2025 can be seen as a year of implementation, where the tech industry in APAC and globally focused on translating the potential of emerging technologies into performance and real-world value.
AI in particular, has fuelled transformative changes for businesses the past year, from back and front office applications, product development to products and services.
At the same time, organisations have had to navigate a more complex risk environment, marked by escalating cybersecurity threats, geopolitical tensions, and growing sustainability pressures. The surging demand for compute-intensive workloads, especially from Gen AI and immersive environments, is creating new demands on the tech infrastructure.
Yet significant challenges persist. Competition for critical technologies, data-centre power limitations, physical network weaknesses, multi-cloud complexity, and rising identity-based cyberattacks continue to expose infrastructural vulnerabilities. Non-technical barriers such as supply-chain delays, talent shortages, and regulatory uncertainty have also hampered deployment timelines.
To shed light on the year’s key developments and explore what lies ahead, we spoke with industry leaders and technology experts who shared their perspectives on the changing landscape and the opportunities shaping 2026.
- Tee Jyh Chong, SVP, Asia Pacific, Alcatel-Lucent Enterprise (ALE)
- Rodney Kinchington, Managing Director, Asia-Pacific, Japan and Greater China, BT International
- Peter Marrs, President, Asia Pacific, Japan & Greater China, Dell Technologies
- Frederic Giron, VP, Senior Research Director, Forrester
- Kim Jaeseung, Regional CEO, Asia Pacific, LG Electronics
- Glenn Neo, CTO and COO, Asia Pacific, Logicalis
- Elaine Chan, Director and APAC Head of AI Sales & GTM, NetApp
- Peter Marelas, Senior Director of Product Management, New Relic
- George Lee, Senior Vice President, Asia Pacific & Japan, Proofpoint
- Simon Davies, President, Asia Pacific, SAP
- Ivy Xin, Vice President for Secure Power and Data Centre Business, East Asia, Schneider Electric
- Nick Smith, General Manager APAC, Smart Communications
- Malis Selamat, Managing Director for ASEAN, Greater China, and Korea, Sophos
- Andy Zollo, Senior Vice President, Application & Data Security, Thales
iTNews Asia: Looking back at 2025, in your perspective, what was the most significant development for the industry? Which frontier technology has made the most breakthrough?
Neo (Logicalis): This year’s biggest development remains AI, with alternatives to large language models, open standards, and innovative licensing emerging. As AI experimentation grows, so does demand for infrastructure and computing power, driving investment. Mission-specific AI applications like compliance and fraud detection in finance, or diagnostic imaging in healthcare are now delivering measurable results.
Jyh Chong (ALE): We can all agree that AI dominated the past year, but more importantly, it marked a period of rapidly rising global AI investment. We have moved beyond the hype, entrusting critical operations like network monitoring to AI agents. Their ability to detect, predict, and mitigate anomalies in real time has reshaped IT operations, helping teams secure increasingly complex infrastructures and turn risks into manageable, automated workflows.
Kinchington (BT International): The biggest development in 2025 was the large-scale integration of AI into global networks. AI was applied to optimise performance, strengthen cyber-defence and automate connectivity across cloud, edge and data-centre environments.
We also saw networks become more programmable and on-demand as CIOs navigated disruption from AI, geopolitics and rapid digitalisation.
This year marked AI’s shift from experimentation to real operational intelligence improving visibility, resilience and agility as organisations demanded instant, secure access to data across regions.
- Rodney Kinchington, Managing Director, Asia-Pacific, Japan and Greater China, BT International
Marrs (Dell Technologies): This year, unified AI platforms supporting AI agents have driven a shift from pilots to large-scale operational integration, embedding multi-agent systems across finance, HR, and IT. While agentic AI is still nascent, the breakthrough is in scaling AI with proper service-level objectives and lifecycle management.
There is a growing consensus that AI and humans will work synergistically, moving toward autonomous AI under human oversight - a strategic alignment set to become a reality in the near future.
Jaeseung (LG Electronics): AI advanced towards more human-cantered, multimodal capabilities, driving major industry shifts. A key development was the rapid expansion of AI-focused data-centre capacity, fuelled by higher-density compute and adoption of liquid and hybrid cooling. As AI delivers real-time reasoning across text, voice, vision, and sensor data, energy usage and environmental impact have become critical.
Zollo (Thales): The most significant development was the rise of what we can call ‘Automated Attack Innovation’. For the first time, automated bot traffic surpassed human activity, with AI-driven bots now accounting for 51 percent of all internet traffic, and more than a third of that automated traffic is malicious. As AI tools become more accessible, cyber criminals are increasingly leveraging them to create and deploy malicious bots.
Organisations are already investing in AI-specific security tools to counter this new wave of automated, AI-enhanced threats. They also need to strengthen organisational readiness in areas like governance, data protection and AI-specific threat modelling.
