Every year, TechTrade Asia compiles a year-end roundup, and a set of predictions for the next year. These were the posts that appeared at the end of 2025, and into early 2026, with comments on AI dominating.
Gavin Barfield, VP and CTO, Solutions, Salesforce ASEAN said: "We’ve only just begun to discover where and how AI can be applied, and it is clear that there is much untapped potential with the technology. Businesses cannot afford to 'wait-and-see' and must proactively establish systems, procedures, and infrastructure that allow them to seize the AI opportunity."This includes establishing a strong foundation of unified, trusted data to ensure that AI can deliver accurate, relevant, and actionable outputs. Crucially, businesses will need to remain open to constant experimentation and move with agility to capitalise on the latest AI advancements, or risk being left behind."
"Governments across the region are investing heavily in sovereign AI infrastructure as AI becomes a foundation of national competitiveness. Compute, data, and AI pipelines are increasingly treated as strategic assets that must be locally governed and secured. As more AI workloads operate inside domestically controlled compute zones, the need for quantum-safe communications, AI runtime security, and consistent application delivery frameworks becomes increasingly important," said Mohan Veloo, CTO, Asia-Pacific, China & Japan, F5.
Timeline 2025
Monthly highlights were also published in 2025:
Corporate highlights in 2025
2025 landscape
Marketing and advertising trends
Thales, the global technology and security provider, noted that despite the hype surrounding AI and quantum driving billions in new spending, the most severe breaches in 2025 were caused by fundamental failures such as poor credentials, continued use of legacy security software, and misconfiguration.These observations align with the 2025 Thales Data Threat Report, which also pointed out that some organisations are not waiting to get their security or technology houses in order before departing on their AI journey, as the urgency to move into transformation is superseding improvements to organisational readiness.
"For much of 2025, discussions around AI agents largely centred on theoretical potential and early prototypes. But by Q4, agentic behaviours began appearing in production systems at scale: models that could fetch and analyse documents, interact with external APIs, and perform automated tasks. These agents offered obvious productivity benefits, but they also opened doors that traditional language models did not," said Mateo Rojas-Carulla, Head of Research for AI Agent Security, Check Point Software.
"Our analysis shows that the instant agents became capable of interacting with external content and tools, attackers noticed and adapted accordingly. This observation aligns with a fundamental truth about adversarial behaviour: attackers will always explore and exploit new capabilities at the earliest opportunity. In the context of agentic AI, this has led to a rapid evolution in attack strategies."
"In 2026 and beyond, the organisations that succeed with agentic AI will be those that treat security not as an afterthought, but as a foundational design principle."
Manufacturing security in 2025
Cloudflare's Internet trends for 2025
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| Concept artwork generated for tech predictions in 2026 by Google Gemini Flash 2.5. |
The sneak peek, starring agentic AI
"The next wave of AI will focus on systems that act and learn on their own, not just generate content," said Elaine Chan, Director and APAC Head of AI Sales & GTM, NetApp.
"These systems will depend on fast, trusted access to well-governed enterprise data across hybrid environments. Unified data models, AI application integrations, and AI engines...will help empower this wave both on-premises and in the cloud, including unique integrations with hyperscalers, sovereign clouds, and neoclouds."
"Architecture that enables independent scaling of performance and capacity will make this possible, ensuring flexibility and efficiency across AI environments," Chan added.
Digital transformAItion, 2026-style
"The old way of buying software (SaaS) meant paying a monthly fee for every employee ("seats") to use a set of fixed features, with all their data locked in a central silo. That model is breaking. In 2026, the focus will shift to AI-as-a-service. Companies will demand software that is smart, real-time, and customised. They will pay for the actual intelligence and insights the AI provides, not the right to use the program," said Kenneth Lai, VP, ASEAN, Cloudflare.
"This move pushes smart AI assistants to the forefront and requires keeping sensitive data secure and close to home. While SaaS won't disappear, its dominance will end as AI agents become the primary interface for enterprise workflows."
"Enterprises are beginning to realise that the future of AI lies not in models that attempt to do everything, but in specialised, right-sized, and explainable systems designed for specific industries and workflows," said Guna Chellappan, GM for Singapore, Red Hat."Business leaders will need to rethink their infrastructure strategies to support more diverse and demanding AI workloads. We will see growing interest in unified inference layers that can support a wide range of AI models without compromising performance and cost efficiency.
"At the same time, there is strong momentum around connecting enterprise application platforms with cloud-based AI accelerators, giving organisations a more seamless way to operationalise AI at scale. By pairing flexible platforms with specialised computing, enterprises can accelerate the shift from pilots to producing measurable business impact."
