workflow completion velocity, not just user activity?
How should we rethink vendor lock-in when a single platform begins controlling both conversation and execution?
Will hyperlocal infrastructure (e.g., Indonesia’s data sovereignty laws) limit seamless cross-border collaboration?
How do we balance frontline worker needs with those of knowledge workers on a single integrated platform?
What new security boundaries are needed when AI “follow-through” pulls data across previously siloed systems?