Marelas (New Relic):
2025 marked AI adoption at true enterprise scale. Organisations built dynamic digital ecosystems with data pipelines, models, and automated workflows, requiring intelligent observability.
- Peter Marelas, Senior Director of Product Management, New Relic
The observability graph - a real-time map of every service, dependency, and interaction replaced traditional Configuration Management Databases (CMDBs), giving enterprises unmatched visibility, faster diagnostics, and contextual intelligence to support AI-driven operations.
Xin (Schneider): 2025 has reinforced a critical lesson for the data centre industry: scalability, sustainability and resilience must progress together. Generative AI and high-performance computing are pushing power densities to new highs, creating challenges in energy efficiency and cooling.
Traditional cooling methods are no longer sufficient, and liquid cooling has become essential for maintaining density and performance while reducing energy and water consumption.
Chan (NetApp):
2025 is the year AI moved from “what if” to delivering real value. Organisations needed to automate data curation, vectorisation, and access to train, tune, and operationalise AI at scale, supported by intelligent data infrastructure.
- Elaine Chan, Director and APAC Head of AI Sales & GTM, NetApp
The real game-changer is Agentic AI that reason and execute complex tasks, turning data into an active decision-maker.
Lee (Proofpoint): The most significant development in 2025 was the emergence of agentic AI and continued industry consolidation, both transforming how organisations stay resilient against fast-moving threat actors. At the same time, organisations have faced significant struggles from unmanaged AI usage and data exposure.
Giron (Forrester): Humanoid robotics was 2025’s standout breakthrough, with APAC factories deploying robots that walk, lift, and collaborate alongside workers, enabled by cheaper hardware and adaptive “physical AI.” Automation is now a flexible workforce.
Equally important, technology strategy became inseparable from sovereignty: export controls, data localisation, and supply chain issues pushed firms to diversify cloud providers, secure semiconductor access, and embed compliance into innovation.
For CIOs, 2025 was the year "optionality" moved from jargon to imperative: leaders who built flexibility into their architecture and operating models are now able to act.
- Frederic Giron, VP, Senior Research Director, Forrester
Selamat (Sophos): In cybersecurity, generative AI (Gen AI) is both a threat and a tool. Cybercriminals use it to speed up attacks, while defenders use it for detection, automation, and scalability. Its real promise lies in alert triage, helping human analysts through smart automation.
We may also see AI automating bug discovery and improving phishing detection before code or emails reach users.
Davies (SAP): 2025 is the year AI moved from hype to reality. The frontier of enterprise innovation has become AI, driving business processes and outcomes. Research showed that the average company in APAC is already driving 16 per cent ROI from AI, a figure which will double in the next two years. Companies like Olam Food Ingredients, Singapore Airlines and Bank Danamon are already working with SAP and using AI in their contract processing, supply chain innovation and in skilling and recruitment.
Smith (Smart): Many organisations found AI more complex than expected, especially for multi-step business processes. Simple tasks are manageable, but complex workflows like mortgage applications involve many inputs and decision points, where errors can occur.
The human element remains essential. In customer experience, you can’t control individual reactions, so a framework that lets customers engage on their terms is crucial.
- Nick Smith, General Manager APAC, Smart Communications
iTNews Asia: What do you think was the greatest challenge or challenges faced by your customers or businesses in 2025? How are they being resolved?
Marrs (Dell Technologies): The biggest challenges for businesses are organisational readiness and AI integration, with outdated infrastructure, skills gaps, and proving clear ROI remaining key concerns. To address this, enterprises are focusing on AI use cases tied to revenue, cost, or risk, investing in workforce readiness and AI literacy, and fostering human-AI collaboration.
Modernising infrastructure while ensuring data sovereignty is also a priority, supported by cross-functional teamwork and strategic ecosystem partnerships.
Neo (Logicalis):
A key challenge has been demonstrating tangible value from AI investments. While generative AI and multi-model platforms empower innovation, they remain costly and often fail to transform workflows and workforce effectively.
- Glenn Neo, CTO, COO, Asia Pacific, Logicalis
Many projects also lack clear success criteria. Workforce concerns are rising, and we are seeing the media highlighting job reductions linked to AI adoption.
Jyh Chong (ALE): From our conversations with customers, complexity remained a major headache, from supply chain friction and identity-based cyber threats to power and talent constraints.
Many turned to As-a-Service (XaaS) models as the answer. Adopting subscription-based consumption like NaaS and CPaaS, enabled businesses to bypass supply chain delays, avoid heavy CAPEX and gain the agility needed to modernise infrastructure without carrying the full burden of physical assets.