"Ultimately, 2026 will be the year enterprises recognise that AI ROI is inseparable from modernisation. Those that invest in resilient infrastructure, robust data foundations and secure-by-design AI operations will move from pilots to production — and turn AI ambition into measurable business impact," said Andrew Lim, MD, Kyndryl ASEAN & Korea.
"2026 will mark the arrival of agentic systems: AI that acts with autonomy and intention. In this model, agreements evolve into active components of business execution, said Kartik Krishnamurthy, VP Asia, Docusign.
"Imagine a master services agreement that continuously monitors purchase orders in an ERP system. When an order deviates from agreed pricing, the system intervenes immediately to stop the transaction, alert stakeholders, and enforce compliance.
"Across Asia, enterprises will increasingly rely on AI agents to manage high-stakes, high-volume functions such as supplier compliance and cross-border data governance. The scale and speed of regional commerce have outgrown human-only workflows."
The bad data problem that could worsen in 2026
"As AI tools become easier to build and increasingly interchangeable, the real advantage shifts to the quality, connectedness, and trustworthiness of the data behind them. Early adopters already prove this: 92% are seeing ROI from AI, yet many still struggle with fragmented systems and data that isn’t ready for machine learning. The biggest gains now belong to the companies that fix the foundation, not the ones chasing the flashiest model," said Satchit Joglekar, MD, ASEAN, Snowflake."The winners are those that master the 'data flywheel': unique data fuels AI, smarter AI produces even more unique data. This cycle builds a lasting competitive edge. In a region as dynamic and digitally driven as Southeast Asia, this shift will redraw competitive lines fast."
"In a world where AI tools are becoming commodities, the real advantage goes to enterprises that prioritise data quality, accessibility and identifying use cases with clear business impact," Joglekar added.
Martin Creighan, VP, Asia Pacific at Commvault said: "In 2026, enterprises will recognise that AI initiatives stall not from lack of data, but from the inability to safely access and prepare the data they already have. Across APAC, multiple surveys show that data quality, security, and governance – not enthusiasm for AI – are the primary bottlenecks to scaling projects beyond pilots, with many organisations citing fragmented data estates and compliance concerns as the main reasons initiatives slow or stall."
Creighan said that historical data will be reframed from 'backup insurance' to a strategic intelligence asset, if activated responsibly. "This will accelerate the rise of sovereign, resilience-aware data rooms – secure environments that connect governed backup data directly to AI platforms and data lakes without risky, ad-hoc workflows. By providing controlled, self-service access with built-in classification, lineage, and compliance, data rooms will turn protected data into clean, compliant, AI-ready fuel that can power analytics and AI without breaching local data protection rules."
"As we move into 2026, the stakes for getting data foundations right have shifted dramatically in Asia Pacific. AI has already moved beyond proof-of-concept, with AI-related investments in Asia/Pacific expected to grow 1.7x faster than overall digital technology spending, according to IDC," said Amitabh Sarkar, VP & Head of Asia Pacific and Japan - Enterprise at Tata Communications.
"Data remains the first bottleneck and the biggest multiplier. Organisations will need to invest early in data governance, quality management and building a single source of truth across silos. This will go hand-in-hand with investing in the right digital infrastructure: environments that are elastic, scalable, performant, and able to support the heavy compute demands of AI across cloud and edge.
"As more real-time use cases emerge, we will see a stronger push toward processing data closer to where it is generated, reducing latency and improving the speed of insight."
"Equally important is culture. AI programmes only succeed when people understand how to work with these systems — when there is clear ownership, the right skills in place, and a mindset that encourages experimentation, learning and responsible use," Sarkar added.
Jobs in AI: what makes the cut
AI cybersecurity in 2026: the state of play
"The cyberthreat landscape is evolving faster than ever, especially as businesses accelerate cloud adoption, hybrid working, and digital transformation. It is clear that simply having perimeter defences is not enough. Cybersecurity is no longer the sole responsibility of IT teams, but a shared accountability across the enterprise. To thrive in this environment, businesses must embed Zero Trust principles, strengthen identity protection with multifactor authentication, and adopt continuous monitoring to detect and contain threats before they escalate. Just as important is cultivating a cyber-aware culture where employees serve as the first line of defence," said Adhil Badat, MD, Asia Pacific and Japan, Rackspace Technology."In our region, where regulatory expectation, such as PDPA in Singapore, and cross-border data flows are increasingly complex, the imperative is to embed security into every workload, every cloud, and every user interaction. Solutions like always-on monitoring, cloud posture assessments, and Zero-Trust architectures are no longer optional. Enterprises that integrate these into their core digital strategy will not only reduce risk, but build customer trust, strengthen brand credibility, and unlock innovation in a secure manner."
