Early last year at an event, only one in twenty hands went up when I asked a room who had AI in production. Today, that number is two-thirds. We have gone past the “pilot and prove” stage with AI. Asia Pacific (APAC) leaders now know what they want to build, and are building it.
Confluent’s 2025 Data Streaming report showed that 56 percent of APAC businesses have already deployed chatbots, copilots, and AI assistants, outpacing Europe and North America.
This is scale under pressure: not just to deliver a competitive edge, but to weather out economic headwinds, supply-chain fragility, and geopolitical risk. This approach worked in 2025, but 2026 will test businesses’ resilience even more. I expect to see four shifts that will define the world of AI and data across Asia Pacific (APAC) next year.
1. Optionality will become a strategic imperative and accelerate AI development
Agility is no longer enough. Boards across APAC are pursuing optionality: the ability to adapt, pivot, and succeed with a choice of approaches without disrupting business continuity. As global geopolitical movements continue to drive volatility across APAC, optionality is becoming as critical as cost control. Businesses, especially those with cross-border operations, will increasingly look at how they can reshore, choose vendors, and adaptively reroute their supply chains to improve their ability to manage uncertainties. Hence, I expect to see an accelerated development of AI systems that can anticipate change and act dynamically.
As competition and environmental pressures build, companies will increasingly look to embed models directly into live data streams to see what’s ahead. When context flows continuously, agents can sense change and act immediately, giving businesses true strategic options before inflection points arise.
We already see this mindset in travel. When a typhoon grounds flights, a streaming-aware agent can review seat inventory, customer history and preferences, weather en-route, then provide customers with tailored options to rebook in minutes. In 2026, this AI-driven optionality will scale across retail, logistics, and finance.
2. Organizations will need to work much harder to justify their AI projects as ROI definitions evolve
While AI adoption has surged in 2025, so has scrutiny. ROI pressure has moved from the boardroom to every business unit. Cost-control remains top-of mind for executives, many of which now prioritize ensuring measurable payback.
However, I believe 2026 will be the year boardrooms define ROI as not just amounts saved, but also growth enabled, market share captured, and possibilities unlocked. Success with AI will be increasingly defined by its impact on the company’s ability to grow and thrive, rather than survive. That will also redefine the way data streaming is evaluated: compliance automated, high agility of insights reused instantly, and decisions driven by the freshest possible data. ROI per stream will be the metric that matters.
As ROI definitions shift, boards will double down on initiatives that master continuous intelligence and quietly defund projects that don’t. To sustain momentum into 2026, AI project owners must present clear benefits and financial justifications up front.
How does investment in anti-fraud agents contribute to greater customer confidence? How will customer relationship management AI models drive greater spend? Answering these questions clearly will enable AI project owners to demonstrate how each investment moves the needle. In 2026, I expect fraud, security, and customer operations to remain the clearest ROI lanes.
3. The AI that scales will come from organizations that “eat their data vegetables”
Today’s AI landscape is still in its infancy, with most deployments seen in a “baby AI” stage: narrow in use case, fragile, and heavily supervised. The problem is scale and the way data is used. The reality is that most firms still run siloed systems that simply cannot deal with the immense volume, variety, and velocity of real-time data – the very lifeblood of AI. Our Data Streaming Report found that nearly half (49%) of APAC businesses cited insufficient infrastructure for real-time data processing as a barrier to AI adoption.
Those walls will come down as AI development accelerates through 2026. The organizations that scale successfully and drive results will be ones that “eat their data vegetables”: doing the hard but necessary work to fix data pipelines, enable continuous movement of data in real-time, and reinforce data governance.
Data integration will also define the next frontier of AI. Gaming platforms now review vast amounts of live telemetry to deliver truly personalized in-game offers down to the individual. Telcos use streaming analytics on a wealth of network data pipelines to steer bandwidth dynamically. More of such efforts will improve user experience, increase business efficiency, and strengthen competitive edge.
As AI agents become more mainstream in 2026, integration with different model context protocols and agent-to-agent standards will yield to a realization that agents are, in many respects, not so different from event-driven microservices. Rather than orchestrating complex workflows between them upfront, there is already a movement towards constructing them to react to changes in the world around them – whether those changes originate from a sensor on a container, by a user interaction on a mobile app, or by the actions of another agent.
For example, with multiple agents seamlessly communicating and collaborating with each other, marketing teams across APAC can automate more of the go-to-market process; with one agent scoring leads, another adapting outreach, another tuning outreach cadence and personalization—before potentially handing things over to a customer representative for a sense check and to drive the necessary human touch for customer assurance.
The best AI systems will ensure every domain consumes and emits live events, and the teams that fix the plumbing and “eat their data vegetables” will scale the fastest.
4. Regulation will increasingly power responsible AI in APAC, and the most localized public sector innovations will succeed
Regulation and policy are fast becoming an accelerator for AI in APAC. Singapore’s National AI Strategy 2.0 and numerous emerging AI regulatory frameworks are setting clear boundaries. More importantly, it’s defining the playing field so innovators can operate confidently within them.
The country’s Scam Analytics and Tactical Intervention System (SATIS), is one such AI-powered innovation. The system analyses hundreds of thousands of URLs daily to protect the public from scams and evolving digital threats, which exemplifies how well-designed regulation can enable AI for public good. Elsewhere in APAC, Bangkok is piloting AI-optimized traffic systems with Google’s Project Green Light to reduce congestion and emissions, while Indonesia is deploying AI platforms to tackle climate-driven diseases.
In 2026, I believe APAC’s focus on AI will begin to harmonize on common principles: safety, transparency, accountability — yet be executed in ways unique to each market. Governments will take cues from early leaders, and increasingly adopt similar guardrails. However, the success of every public-sector AI initiative will depend on how well it is tuned to local data, language, and social context.
This harmonization of principles, paired with localized execution, will drive greater regional collaboration and shared innovation frameworks. This is also why I believe APAC will be best positioned to lead in responsible AI globally. With fewer legacy systems, faster policy cycles, and a strong bias for execution, we will see APAC move from experimentation to scaled deployment of AI for public good.
2026: The year real-time AI becomes the operating reality for APAC
The volatility ahead looks much like the early COVID years: unpredictable yet full of opportunity for those built to move. The difference now is readiness.
After years of experimentation, most APAC organizations know the ingredients for scale: dependable streaming foundations, disciplined governance, and integrated platforms. The groundwork is in place. What changes next is how these systems think and act together. In 2026, those that fundamentally re-think their data strategy as strategic engines of optionality will be first to sport a sustained advantage.
Nick Dearden is Global Field CTO, Confluent.
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