Kinchington (BT International): Managing the pace and complexity of change was a big challenge. AI adoption surged, geopolitical tensions disrupted data flows, and digitalisation intensified across industries. As a result, organisations struggled with secure, instant access to data across regions, maintaining interoperability and sovereignty, and managing resilience in increasingly distributed environments.
This is why they now seek partners that operate securely and at scale, yet deliver cloud-like agility: open by design, API-integrated and available on demand to help them navigate ongoing disruption.
Chan (NetApp): For many of our customers, the challenge was building resilient businesses amid geopolitical volatility and evolving regulations. They were chasing growth and productivity, whether faster drug discovery in healthcare, or digital twins in manufacturing, while complying with cybersecurity demands. At the same time, the shift to agentic AI made building these systems much more complex.
Marelas (New Relic): Digital resilience was a major challenge in 2025. Global outages caused by multinational cloud providers and security firms demonstrated how interconnected and fragile the digital ecosystem is, and laid bare the financial implications of these high-impact events.
Without intelligent observability to flag issues proactively, revenue and trust are at risk. A comprehensive observability strategy is essential for organisations to stay proactive and resilient in 2026 and beyond.
Lee (Proofpoint):
In 2025, our customers faced a surge in AI-enabled attacks that grew sharply in both volume and sophistication. CISOs remain concerned about human-centred risks, from insider threats and AI governance gaps to security team burnout.
- George Lee, Senior Vice President, Asia Pacific & Japan, Proofpoint
With new vectors emerging, including human-like AI agents, organisations must strengthen multilayered, human-centred defence strategies to address risk at its source.
Giron (Forrester): In 2025, the biggest challenge was turning GenAI and agentic AI hype into real business outcomes, revealing gaps in skills, governance, and risk culture. Leading firms reframed risk as a competitive advantage by aligning AI with strategic goals, fostering a culture of reinvention, embedding adaptive operating models, upskilling for AI fluency, and treating governance as an innovation driver. This mindset, not the technology itself, distinguished winners from laggards.
Jaeseung (LG Electronics): Keeping pace with rapid AI adoption while managing heavy infrastructure demands is difficult. As multimodal AI workloads scaled, organisations faced higher energy costs, capacity constraints, and sustainability pressures.
Davies (SAP): In a competitive, cost-focused environment, driving value from AI hinges on data. AI is only powerful with contextual, integrated data from connected enterprise applications. APAC companies struggle with incomplete or poor-quality data, highlighting that robust data governance and integration are as crucial as investing in AI itself.
Xin (Schneider):
A major challenge has been supporting high-density computing. AI processors demand far more power and generate significantly more heat, creating both physical and operational constraints.
- Ivy Xin, Vice President for Secure Power and Data Centre Business, East Asia, Schneider Electric
Air cooling alone no longer suffices, and operators are turning to liquid cooling to maintain performance without compromising density or latency.
While liquid cooling delivers clear benefits, it also brings new complexities. Resolving such a challenge requires a commitment to innovation and collaboration.
Zollo (Thales): Cloud complexity continues to be a major issue for our customers. This complexity fuelled a global surge in identity-based attacks, with 44 percent of advanced bot traffic now specifically targeting APIs to exploit these gaps.
Businesses are resolving this by moving from siloed security practices to operational resilience. By consolidating tools to gain visibility and accepting that perfect prevention is impossible, organisations are focusing instead on continuity and the ability to resume business and productivity afterwards.
Smith (Smart): On the journey to seeing how AI will work for a business, it’s important to step back and look at the foundations. Customers aim to create automated, connected journeys, but projects stall without clean data, simple workflows, and a flexible tech stack. Integrated ecosystems are replacing fragmented workflows, breaking down silos to deliver seamless, scalable communication.
Selamat (Sophos): Burnout among cybersecurity professionals is widespread. This exhaustion was due to higher cyberthreat activity, heightened regulatory demands, and resource shortages. Burnout degrades staff productivity and cybersecurity stance.
A resource shortage, for instance, hinders firms’ attempts to rein in shadow AI and mitigate associated threats. Organisations are now turning to AI-augmented tools to help teams detect threats and respond faster.
- Malis Selamat, Managing Director for ASEAN, Greater China, and Korea, Sophos
iTNews Asia: What lessons have we learnt in the past year and what do you think 2026 will look like? Will AI really take off? Or will it take more experimentation and guidelines for safety, data privacy and governance to be resolved before its potential can be fully realised?
Giron (Forrester): This year showed that AI adoption isn’t the bottleneck but organisational reinvention is. While knowledgeable workers use AI to write faster, brainstorm better, and tackle harder problems, these gains rarely appear on balance sheets.
Many enterprises deploy tools without rethinking workflows. In 2026, mature organisations will operationalise safety and privacy while transforming.
Jaeseung (LG Electronics):
2025 showed that AI’s progress relies not just on advanced models, but on responsible integration, governance, and sustainable infrastructure.