AI cybersecurity in 2026: the attack and defence playbook
Lee Anstiss, Regional Director, Southeast Asia and Korea, Infoblox said that in 2026, APAC’s cyber landscape will be defined by systemic, AI-driven threats that outpace legacy defenses, demanding a shift to proactive strategies and continuous monitoring to build resilience."The industrialisation of crime will make attacks more frequent and sophisticated, as plug-and-play exploit kits, darknet 'as-a-service' offerings and AI tools make hacking accessible to everyone," Anstiss said.
"As AI governance and regulations in APAC remain fragmented, CISOs and business leaders must invest in internal frameworks to securely manage AI agents and train internal teams against personalised scams like deepfakes. Reinforcing foundational and often overlooked network weaknesses, such as the domain name system (DNS) will continue to be critical. Protective DNS services, enhanced by machine learning and real-time analysis, can block malicious domains before hackers can even get close and will soon be mandatory in critical sectors."
AI cybersecurity in 2026: ensuring the show goes on
AI cybersecurity in 2026: deepfakes to become more menacing
AI cybersecurity in 2026: a broader attack surface with agentic AI
App development in 2026: code? What code?
Marcus Low, VP and MD, Asia-Pacific and Japan, Sonar, said that AI-assisted software development will drive workforce recalibration in APJ. "Following widespread tech sector layoffs, 2026 will mark a recalibration of the region’s digital workforce. As AI lowers the barriers to entry in coding, software development is becoming more accessible to professionals beyond traditional engineering backgrounds," he said.
"AI-assisted tools can now generate, test, and refine code through natural language prompts – allowing individuals with minimal coding experience to upskill quickly and contribute to digital product creation."
"This democratisation of software development presents a major economic opportunity for APJ, where countries such as India, China, and Indonesia are investing heavily in digital skilling and innovation ecosystems. With this, we’ll also see more of a focus from the volume of AI-generated code to the verification of its output. By 2026, the ability to collaborate with AI in software development, rather than compete against it, and focus on verifying its output, will be a defining skill for employability and growth in the region’s evolving tech economy."
App development in 2026: how teams could evolve
The 2-Z of 2026 tech predictions
2 is for 2-factor authentication (2FA)
D is for distributor (and the entire channel ecosystem)
Mei Dent, Chief Product & Technology Officer, TeamViewer said: “While AI agents are already being deployed for practical, everyday tasks, wider autonomous adoption is being held back by governance rather than technology."In 2026, organisations that succeed with AI will be those that prioritise data governance, change management and business process transformation, rather than focusing solely on technical readiness. As AI agents move towards intent-based execution across more complex workflows, companies will need to rethink how their processes, data and operating models support autonomy at scale.”
H is for hybrid cloud, multicloud, and all flavours of cloud
I is for the Internet of Things (IoT)
L is for large language model (LLM)
Matthew Oostveen, VP & CTO, Asia Pacific & Japan, Pure Storage said that 2026 marks the shift from AI models mining the open Internet to unlocking untapped internal data. "By 2026, we’ll reach peak value from publicly available data, as AI models extract the last drops of signal from the open Internet. The next wave of AI progress will depend as much on discovering untapped data as on refining algorithms," he said.
"Organisations will turn inward, racing to unlock data long trapped in legacy systems, mainframes, on-prem databases, and unstructured silos; though privacy and governance hurdles will slow progress. Synthetic data will emerge as a critical enabler, offering safe, scalable ways to train and test models without exposing sensitive information. Financial services will lead in simulations and risk modelling, while healthcare and other regulated sectors tread carefully. 2026 will mark an inflection point: a shift from mining what’s public to reimagining and reclaiming the hidden data within every organisation."
M is for machine-to-machine (M2M)
Seagate’s EVP & Chief Commercial Officer, BS Teh, said that one of the most under-recognised shifts is the return of AI workloads back to enterprise environments.
"Global research shows 80% of organisations have already repatriated or are planning to repatriate AI workloads, driven by cost, compliance and performance needs. In Singapore, where tightly regulated sectors anchor the digital economy, data gravity is increasingly pulling compute closer to where data resides. The priority now is storage that is high-density, energy-efficient and built for low-latency hybrid AI — enabling organisations to keep sensitive data local while scaling AI safely and economically,” he said.