- Kim Jaeseung, Regional CEO, Asia Pacific, LG Electronics
Scaling AI works best with clear safety practices, transparent data stewardship, and efficient, high-density data centres.
In 2026, adoption will accelerate, depending on mature ecosystems, reliable infrastructure, and energy-efficient operations.
Neo (Logicalis): In 2026, mission-specific AI will deliver tangible value, while general-purpose generative AI adoption grows, with impact depending on cost, scalability, and moving from experimentation to production.
Humans and AI will collaborate more seamlessly, unlocking new ways of working. AI safety and governance will tighten, with robust policies, compliance, and monitoring, tracking model drift and neutralising cyber threats.
Zollo (Thales):
An important takeaway for the past year is that compliance can be an organisation’s best predictor of security.
- Andy Zollo, Senior Vice President, Application & Data Security, Thales
We found that 78 percent of organisations that failed a compliance audit often have a history of data breaches. At the end of the day, deploying complex technology does not remove the need for basic safety measures; in fact, ignoring these basics remains a leading cause of exposure.
Chan (NetApp): The key lesson is not to be carried away by AI hype. AI is only as smart as the data it uses. We are moving toward industrialised AI where trust and safety are not conceptual afterthoughts. Success will not just be measured by speed anymore, but with governance and sovereignty.
Marrs (Dell Technologies): As enterprises scale AI, the focus will remain on keeping it human-centric, with autonomous systems that collaborate seamlessly with humans to boost productivity and unlock creativity.
Lessons from 2025 show that success requires strategic governance of AI investments, leveraging existing ecosystems, and prioritising ROI-driven use cases. This approach, combined with robust safety and governance guidelines, will push businesses to realise the full potential of AI.
- Peter Marrs, President, Asia Pacific, Japan & Greater China, Dell Technologies
Kinchington (BT International): A key lesson from 2025 is that networks are moving from fixed, provider-led connectivity to a programmable, on-demand fabric. By 2026, more organisations will adopt a cloud-like model where connectivity is provisioned, scaled, and secured instantly, with routing, performance, and security unified.
AI will continue to advance, but its potential depends on a network foundation built on the core outcomes customers prioritise today - stability, security, scalability, skills and sovereignty - supported through a true NaaS model.
Marelas (New Relic): The key lesson is that AI in production needs deep operational understanding. Without system visibility, trust, performance, and governance suffer.
In 2026, the differentiator will be intelligent observability involving real-time system graphs, autonomous AI agents, and human oversight. This shifts observability from a cost to a value driver, reducing outages, optimising cloud use, and enabling faster decisions.
Davies (SAP):
Two key lessons stand out: invest in integrated technology and in people. A patchwork of best-of-breed apps no longer suffices. AI demands integrated, embedded access to data that can only come from a suite-first strategy.
- Simon Davies, President, Asia Pacific, SAP
The key for 2026 will be empowering people to drive tangible value from AI especially with new developments like agentic AI. That means investment in skilling, in ecosystem partners, and in empowering people to augment their roles to focus on higher value work.
Lee (Proofpoint): The key lesson is that humans are central to AI’s impact. Visibility, adaptability, and human judgment matter the most. Technology alone isn’t enough; real advantage comes from empowering people.
Selamat (Sophos): In the age of AI, it’s easy to focus on the flashiest technology, but tech only works alongside people and processes. Burnout affects employees and the businesses relying on them, so leaders must stay flexible and support psychological well-being.
In 2026, AI agents will bring greater efficiency and autonomy, making it crucial for stakeholders to align and accelerate ethical and regulatory frameworks for AI use.
Jyh Chong (ALE): Trust will remain central in 2026. AI will continue to advance, but only within the guardrails of sovereign and private environments.
The year (2026) will be defined not by what AI can do, but by where it’s allowed to operate, prioritising data privacy, regulatory compliance (such as NIS2) and Zero Trust principles.
- Tee Jyh Chong, SVP, Asia Pacific, Alcatel-Lucent Enterprise (ALE)
Smith (Smart): In regulated industries, customer demands and expectations go hand in hand with stricter compliance. AI can help connect knowledge, but siloed data, legacy systems, and tribal knowledge are constraints.
Success means unifying data to make it clean and trusted. That’s why organisations must choose the right use cases, which requires experimentation not blind adoption.
Xin (Schneider): Don’t underestimate what technology can achieve. AI is already reshaping the data centre industry, delivering clear gains in efficiency and sustainability.
In the year ahead, we expect companies to focus on streamlining energy sourcing, securing sustainable power, integrating green technologies and aligning with carbon-reduction goals.
The future of data centres is digital, electric and sustainable with AI as a key enabler alongside green energy pathways, advanced cooling technologies and strong governance standards.