Ee Khoon Oon, VP & MD, APAC, Jumio, said agentic AI and fully-automated cross-border digital transactions could cause problems. "Imagine an AI agent hosted in Singapore reallocating savings into a Thai equity fund, or executing a digital asset purchase in the Philippines. If the user disputes the outcome, the argument 'my AI did it — not me' will not stand in court or in front of regulators," Oon said.
"Liability will still fall on humans or institutions. Regulators will demand verifiable proof of who authorised the transaction and whether the AI remained within its approved mandate. This is where the region’s identity framework must evolve. Traditional KYC (know your customer) is no longer enough in a world of autonomous AI. Institutions will need to adopt KYA — know your agent."
Oon observed that Singapore is already signalling how this should work. "The Monetary Authority of Singapore (MAS) has strengthened its stance through the FEAT principles, the Veritas initiative, and most recently the AI Risk Management Guidelines, which emphasise governance, human accountability and rigorous controls across the AI lifecycle. The message is clear: autonomy cannot exist without oversight," she added.
"In the future, every authorised AI agent will need its own verifiable identity, bound directly to a human’s proven biometric. This creates a secure, traceable chain of custody — from a person’s intent in Jakarta to an AI agent’s execution in Hong Kong — that can withstand regulatory scrutiny across borders. Far from slowing innovation, this strengthens trust, enabling the region’s digital economy to scale confidently and safely."
"The winners in APAC’s next phase of digital transformation will not be the fastest movers, but the most trusted. As AI becomes an active participant in financial and commercial life, the ability to anchor every autonomous action to a verified human will be the foundation of digital trust for the next decade," Oon concluded.
U is for usage limitations (aka data sovereignty)
- Fast-moving consumer goods (FMCG)
"Governments around the world will increasingly pursue 'sovereign AI' solutions to ensure control over data and compute resources within their borders, driving the creation of national AI ecosystems and regional data centres," said Vrushali Sawant, Data Scientist, SAS Data Ethics Practice.See also
V is for verticals in 2026: finance
V is for verticals in 2026: logistics
V is for verticals in 2026: retail
The high cost and poor performance of rigid, all-in-one platforms will drive a dramatic architectural shift in conversational AI across APJ, said Christopher Connolly, Director of Solutions Engineering, Twilio."With 81% of APJ directors finding it costly to keep up with rapidly evolving models, brands can no longer afford to maintain monolithic systems that age quickly and necessitate expensive, frequent overhauls. This urgency is compounded by critical performance failures at the local level.
"Most AI solutions fail to meet the diverse linguistic needs of the region: for 40% APAC consumers, AI agents created a conversational barrier by failing to understand their accents over the phone. In addition, 41% of APAC consumers encountered AI agents that were unable to support their language—either written or spoken."
Connolly said brands will decisively move towards adopting modular, plug-and-play systems that are easier to update, cheaper to run, and better equipped to meet the nuanced local language expectations to mitigate the twin pressures of cost and performance.
"This approach supports bring-your-own-LLM (BYO-LLM), giving brands the flexibility to swap out models cost-effectively, avoid vendor lock-in, and integrate specialised AI tailored for local languages and accents."
"In 2026, APJ is poised to export groundbreaking AI innovation worldwide, marking a definitive maturation of its role in the global technology landscape. This signals a shift in the region from being primarily an adopter of global solutions to becoming a developer and exporter of technology," said Amit Khandelwal, Regional VP and MD for Southeast Asia, UiPath.
"APJ’s rise in the global AI landscape can be attributed to the collective strengths of its diverse markets. India is establishing itself as the world’s R&D engine, powered by a vast developer base and a growing network of over 1,950 global capability centres (GCCs). Previously functioning as support centres for back-office processes, GCCs are transforming into strategic hubs that drive innovation, research, and digital transformation. Many are now responsible for building and exporting global AI solutions, solidifying India’s pivotal role in the global tech landscape.
"In Southeast Asia, agile startup ecosystems in places like Singapore, Vietnam, and Indonesia are serving as real-world sandboxes for AI-first applications. This fast-paced, dynamic environment is fuelling rapid innovation, reshaping diverse industries with AI-driven solutions. Meanwhile, Australia is establishing itself as a valuable testbed for developing and scaling AI solutions across sectors, while (mainland) China’s leadership in AI patents, Taiwan’s semiconductor chips dominance, and Japan’s advanced R&D infrastructure are anchoring innovation at a global scale. These established powerhouses provide the deep expertise and resources needed to push the boundaries of AI technology."
APAC stands for the Asia-Pacific region. APJ refers to Asia-Pacific and Japan, while PDPA is an acronym for Personal Data Protection Act. SaaS stands for software-as-a-service.
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